Patent Publication Number: US-11642784-B2

Title: Database construction for control of robotic manipulator

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims the benefit of U.S. Provisional Patent Application No. 63/032,168, filed May 29, 2020, which is incorporated by reference herein in its entirety. 
    
    
     BACKGROUND 
     Generally, robotic manipulators may be remotely operated via an interface to perform a task (such as a pick and place task). For example, the robotic manipulators may include anthropomorphic effectors (such as a humanoid robot). To control the anthropomorphic effectors, the interface may include an input device (such as a joystick) that may be configured to receive a fixed set of user inputs (such as a set of movements of the joystick). The fixed set of user inputs may include inputs related to only six degrees of freedom. Based on the limited number of user inputs, the interface may transmit limited control instructions (such as limited positional and orientational information associated with the task) to control the anthropomorphic effectors of the robotic manipulators. Because of such limitations of the interface, it may be difficult for an operator to communicate with and/or control the robotic manipulators using low-cost interfaces. Additionally, such interfaces may generate unnatural and inconsistent motion information for the robotic manipulators to execute the task. 
     Further, in order to perform a continuous transition (such as a human-like motion) of the task from the anthropomorphic effectors, the interface may require a complex structural design, to receive the user inputs for such continuous transition, which may eventually increase a cost of the interface. Therefore, there may be a need for a system which may use a cost-effective interface to effectively control the robotic manipulator (such as humanoid robot) to execute the task. 
     Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings. 
     SUMMARY 
     According to an embodiment of the disclosure, an electronic apparatus to construct a database to control a robotic manipulator is provided. The electronic apparatus may include a memory to store information associated with a task of a robotic manipulator. The electronic apparatus may further include circuitry which may be coupled with the memory. The circuitry may receive a first plurality of signals from a first plurality of sensors associated with a wearable device. The first plurality of signals may correspond to each of a first plurality of poses performed for the task using the wearable device. The circuitry may further apply a predefined model based on a first set of signals of the first plurality of signals for each of the first plurality of poses. The first set of signals may correspond to one or more positional and orientational coordinates of at least one part of the wearable device. The circuitry may further determine arrow direction information based on the application of the predefined model on the first set of signals for each of the first plurality of poses. The arrow direction information may relate to joint angle information for the robotic manipulator to perform the task. The circuitry may further aggregate the determined arrow direction information with information about the first set of signals to generate output information for each of the first plurality of poses. The circuitry may further control the memory to store the generated output information for each of the first plurality of poses performed for the task using the wearable device. 
     According to another embodiment of the disclosure, a method to construct a database to control a robotic manipulator is provided. The method may be performed in an electronic apparatus. The method may include receiving a first plurality of signals from a first plurality of sensors associated with a wearable device. The first plurality of signals may correspond to each of a first plurality of poses performed for a task using the wearable device. The method may further include applying a predefined model on a first set of signals of the first plurality of signals for each of the first plurality of poses. The first set of signals may correspond to one or more positional and orientational coordinates of at least one part of the wearable device. The method may further include determining arrow direction information based on the application of the predefined model on the first set of signals for each of the first plurality of poses. The arrow direction information may relate to joint angle information for a robotic manipulator to perform the task. The method may further include aggregating the determined arrow direction information with information about the first set of signals to generate output information for each of the first plurality of poses. The method may further include storing, in a memory, the generated output information for each of the first plurality of poses performed for the task using the wearable device. 
     According to an embodiment of the disclosure, an electronic apparatus having a database to control a robotic manipulator is provided. The electronic apparatus may include a memory to store output information for each of a first plurality of poses performed for a task using a wearable device. The output information may include arrow direction information associated with each of the first plurality of poses performed for the task. The electronic apparatus may further include circuitry coupled to the memory. The circuitry may receive a second plurality of signals from a second plurality of sensors associated with a handheld device. The second plurality of signals may correspond to each of a second plurality of poses performed for the task using the handheld device. The circuitry may further retrieve, from the memory, the stored output information corresponding to a third set of signals of the received second plurality of signals for each of the second plurality of poses. The third set of signals may correspond to one or more positional and orientational coordinates of at least one part of the handheld device. The circuitry may further extract the arrow direction information from the retrieved output information for each of the second plurality of poses. The circuitry may further transmit control instructions to a robotic manipulator to execute the task based on the extracted arrow direction information and the received second plurality of signals for each of the second plurality of poses performed for the task using the handheld device 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a block diagram that illustrates an exemplary network environment for a construction of a database to control a robotic manipulator, in accordance with an embodiment of the disclosure. 
         FIG.  2    is a block diagram that illustrates an exemplary electronic apparatus for a construction of a database to control a robotic manipulator, in accordance with an embodiment of the disclosure. 
         FIGS.  3 A- 3 B  are diagrams that collectively illustrate an exemplary arrangement of a wearable device that is associated with the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure. 
         FIG.  4    is a diagram that illustrates an exemplary scenario to perform a task using a wearable device that is associated with the electronic apparatus of  FIG.  1    to construct a database, in accordance with an embodiment of the disclosure. 
         FIG.  5    is a sequence diagram that illustrates exemplary operations for construction of a database for the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure. 
         FIG.  6    is a diagram that illustrates an exemplary visualization of arrow direction information determined by the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure. 
         FIG.  7    is a diagram that illustrates an exemplary scenario to perform a task using a handheld device that is associated with the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure. 
         FIG.  8    is a sequence diagram that illustrates exemplary operations for a control of a robotic manipulator using a database associated with the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure. 
         FIG.  9    is a diagram that illustrates an exemplary scenario for a control of a robotic manipulator using the electronic apparatus and the handheld device, in accordance with an embodiment of the disclosure. 
         FIG.  10    is a flowchart that illustrates exemplary operations for a construction of a database to control a robotic manipulator, in accordance with an embodiment of the disclosure. 
         FIG.  11    is a flowchart that illustrates exemplary operations for a control of a robotic manipulator through a database associated with the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure. 
     
    
    
     The foregoing summary, as well as the following detailed description of the present disclosure, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the preferred embodiment are shown in the drawings. However, the present disclosure is not limited to the specific methods and structures disclosed herein. The description of a method step or a structure referenced by a numeral in a drawing is applicable to the description of that method step or structure shown by that same numeral in any subsequent drawing herein. 
     DETAILED DESCRIPTION 
     The following described implementations may be found in a disclosed electronic apparatus for a construction of a database to control a robotic manipulator. Exemplary aspects of the disclosure may provide an electronic apparatus (such as a computing device) that may be configured to store information associated with a task (such as a pick and place task) of a robotic manipulator (such as an anthropomorphic robot). The electronic apparatus may receive a first plurality of signals (that may include a first set of signals that may correspond to positional and orientational coordinates) from a first plurality of sensors (such as Inertial Motion Unit (IMU) sensor) which may be associated with or positioned on a wearable device (such as an exoskeleton, a wearable jacket, a wearable pant, and the like). The wearable device may acquire the first set of signals based on a plurality of poses (including a first set of poses that may correspond to an effector pose) that may be performed by an operator for the task using the wearable device. The first plurality of sensors acquires each pose of the first set of poses from at least one part of the wearable device to form natural and consistent information of the task. 
     The electronic apparatus may further apply a predefined model (such as Inverse Kinematics Algorithm and a Bayesian Interaction Primitive (BIP)) on the first set of signals. The electronic apparatus may further determine arrow direction information based on the application of the predefined model on the first set of signals for each of the first set of poses. The arrow direction information may relate to joint angle information for the robotic manipulator to perform the task, where the arrow direction information may be invariant from a number of joints or a structure associated with the robotic manipulator. Thus, the determined arrow direction information may be provided to any robotic manipulator irrespective of the number of joints or the structure associated with the robotic manipulator. 
     The electronic apparatus may further aggregate the determined arrow direction information with information about the first set of signals (and with object information indicating at least one of: a grasp force, a head pose, or an object pose) to generate output information for each of the first set of poses performed using the wearable device. The electronic apparatus may further control the memory to store the generated output information for each of the first set of poses performed for the task using the wearable device. The stored output information in the memory may form a database that may include information related to each pose of the first set of poses of the at least one part of the wearable device. Thus, the database may form natural and consistent information for the robotic manipulator to perform the task. 
     Therefore, the disclosed electronic apparatus may construct the database, such that, during a runtime operation of control (or teleoperation) of the robotic manipulator using a handheld device (such as cost-effective VR device or interface), the electronic apparatus may compare the first set of signals associated with the output information stored in the database, with signals associated with an effector pose performed for the task using the handheld device, and accordingly retrieve the stored arrow direction information (i.e. from the database) corresponding to the effector pose of the handheld device. Thus, the electronic apparatus may supplement the effector pose (or trajectories) of the handheld device (which may include six degrees-of-freedom (6-DOF)) with the stored arrow direction information (indicating at least one additional degree-of-freedom (1-DOF)), to form natural and consistent motions for the robotic manipulator which may be controlled (or teleoperated) by the cost-effective handheld device during runtime operation to perform the task (such as, but not limited to, a pick and place task). Details of the electronic apparatus for the construction of the database, and the control of the robotic manipulator using the cost-effective handheld device and the constructed database, are provided, for example, in  FIGS.  1 - 11   . 
     Reference will now be made in detail to specific aspects or features, examples of which are illustrated in the accompanying drawings. Wherever possible, corresponding, or similar reference numbers will be used throughout the drawings to refer to the same or corresponding parts. 
       FIG.  1    is a block diagram that illustrates an exemplary network environment for a construction of a database to control a robotic manipulator, in accordance with an embodiment of the disclosure. There is shown a network environment  100  which may include an electronic apparatus  102 . The electronic apparatus  102  may be communicatively coupled with a wearable device  104 , a server  106 , a handheld device  108 , and a robotic manipulator  110 , through a communication network  112 . The wearable device  104  may include a first plurality of sensors  104 A that may be configured to acquire poses performed using the wearable device  104 . The wearable device  104  may be worn by a user  114  during the construction of the database. The handheld device  108  may include a second plurality of sensors  108 A that may be configured to acquire poses performed using the handheld device  108  during runtime operations of the control (or teleoperation) of the robotic manipulator  110 . The handheld device  108  may be held or worn by the user  114  during the control of the robotic manipulator  110 . The robotic manipulator  110  may include an electronic controller  110 A to communicate with the electronic apparatus  102 . Modifications, additions, or omissions may be made to  FIG.  1    without departing from the scope of the present disclosure. For example, the network environment  100  may include more or fewer elements than those illustrated and described in the present disclosure. For instance, in some embodiments, the network environment  100  may not include the server  106 , without deviation from the scope of the disclosure. 
     The electronic apparatus  102  may include suitable logic, circuitry, interfaces and/or code that may be configured to store information associated with a task of the robotic manipulator  110 . For example, the task may relate to a pick and place task, which may include, but is not limited to, grasping an object, picking the object from a starting point, carrying the object towards a destination point, and placing the object at the destination point. The electronic apparatus  102  may also store information associated with other tasks for the robotic manipulator  110 , which may include, but not limited to, controlling a home-appliance (such as a vacuum machine), tele-operating a patient, and the like. The description of other types of tasks has been omitted from the disclosure for the sake of brevity. 
     The electronic apparatus  102  may be further configured to communicate between the wearable device  104  and the server  106 , through the communication network  112 , to construct the database. The construction of the database may primarily include, reception of signals from the first plurality of sensors  104 A associated with the wearable device  104 , and application of a predefined model on the received signals to generate output information (including arrow direction information) for storage in the database. Details of such construction are further described, for example, in  FIGS.  4 - 6   . 
     The electronic apparatus  102  may be further configured to communicate with the handheld device  108  and the robotic manipulator  110 , through the communication network  112 , to control the robotic manipulator  110  based on the constructed database. The control of the robotic manipulator  110  may primarily include, reception of signals from the second plurality of sensors  108 A associated with the handheld device  108 , compare the received signals with the output information of the constructed database, and transmit control instructions for the robotic manipulator  110  based on the comparison, to perform the task. Details of such control are further described, for example, in  FIGS.  7 - 9   . 
     In an embodiment, the electronic apparatus  102  may be a computing device, which may include, but not limited to, an automatic controller, a data processing machine, mainframe machine, a computer work-station, and the like. In yet another embodiment, the electronic apparatus  102  may be a handheld or a portable device. In such case, the examples of the electronic apparatus  102  may include, but are not limited to, a smartphone, a cellular phone, a mobile phone, and/or any electronic device with data processing and networking capabilities. In yet another embodiment, the electronic apparatus  102  may be implemented as a cloud server, which may be utilized to execute various operations through web applications, cloud applications, HTTP requests, repository operations, file transfer, and the like. Examples of the electronic apparatus  102  may include, but are not limited to, a database server, an event server, a file server, a web server, a media server, a content server, an application server, a mainframe server, or a combination thereof. In one or more embodiments, the electronic apparatus  102  may be implemented as a plurality of distributed cloud-based resources. 
     The wearable device  104  may include suitable logic, circuitry, and/or interfaces that may be configured to generate a first plurality of signals through the first plurality of sensors  104 A which may be associated with or positioned on the wearable device  104 . In some embodiments, the wearable device  104  may include a communication interface (not shown) or a processor (not shown) to communicate (for example, the generated first plurality of signals) with the electronic apparatus  102 , through the communication network  112 . In an embodiment, the first plurality of signals may correspond to each of a first plurality of poses performed for the task by the user  114  using the wearable device  104 . For example, the wearable device  104  may be worn by the user  114  and generate the first plurality of signals based on the first plurality of poses of the user  114 . In some embodiments, the wearable device  104  may be worn on a complete body of the user  114  or may cover certain body parts of the user  114 . For example, the wearable device  104  may be worn on an upper portion of the user  114 , or on a lower portion of the user  114 , or a combination of both. Details of such upper portion and the lower portion are further described, for example in  FIGS.  3 A- 3 B . Examples of the wearable device  104  may include, but not limited to, an exoskeleton, a wearable garment, a headgear, a glove, and the like. Details of the wearable device  104  are further described, for example, in  FIGS.  3 A- 3 B . 
     The first plurality of sensors  104 A associated with the wearable device  104  may include suitable logic, circuitry, and/or interfaces that may be configured to generate the first plurality of signals based the first plurality of poses of the user  114  performed using the wearable device  104 . For example, the first plurality of sensors  104 A may be communicatively coupled with the wearable device  104 , via a wired or wireless connection (not shown), and may further generate the first plurality of signals based on the first plurality of poses of the user  114  performed using the wearable device  104 . The first plurality of signals may include a first set of signals and a second set of signals. 
     The first set of signals may correspond to one or more positional and orientational coordinates of at least one part of the wearable device  104 . The at least one part of the wearable device  104  may relate to at least one effector of the wearable device  104 . Details of the at least one part of the wearable device  104  are further described, for example, in  FIG.  4   . The second set of signals may correspond to object information which may indicate at least one of: a grasp force, a head pose, or an object pose, for each of the first plurality of poses performed for the task using the wearable device  104 . The object information corresponding to the second set of signals may be received from the first plurality of sensors  104 A for a second set of poses of the first plurality of poses. The second set of poses may be different from the first set of poses (i.e. which may be indicated by the first set of signals). Details of the object information are further described, for example, in  FIG.  4   . 
     The first plurality of sensors  104 A may detect each pose of the first plurality of poses of the user  114 , to generate the first set of signals and the second set of signals of the first plurality of signals. The first plurality of sensors  104 A may detect at least one of: inertial motion information, force information, or optical motion information for each pose of the first plurality of poses. The inertial motion information and the optical motion information may include the one or more positional and orientational coordinates, associated with the at least one part of the wearable device  104 , for each of the first plurality of poses performed for the task by the user  114  using the wearable device  104 . The force information may be associated with the at least one part of the wearable device  104  for each of the first plurality of poses performed for the task. Upon generation of the first plurality of signals, the first plurality of sensors  104 A may be further configured to transmit the first plurality of signals, indicating at least one of: the inertial motion information, the force information, or the optical motion information, to the electronic apparatus  102  to determine the arrow direction information. Examples of the first plurality of sensors  104 A may include, but is not limited to, an inertial motion unit (IMU) sensor, a force sensor, an optical sensor, and the like. 
     The IMU sensor of the first plurality of sensors  104 A may include suitable logic, circuitry, and/or interfaces that may be configured to detect inertial motion information including the one or more positional and orientational coordinates, associated with the at least one part of the wearable device  104 , for each of the first plurality of poses performed for the task. For example, the inertial motion information may include at least one of, an angular rate or an angular orientation that may act on the IMU sensor during a movement (such as the first set of poses of the first plurality of poses) of the user  114  performed using the at least one part of the wearable device  104 . For example, the at least one part of the wearable device  104  may relate to at least one effector of the wearable device  104  that may perform the first set of poses of the first plurality of poses. The IMU sensor may generate the first set of signals that may correspond to the one or more positional and orientational coordinates of the first set of poses of the at least one effector of the wearable device  104 . The IMU sensor may be a combination of one of, an accelerometer, a gyroscope, and a magnetometer. Examples of the IMU sensor may include, but not limited to, a silicon Micro-Electro-Mechanical Systems (MEMS), a quartz MEMS, a Fiber Optic Gyro (FOG), a Ring Laser Gyro (RLG), and the like. 
     The force sensor of the first plurality of sensors  104 A may include suitable logic, circuitry, and/or interfaces that may be configured to detect force information associated with the at least one part of the wearable device  104  for each of the first plurality of poses performed for the task. For example, the force information may include at least one of, a tensile force, a compression force, a stress, a strain, or a change in pressure that may act on the force sensor during a movement (such as a second set of poses of the first plurality of poses) of the user  114  performed using the at least one part of the wearable device  104 . For example, the at least one part of the wearable device  104  may relate to the at least one effector of the wearable device  104  that may perform the second set of poses of the first plurality of poses. The force sensor may generate the second set of signals that may correspond to the object information, which includes at least one of, the grasp force, the head pose, or the object pose force corresponding to the second set of poses of the at least one part (such as the headgear, or the glove) of the wearable device  104 . Examples of the force sensor of the first plurality of sensors  104 A may include, but not limited to, a Load Cell, a Strain Gage, a Force Sensing Resistor (such as a piezo-resistive force sensor), and the like. 
     The optical sensor of the first plurality of sensors  104 A may include suitable logic, circuitry, and/or interfaces that may be configured to detect optical motion information comprising the one or more positional and orientational coordinates, associated with the at least one part of the wearable device  104 , for each of the first plurality of poses performed for the task. For example, the optical sensor may include an illuminator and a detector. The illuminator may illuminate a light beam on the wearable device  104 . The detector may be configured to detect a change in the light beam and may generate electric signals corresponding to the change in the light beam to generate the optical motion information. The generated optical motion information may relate to the positional and orientational coordinates of the first set of poses of the first plurality of poses performed for the task. In an embodiment, the generated optical motion information may also relate to the object information that may be associated with the second set of poses of the first plurality of poses. Examples of the optical sensor of the first plurality of sensors  104 A may include, but not limited to, a photoconductive sensor, a photovoltaic sensor, a photodiode sensor, a phototransistor, and the like. 
     In another embodiment, the first plurality of sensors  104 A may be remotely associated with the wearable device  104 . For example, the first plurality of sensors  104 A may include an image capturing device (not shown) to remotely detect the pose of the user  114 . The image capturing device may include suitable logic, circuitry, and/or interfaces that may be configured to capture one or more images that corresponds to the first plurality of poses of the user  114  performed using the wearable device  104 , to generate the first plurality of signals. Examples of the image capturing device may include, but are not limited to, an image sensor, a wide-angle camera, an action camera, a closed-circuit television (CCTV) camera, a camcorder, a digital camera, camera phones, a time-of-flight camera (ToF camera), a night-vision camera, and/or other image capture devices. In some embodiments, the electronic apparatus  102  may include a plurality of image capturing devices (not shown) arranged at different positions of surroundings of the wearable device  104  to capture the first plurality of poses. In some embodiments, the image capturing device may be a 360-degree camera which may be configured to capture a 360-degree view of the surroundings of the wearable device  104 . In accordance with an embodiment, the 360-degree camera may further include a plurality of image sensors (not shown) to capture the 360-degree view of the surroundings of the wearable device  104  to capture the first plurality of poses, and generate the first plurality of signals corresponding to the first plurality of poses. 
     The server  106  may include suitable logic, circuitry, interfaces and/or code that may be configured to store information associated with the predefined model. For example, the information associated with the predefined model on the server  106  may be applied on the first set of signals of the first plurality of signals for each of the first plurality of poses. The server  106  may be further configured to communicate to the electronic apparatus  102  (through the communication network  112 ) a result of the application of the predefined model on the first set of signals of the first plurality of signals. Based on the application of the predefined model on the first set of signals for each of the first plurality of poses, the server  106  may be configured to determine arrow direction information for the database. Details of the arrow direction information are further described, for example, in  FIG.  5   . 
     In an embodiment, the information associated with the predefined model may include a first algorithm and a second algorithm. The first algorithm may be applied on the first set of signals of the first plurality of signals to determine joint angle data for the robotic manipulator  110  to perform the task. In an embodiment, the first algorithm may be an inverse-kinematics algorithm that may be applied on the first set of signals of the first plurality of signals to determine the joint angle data for the robotic manipulator  110  to perform the task. For example, the inverse-kinematics algorithm may include a mathematical formulation (such as an iterative Newton-Raphson method or gradient-based optimization) that may be applied on the one or more positional and orientational coordinates associated with the first set of signals to determine the joint angle data for the robotic manipulator  110 . Thus, based on the first of signals associated with the first plurality of poses of at least one part of the wearable device  104 , the joint angle data may be determined for the robotic manipulator  110 . Although the inverse-kinematics algorithm is a straight-forward deterministic method (such as the mathematical formulation to determine the joint angle data), the determined joint angle data may be specific to the number of joints or the structure associated with the robotic manipulator  110 . In order to convert the joint angle data to be invariant from the number of joints or the structure associated with the robotic manipulator  110 , the second algorithm may be applied on the joint angle data. 
     The second algorithm may be applied on the joint angle data to determine that arrow direction information that may relate to the joint angle information for the robotic manipulator  110  to perform the task. In one example, the joint angle information may be a directional constraint that may be applied for each of the at least one effector of the robotic manipulator  110 . Based on such directional constraint for each of the at least one effector of the robotic manipulator  110 , the robotic manipulator  110  may avoid redundant degree-of-freedom (such as kinematic redundancy). In an embodiment, the second algorithm may be a Bayesian Interaction Primitive (BIP) that may be applied on the joint angle data to determine the arrow direction information. For example, the Bayesian Interaction Primitive (BIP) may include a statistical formulation (such as a conditional probability) that may be applied on the joint angle data to determine the arrow direction information. The determined arrow direction information may be invariant from the number of joints or the structure associated with the robotic manipulator  110 . Thus, the determined arrow direction information may be provided to any robotic manipulator irrespective of the number of joints or the structure associated with such robotic manipulator. 
     It may be noted that the Bayesian Interaction Primitive (BIP) may be presented merely as an example of a statistical model. The present disclosure may be also applicable to other types of statistical model, such as, but not limited to, a Look-up table Model, a Learning from Demonstration Model (LfD Model), a Hidden Markov Model (HMMs), a Gaussian Mixture Model (GMMs), and the like. The description of other types of statistical model has been omitted from the disclosure for the sake of brevity. 
     In another embodiment, the second algorithm may include a recurrent neural network (RNN) that may be configured to convert the joint angle data to the arrow direction information based on the application of artificial neural network on the joint angle data, which may be generated from the first algorithm. It may be noted that the Recurrent Neural Network (RNN) is presented merely as an example of the artificial neural network. The present disclosure may be also applicable to other types of artificial neural networks, such as, but not limited to, a Convolutional Neural Network (CNN), a Modular Neural Network, a Radial Basis Function Neural Network, a Feed-Forward Neural Network, and the like. The description of other types of the artificial neural network has been omitted from the disclosure for the sake of brevity. 
     In yet another embodiment, the second algorithm may include an artificially intelligent algorithm other than the recurrent neural network that may be configured to convert the joint angle data to the arrow direction information based on the application of such artificial neural network algorithm on the joint angle data. Examples of the artificially intelligent algorithm may include, but not limited to, a machine learning algorithm and a deep learning algorithm. In another embodiment, the second algorithm may deploy a plurality of learning techniques to convert the joint angle data to the arrow direction information. Examples of the learning techniques may include, but not limited to, a supervised learning technique, an unsupervised learning technique, an ensemble learning technique, or a fuzzy logic learning technique. 
     In yet another embodiment, the second algorithm may include electronic data, such as, for example, a software program, code of the software program, libraries, applications, scripts, or other logic or instructions for execution by a processing device, such as the circuitry  202 . The second algorithm may include code and routines configured to enable a computing device, such as the circuitry  202  to perform one or more operations for classification of one or more inputs into the arrow direction information. Additionally or alternatively, the second algorithm may be implemented using hardware including a processor, a microprocessor (e.g., to perform or control performance of one or more operations), a field-programmable gate array (FPGA), or an application-specific integrated circuit (ASIC). Alternatively, in some embodiments, the second algorithm may be implemented using a combination of hardware and software. 
     In yet another embodiment, the second algorithm may be a computational network or a system of artificial neurons, arranged in a plurality of layers, as nodes. The plurality of layers of the second algorithm may include an input layer, one or more hidden layers, and an output layer. Each layer of the plurality of layers may include one or more nodes (or artificial neurons, represented by circles, for example). Outputs of all nodes in the input layer may be coupled to at least one node of hidden layer(s). Similarly, inputs of each hidden layer may be coupled to outputs of at least one node in other layers of the second algorithm. Outputs of each hidden layer may be coupled to inputs of at least one node in other layers of the second algorithm. Node(s) in the final layer may receive inputs from at least one hidden layer to output a result. 
     In yet another embodiment, the second algorithm may be trained based on a stochastic model (such as the artificial neural network). The training may include one or more parameters of each node of a network associated with the second algorithm may be updated based on whether an output of the final layer for a given input matches a correct result based on a loss function for the second algorithm. The above process may be repeated for same or a different input till a minimal of loss function may be achieved and a training error may be minimized. Several methods for training are known in art, for example, gradient descent, stochastic gradient descent, batch gradient descent, gradient boost, meta-heuristics, and the like. 
     In an embodiment, the server  106  may be implemented as a cloud server, which may be utilized to execute various operations (such as application of the first algorithm and the second algorithm) through web applications, cloud applications, HTTP requests, repository operations, file transfer, and the like. Examples of the server  106  may include, but are not limited to, a database server, an event server, a file server, a web server, a media server, a content server, an application server, a mainframe server, or a combination thereof. In one or more embodiments, the server  106  may be implemented as a plurality of distributed cloud-based resources. In another embodiment, the server  106  may be a computing device, which may include, but not limited to, a mainframe machine, a computer work-station, and the like. In yet another embodiment, the server  106  may be a handheld or a portable device. In such case, the examples of the server  106  may include, but are not limited to, a smartphone, a cellular phone, a mobile phone, and/or any electronic device with data processing and networking capabilities. In another embodiment, the server  106  may be an integral part of the electronic apparatus  102 . The information associated with the predefined model may be directly stored in the electronic apparatus  102  and may be applied on the first set of signals of the first plurality of signals. Details of the integration of the predefined model in the electronic apparatus  102  is further described, for example in  FIG.  2   . 
     The handheld device  108  may include suitable logic, circuitry, and/or interfaces that may be configured to generate a second plurality of signals from the second plurality of sensors  108 A associated with or position on the handheld device  108 . In some embodiments, the handheld device  108  may include a communication interface (not shown) or a processor (not shown) to communicate (for example, the generated second plurality of signals) to the electronic apparatus  102 , through the communication network  112 . In an embodiment, the second plurality of signals may correspond to each of a second plurality of poses performed by the user  114  for the task using the handheld device  108 , to further control (or teleoperate) the robotic manipulator  110 . For example, the handheld device  108  may be held by the user  114  and may generate the second plurality of signals based on the second plurality of poses of the user  114 . In an embodiment, the second plurality of poses of the user  114  performed using the handheld device  108 , may correspond to the task to be performed by the robotic manipulator  110  based on control instructions provided by the electronic apparatus  102 . In an embodiment, the handheld device  108  may be include a monetary value (i.e. cost) that may be lower than a monetary value of the wearable device  104 . Thus, the handheld device  108  may be cost-effective compared to the wearable device  104 . Examples of the handheld device  108  may include, but not limited to, Virtual-Reality (VR) device, a headgear, a glove, and the like. Details of the VR device, the headgear, and the glove are further described, for example, in  FIG.  7   . 
     The second plurality of sensors  108 A associated with the handheld device  108  may include suitable logic, circuitry, interfaces and/or code, that may be configured to generate the second plurality of signals based the second plurality of poses of the user  114  performed using the handheld device  108 . For example, the second plurality of sensors  108 A may be communicatively coupled with the handheld device  108 , via a wired or wireless connection (not shown), and may further generate the second plurality of signals based on the second plurality of poses of the user  114  performed using the handheld device  108 . The second plurality of signals may include a third set of signals and a fourth set of signals. The third set of signals may correspond to one or more positional and orientational coordinates of at least one part of the handheld device  108 . The at least one part of the handheld device  108  may relate to at least one effector of the handheld device  108 . Details of the at least one part of the handheld device  108  are further described, for example, in  FIG.  7   . The fourth set of signals may correspond to object information which indicates at least one of: a grasp force, a head pose, or an object pose, for each of the second plurality of poses performed for the task using the handheld device  108 . Details of the object information are further described, for example, in  FIG.  7   . 
     The second plurality of sensors  108 A may detect each pose of the second plurality of poses of the user  114  performed using the handheld device  108 , to generate the third set of signals and the fourth set of signals of the second plurality of signals. The second plurality of sensors  108 A may detect at least one of: motion information or force information associated with the at least one part of handheld device  108  for each of the second plurality of poses performed for the task to generate the second plurality of signals. Upon generation of the second plurality of signals, the second plurality of sensors  108 A or the handheld device  108  may further transmit the second plurality of signals, indicating at least one of: the detected motion information or the force information, to the electronic apparatus  102  to retrieve (or infer) the output information stored in the database for further extraction of the arrow direction information. Examples of the second plurality of sensors  108 A may include at least one of, a motion sensor, a force sensor, an optical sensor, and the like. 
     The motion sensor of the second plurality of sensors  108 A may include suitable logic, circuitry, and/or interfaces that may be configured to detect motion information including the one or more positional and orientational coordinates, associated with the at least one part of the handheld device  108 , for each of the second plurality of poses performed for the task. For example, the motion information may include at least one of, an angular rate or an angular orientation that may act on the motion sensor during a movement (such as a third set of poses of the second plurality of poses) of the user  114  performed using the at least one part of the handheld device  108 . For example, the at least one part of the handheld device  108  may relate to at least one effector of the handheld device  108  that may perform the third set of poses of the second plurality of poses. The motion sensor may generate the third set of signals that may correspond to the one or more positional and orientational coordinates of the third set of poses of the at least one effector of the handheld device  108 . Examples of the motion sensor may include, but not limited to, an infrared sensor, an ultrasonic sensor, a microwave sensor, a tomographic sensor, a Passive Infra-Red (PIR) sensor, a camera, and the like. 
     The force sensor of the second plurality of sensors  108 A may include suitable logic, circuitry, and/or interfaces that may be configured to detect force information associated with the at least one part of the handheld device  108  for each of the second plurality of poses performed for the task. For example, the force information may include at least one of, a tensile force, a compression force, a stress, a strain, or a change in pressure that may act on the force sensor during a movement (such as a fourth set of poses of the second plurality of poses) of the user  114  performed using the at least one part of the handheld device  108 . For example, the at least one part of the handheld device  108  may relate to the at least one effector of the handheld device  108  that may perform the fourth set of poses of the second plurality of poses. The force sensor may generate the fourth set of signals that may correspond to the object information, which includes at least one of, the grasp force, the head pose, or the object pose force corresponding to the fourth set of poses of at least one part (such as the headgear, or the glove) of the handheld device  108 . Examples of the force sensor of the second plurality of sensors  108 A may include, but not limited to, a Load Cell, a Strain Gage, a Force Sensing Resistor (such as a piezo-resistive force sensor), and the like. 
     The optical sensor of the second plurality of sensors  108 A may include suitable logic, circuitry, and/or interfaces that may be configured to detect optical motion information comprising the one or more positional and orientational coordinates, associated with the at least one part of the handheld device  108 , for each of the second plurality of poses performed for the task. For example, the optical sensor may include an illuminator and a detector. The illuminator may illuminate a light beam on the handheld device  108 . The detector may be configured to detect a change in the light beam and may generate electric signals corresponding to the change in the light beam to generate the optical motion information. The generated optical motion information may relate to the positional and orientational coordinates of the third set of poses of the second plurality of poses performed for the task. In an embodiment, the generated optical motion information may also relate to the object information that may be associated with the fourth set of poses of the second plurality of poses. Examples of the optical sensor of the second plurality of sensors  108 A may include, but not limited to, a photoconductive sensor, a photovoltaic sensor, a photodiode sensor, a phototransistor, and the like. 
     The robotic manipulator  110  may include suitable structure, circuitry, and/or interfaces, that may be configured to execute the task (for example pick and place an object) for which control instructions are provided from the electronic apparatus  102 . The robotic manipulator  110  may be made of at least one effector (such as an arm) that may be configured to execute the task. In an embodiment, the robotic manipulator  110  may have an anthropomorphic structure (such as a humanoid form), with a shoulder clavicle and at least one elbow. The robotic manipulator  110  may be constructed in such a way that the robotic manipulator  110  may mimic the movement of the user  114  in real-time (using the handheld device  108 ). For example, the robotic manipulator  110  may include at least one rotary actuator to mimic the movement of the user  114 . Examples of the at least one rotary actuator may include, but not limited to, an electric actuator, a pneumatic actuator, a hydraulic actuator, a piezoelectric actuator, or an ultrasonic actuator. In order to mimic the movement of the user  114 , the at least one rotary actuator may require the control instructions associated with the movement of the user  114 . For example, the robotic manipulator  110  may receive the control instructions from the handheld device  108  directly or from the electronic apparatus  102  (including the database). In an embodiment, the robotic manipulator  110  may also receive the control instructions (such as the arrow direction information) from the constructed database, via the electronic apparatus  102 , in addition to the control instructions (such as positional and orientational coordinates) from the handheld device  108 . Examples of the robotic manipulator  110  may include, but not limited to, an open-loop manipulator, a parallel manipulator, or a hybrid manipulator. Details of the operations and control of the robotic manipulator  110  are further described, for example, in  FIGS.  8  and  9   . In an embodiment, the robotic manipulator  110  may include the electronic controller  110 A to communicate with the electronic apparatus  102 . 
     The electronic controller  110 A may include suitable logic, circuitry, interfaces, and/or code that may be configured to communicate with the electronic apparatus  102 , via the communication network  112 . The electronic controller  110 A may be a specialized electronic circuitry that may include an electronic control unit (ECU) processor to control different functions, such as, but not limited to, movement operations, communication operations, and data acquisition for the robotic manipulator  110 . The electronic controller  110 A may control the robotic manipulator  110  to execute the task (such as the pick and place task). The electronic controller  110 A may be configured to control a linear movement or an angular movement of the robotic manipulator  110  based on the control instructions received from the electronic apparatus  102 . The electronic controller  110 A may be a microprocessor. Other examples of the electronic controller  110 A may include, but are not limited to, an embedded device, a human-machine interface (HMI), a computer workstation, a handheld computer, a cellular/mobile phone, a portable consumer electronic (CE) device, a server, and other computing devices, which may communicate with the robotic manipulator  110  to execute the task. 
     The communication network  112  may include a communication medium through which the electronic apparatus  102 , the wearable device  104 , the server  106 , the handheld device  108 , and the robotic manipulator  110  may communicate with each other. The communication network  112  may be one of a wired connection or a wireless connection. Examples of the communication network  112  may include, but are not limited to, the Internet, a cloud network, a Wireless Fidelity (Wi-Fi) network, a Personal Area Network (PAN), a Local Area Network (LAN), or a Metropolitan Area Network (MAN). Various devices in the network environment  100  may be configured to connect to the communication network  112  in accordance with various wired and wireless communication protocols. Examples of such wired and wireless communication protocols may include, but are not limited to, at least one of a Transmission Control Protocol and Internet Protocol (TCP/IP), User Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), File Transfer Protocol (FTP), Zig Bee, EDGE, IEEE 802.11, light fidelity (Li-Fi), 802.16, IEEE 802.11s, IEEE 802.11g, multi-hop communication, wireless access point (AP), device to device communication, cellular communication protocols, and Bluetooth (BT) communication protocols. 
     In operation, the electronic apparatus  102  may receive inputs to construct a database (based on task performed using the wearable device  104 ), and further control the robotic manipulator  110  based on the task performed by the handheld device  108  and the constructed database. For the construction of the database, the electronic apparatus  102  may receive the first plurality of signals from the first plurality of sensors  104 A associated with the wearable device  104 . The first plurality of signals may correspond to each of the first plurality of poses performed for the task using the wearable device  104 . In an embodiment, the first plurality of sensors  104 A may generate the first plurality of signals based on the first plurality of poses performed for the task by the user  114  using the wearable device  104 . The first plurality of sensors  104 A may further transmit the generated first plurality of signals to the electronic apparatus  102 . The first plurality of signals are further described, for example, in  FIGS.  3 A- 3 B,  4 , and  5   . Based on the receipt of the first plurality of signals, the electronic apparatus  102  may apply the predefined model on the first set of signals of the first plurality of signals for each of the first plurality of poses performed using the wearable device  104 . The first set of signals may correspond to one or more positional and orientational coordinates of the at least one part (such as the at least one effector) of the wearable device  104 . For example, the electronic apparatus  102  may receive the predefined model from the server  106  and apply on the first set of signals of the first plurality of signals for each of the first plurality of poses. In other example, the electronic apparatus  102  may apply the predefined model that may be stored or integrated in the electronic apparatus. Details of the application of the predefined model are further described, in example, in  FIG.  5   . 
     In an embodiment, the predefined model may include the first algorithm (such as the inverse-kinematics algorithm) and the second algorithm (such as the Bayesian interaction primitive). The first algorithm may be applied on the first set of signals of the first plurality of signals to determine the joint angle data for the robotic manipulator  110  to perform the task. The second algorithm may be applied on the joint angle data to determine the arrow direction information that may relate to the joint angle information for the robotic manipulator  110  to perform the task. The electronic apparatus  102  may further determine the arrow direction information based on the application of the predefined model (such as the first algorithm and the second algorithm) on the first set of signals for each of the first plurality of poses. The arrow direction information may relate to the joint angle information for the robotic manipulator to perform the task. Details of the arrow direction information are further provided, for example, in  FIGS.  5  and  6   . The electronic apparatus  102  may be further configured to aggregate the determined arrow direction information with information about the first set of signals to generate output information for each of the first plurality of poses. For example, the electronic apparatus may combine the determined arrow direction information with the first set of signals (such as the positional and orientational coordinates) of the wearable device  104  to generate the output information. Upon generation of the output information, the electronic apparatus  102  may further store the generated output information to construct the database for each of the first plurality of poses performed for the task using the wearable device  104 . 
     For the control of the robotic manipulator  110  during runtime, the electronic apparatus  102  may receive the second plurality of signals from the second plurality of sensors  108 A associated with the handheld device  108 . In an embodiment, the second plurality of signals may correspond to each of the second plurality of poses performed for the task (such as the pick and place task) using the handheld device  108 . Details about the reception of the second plurality of signals are further described, for example, in  FIG.  7   . The electronic apparatus  102  may further retrieve the stored output information corresponding to the third set of signals of the received second plurality of signals for each of the second plurality of poses. In an embodiment, the third set of signals may correspond to one or more positional and orientational coordinates of at least one part of the handheld device  108 . Details about the retrieval of the stored output information corresponding to the third set of signals, are further described, for example in  FIG.  8   . The electronic apparatus  102  may further extract the arrow direction information from the retrieved output information for each of the second plurality of poses of the handheld device  108 . Details of the extraction of the arrow direction information are further described, for example in  FIG.  8   . The electronic apparatus  102  may further transmit control instructions to the robotic manipulator  110  to execute the task (such as the pick and place task) based on the extracted arrow direction information and the received second plurality of signals for each of the second plurality of poses performed for the task using the handheld device  108 . Details of the control instructions for the robotic manipulator  110  are further described, for example in  FIGS.  8  and  9   . 
       FIG.  2    is a block diagram that illustrates an exemplary electronic apparatus for a construction of a database to control a robotic manipulator, in accordance with an embodiment of the disclosure.  FIG.  2    is explained in conjunction with elements from FIG.  1 . With reference to  FIG.  2   , there is shown a block diagram  200  of the electronic apparatus  102 . The electronic apparatus  102  may include circuitry  202 , a memory  204 , a I/O device  206 , and a network interface  208 . The circuitry  202  may be coupled to the memory  204 , the I/O device  206 , and the network interface  208 , through wired or wireless connections of the communication network  112 . In an embodiment, the memory  204  may be configured to store information associated with a predefined model  204 A. The functions of the information associated with the predefined model  204 A stored in the memory  204  may be same as the functions of the information associated with the predefined model stored in the server  106  described, for example, in  FIG.  1   . The electronic apparatus  102  may be configured to communicate between the wearable device  104 , the handheld device  108 , and the robotic manipulator  110 , through the communication network  112 . 
     The circuitry  202  may include suitable logic, circuitry, and/or interfaces that may be configured to execute program instructions associated with different operations to be executed by the electronic apparatus  102 . For example, some of the operations may include, but are not limited to, reception of the first plurality of signals from the first plurality of sensors  104 A associated with the wearable device  104 , application of the predefined model on the first set of signals of the first plurality of signals for each of the first plurality of poses, determination of the arrow direction information based on the application of the predefined model on the first set of signals, aggregation of the determined arrow direction information with information about the first set of signals to generate output information, and control of the memory  204  (as the database) to store the generated output information for each of the first plurality of poses performed for the task using the wearable device  104 . The execution of such operations is further explained, for example, in  FIG.  5   . In another example, some of the operations may further include, but are not limited to, reception of the second plurality of signals from the second plurality of sensors  108 A associated with handheld device  108 , retrieval of the stored output information corresponding to the third set of signals of the received second plurality of signals for each of the second plurality of poses, extraction of the arrow direction information from the retrieved output information for each of the second plurality of poses, and transmission of the control instructions to the robotic manipulator  110  to execute the task based on the extracted arrow direction information and the received second plurality of signals for each of the second plurality of poses performed for the task using the handheld device  108 . The execution of such operations is further explained, for example, in  FIG.  8   . 
     The circuitry  202  may include any suitable special-purpose or general-purpose computer, computing entity, or processing device including various computer hardware or software modules and may be configured to execute instructions stored on any applicable computer-readable storage media (for example the memory  204 ). The circuitry  202  may be implemented based on a number of processor technologies known in the art. For example, the circuitry  202  may include a microprocessor, a microcontroller, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a Field-Programmable Gate Array (FPGA), or any other digital or analog circuitry configured to interpret and/or to execute program instructions and/or to process data. The circuitry  202  may include any number of processors configured to, individually or collectively, perform any number of operations of the electronic apparatus  102 , as described in the present disclosure. Examples of the circuitry  202  may include a Central Processing Unit (CPU), a Graphical Processing Unit (GPU), an x86-based processor, an x64-based processor, a Reduced Instruction Set Computing (RISC) processor, a Complex Instruction Set Computing (CISC) processor, and/or other hardware processors. 
     The memory  204  may include suitable logic, circuitry, interfaces, and/or code that may be configured to store the set of instructions executable by the circuitry  202 . The memory  204  may be configured to store the information associated with the task of the robotic manipulator  110 . For example, in case of the pick and place task, the information may include instructions to perform the task, such as, but not limited to, grasp the object, pick the object from the starting point, carry the object towards the destination point, and place the object at the destination point. The memory  204  may be further configured to store at least one of: the motion information, the force information, or the object information associated with the task. Details of the motion information, the force information, and the object information are further described, for example in  FIGS.  4  and  7   . The memory  204  may be further configured to store the predefined model. For example, the memory  204  may be configured to store the first algorithm (such as the inverse kinematics algorithm) and the second algorithm (such as the Bayesian Interaction Primitive (BIP)) for the electronic apparatus  102  to determine the arrow direction information. The memory  204  may be further configured to store the output information to form the constructed database that may be generated from the electronic apparatus  102  based on the determined arrow direction information. In an embodiment, the memory  204  may also be configured to store output information associated with each pose of different tasks (such as a task other than pick and place task). Examples of implementation of the memory  204  may include, but are not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Hard Disk Drive (HDD), a Solid-State Drive (SSD), a CPU cache, and/or a Secure Digital (SD) card. 
     The I/O device  206  may include suitable logic, circuitry, interfaces, and/or code that may be configured to receive user inputs and generate outputs in response to the received user inputs. The I/O device  206  may include various input and output devices, which may be configured to communicate with the circuitry  202 . Examples of the I/O device  206  may include, but are not limited to, a touch screen, a keyboard, a mouse, a joystick, a microphone, a display device, a speaker, and/or an image sensor. 
     The network interface  208  may include suitable logic, circuitry, and interfaces that may be configured to facilitate communication between the circuitry  202 , the first plurality of sensors  104 A associated with the wearable device  104 , the second plurality of sensors  108 A associated with the handheld device  108 , and the electronic controller  110 A associated with the robotic manipulator  110 , via the communication network  112 . The network interface  208  may be implemented by use of various known technologies to support wired or wireless communication of the electronic apparatus  102  with the communication network  112 . The network interface  208  may include, but is not limited to, an antenna, a radio frequency (RF) transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a coder-decoder (CODEC) chipset, a subscriber identity module (SIM) card, or a local buffer circuitry. The network interface  208  may be configured to communicate via wireless communication with networks, such as the Internet, an Intranet or a wireless network, such as a cellular telephone network, a wireless local area network (LAN), and a metropolitan area network (MAN). The wireless communication may be configured to use one or more of a plurality of communication standards, protocols and technologies, such as Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), wideband code division multiple access (W-CDMA), Long Term Evolution (LTE), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Wireless Fidelity (Wi-Fi) (such as IEEE 802.11a, IEEE 802.11b, IEEE 802.11g or IEEE 802.11n), voice over Internet Protocol (VoIP), light fidelity (Li-Fi), Worldwide Interoperability for Microwave Access (Wi-MAX), a protocol for email, instant messaging, and a Short Message Service (SMS). 
     Although in  FIG.  2   , it is shown that the electronic apparatus  102  includes the circuitry  202 , the memory  204 , the I/O device  206 , and the network interface  208 ; the disclosure may not be limiting and the electronic apparatus  102  may include more or less components to perform the same or other functions of the electronic apparatus  102 . Details of the other functions and the components have been omitted from the disclosure for the sake of brevity. The functions or operations executed by the electronic apparatus  102 , as described in  FIG.  1   , may be performed by the circuitry  202  to construct the database. The construction of the database is further explained, for example, in  FIGS.  3 A- 6   . 
       FIGS.  3 A- 3 B  are diagrams that collectively illustrate an exemplary arrangement of a wearable device that is associated with the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure.  FIGS.  3 A- 3 B  are explained in conjunction with elements from  FIG.  1    and  FIG.  2   .  FIG.  3 A  is a diagram that illustrates a front view of the wearable device  104 .  FIG.  3 B  is a diagram that illustrates a rear view of the wearable device  104 . With reference to  FIGS.  3 A- 3 B , there is shown an exemplary arrangement  300  of the wearable device  104  that is associated with the electronic apparatus of  FIG.  1   . The wearable device  104  may include an upper portion  302 A, a lower portion  302 B, a headgear  302 C, and a glove  302 D. In an embodiment, the wearable device  104  may include the first plurality of sensors  104 A, which may include a first set of sensors  304  and a second set of sensors  306 . The first set of sensors  304  and the second set of sensors  306  may be configured to detect the first plurality of poses of the user  114  and generate the first plurality of signals. It may be noted that the user  114  and the wearable device  104  shown in  FIGS.  3 A- 3 B  is merely an example. The present disclosure may be also applicable to other user such as people of different physical structure, genders, and age, without limiting the scope of the disclosure. Similarly, the present disclosure may be also applicable to other types or structure of the wearable devices or garments, without limiting the scope of the disclosure. 
     In an embodiment, the wearable device  104  may be the exoskeleton that may be worn by the user  114  to perform the first plurality of poses corresponding to the task. The exoskeleton may include a plurality of rigid shells forming at least one of the upper portion  302 A or the lower portion  302 B, which may be contoured corresponding to a structural profile (for example, a torso, or a leg) of the user  114 . Examples of the exoskeleton may include, but not limited to, an upper extremity exoskeleton that may be worn on the upper portion  302 A of the user  114 , a lower extremity exoskeleton that may be worn on the lower portion  302 B of the user  114 , and the like. 
     In another embodiment, the wearable device  104  may be the wearable garment that may be a textile product which may be worn by the user  114 . The wearable garment may be made of different combination of materials, for example textile, animal skin, or the like. In an embodiment, the wearable garment may be contoured corresponding to the structural profile (for example, a torso, or a leg) of the user  114  and form the at least one of the upper portion  302 A or the lower portion  302 B. Examples of the wearable garment may include, but are not limited to, a jacket, a blazer, a shirt, a trouser, an inner wear, a pant, or a combination. 
     In yet another embodiment, the wearable device  104  may include the headgear  302 C. The headgear  302 C may be communicably coupled with the wearable device  104 , via wired or wireless connection (not shown). Examples of the headgear  302 C may include, but are not limited to, a head mounted display (such as a virtual-reality headset, an optical head-mounted display, and the like), or a head mounted device (such as a head band, a head cap, and the like), or a helmet, and the like. 
     In yet another embodiment, the wearable device  104  may include the glove  302 D. The glove  302 D may be communicably coupled with the wearable device  104 , via wired or wireless connection (not shown). The second set of sensors  306  on the glove  302 D may be configured to capture the grasping force of the user  114  on an object (i.e. such as an object  406  in  FIG.  4    that may be picked and placed as the task from one position to another position). In an embodiment, the glove  302 D may be replaced by a portable handheld device (such as a virtual-reality device) to capture the grasping force of the user  114  on the object  406 . Examples of the glove  302 D may include, but not limited to, a fabric glove, a leather glove, and the like. 
     The first set of sensors  304  may include at least one of the IMU sensor or the optical sensor. In an embodiment, the at least one of the IMU sensor or the optical sensor may be positioned on at least one of, the upper portion  302 A or the lower portion  302 B of the wearable device  104 . The second set of sensors  306  may include at least one of the force sensor. In an embodiment, the at least one of the force sensor may be positioned on at least one part of the wearable device  104 . The details of the at least one part is explained further, for example, in  FIG.  4   . 
     It may be noted here that the positions, arrangements, or shapes of the first set of sensors  304  and the second set of sensors  306  shown in  FIGS.  3 A- 3 B  is merely an example. The present disclosure may be also applicable to other positions, arrangements, shapes, or structure of first set of sensors  304  and the second set of sensors  306 , without a deviation from scope of the disclosure. 
       FIG.  4    is a diagram that illustrates an exemplary scenario to perform a task using a wearable device that is associated with the electronic apparatus of  FIG.  1    to construct a database, in accordance with an embodiment of the disclosure.  FIG.  4    is explained in conjunction with elements from  FIG.  1   ,  FIG.  2   , and  FIGS.  3 A- 3 B . With reference to  FIG.  4   , there is shown an exemplary scenario  400  to perform the task using the wearable device  104  that is associated with the electronic apparatus  102 . The wearable device  104  may include at least one part  402  that may be configured to perform a first plurality of poses  404 A- 404 B. In one embodiment, the at least one part  402  may relate to an arm-part of the upper portion  302 A of the wearable device  104 . One skilled in the art may understand that the wearable device  104  may also include two or more arm-parts to perform the task, without a deviation from scope of the disclosure. In another embodiment, the at least one part  402  may relate to a leg-part of the lower portion  302 B of the wearable device  104 . One skilled in the art may understand that the wearable device  104  may also include two or more leg-parts to perform the task, without a deviation from scope of the disclosure. The first plurality of poses  404 A- 404 B may include a first pose  404 A and a second pose  404 B as shown in  FIG.  4   . In an embodiment, the first pose  404 A and the second pose  404 B may relate to the task (for example the pick and place task) associated with an object  406 . Based on the first plurality of poses  404 A- 404 B performed by the user  114  for the task, the first set of sensors  304  may be configured to detect the first plurality of poses and generate the first set of signals associated with the task performed using the wearable device  104 . In an embodiment, the first set of signals may relate to one or more positional and orientational coordinates of the at least one part  402  associated with the wearable device  104 . Further, based on the first plurality of poses  404 A- 404 B, the second set of sensors  306  may be configured to detect the second set of signals (i.e. object information such as, but not limited to, grasp force) associated with the task performed on the object  406  using the wearable device  104 . 
     The at least one part  402  of the wearable device  104  may be configured to perform the first plurality of poses  404 A- 404 B for the task. In an embodiment, the at least one part  402  of the wearable device  104  may include at least one effector  402 A of the wearable device  104  that performs the first set of poses of the first plurality of poses  404 . In another embodiment, the wearable device  104  may further include at least one effector  402 B in the lower portion  302 B of the wearable device  104  that may be configured to perform the first plurality of poses  404 A- 404 B for the task. The first set of signals (i.e. generated by the first set of sensors  304 ) may correspond to the one or more positional and orientational coordinates of the first set of poses of the at least one effector  402 A of the wearable device  104 . For example, the at least one effector may be an end effector of the wearable device  104  that may be configured to perform the first set of poses. Based on the first set of poses of the end effector of the wearable device  104 , the first set of signals may be generated from the first set of sensors  304  of the first plurality of sensors  104 A. 
     The first pose  404 A may correspond to an idle pose of the wearable device  104 . In the idle pose, the object  406  may be disposed on an object table  406 A as shown in  FIG.  4   . Based on the task to be performed, the user  114  may perform the second pose  404 B that may relate to picking the object  406 , as shown in  FIG.  4   . The second pose  404 B may correspond to an active pose of the wearable device  104 . In the active pose, the object  406  may be picked up from the object table  406 A. For example, when the second pose  404 B is performed, the first set of sensors  304  associated with the first plurality of sensors  104 A may generate the one or more positional and orientational coordinates of the at least one effector  402 A of the wearable device  104 . Simultaneously, when the second pose  404 B is performed, the second set of sensors  306  associated with the first plurality of sensors  104 A may generate the object information based on a movement of the at least one part  402  of the wearable device  104  or based on an applied grasp force by the at least one effector  402 A of the wearable device  104  on the object  406 . 
     The one or more positional and orientational coordinates may relate to a location of the at least one effector  402 A of the wearable device  104 . For example, when the user  114  performs the second pose  404 B using the wearable device  104 , the at least one part  402  of the wearable device  104  may be moved in six degrees-of-freedom (6-DOF) to perform the second pose  404 B. The one or more positional and orientational coordinates of the at least one effector  402 A related to the six degrees-of-freedom (6-DOF) may include, but not limited to, an allowability of movement of the at least one part  402  along the X-axis, Y-axis, Z-axis, a roll along the X-axis, a pitch along the Y-axis, and a yaw along the Z-axis. In an embodiment, the one or more positional and orientational coordinates of the at least one effector  402 A may be measured by at least one of, the IMU sensor, or the Optical sensor, of the first set of sensors  304 . In an embodiment, based on the IMU sensor, the electronic apparatus  102  may determine the inertial motion information for each pose of the first plurality of poses. The inertial motion information may include the one or more positional and orientational coordinates, associated with the at least one part of the wearable device  104 , for each of the first plurality of poses performed for the task by the user  114  using the wearable device  104 . 
     In an embodiment, the second set of signals (i.e. received from the second set of sensors  306 ) may relate to object information associated with the wearable device  104 . The object information may include information associated with the object  406 . For example, the object information may include at least one of: grasp force information, a head pose  408 , or an object pose  410  associated with the task performed on the object  406  using the wearable device  104 . The grasp force information may include information associated with the grasp force that may be applied by the at least one part  402  of the wearable device  104  on the object  406  to perform the task (for example, to hold the object  406 ). In an embodiment, the grasp force may be measured by the at least one of the force sensor in the second set of sensors  306 . 
     The head pose  408  may indicate information associated with the headgear  302 C (shown in  FIG.  3 A ). In an embodiment, the head pose  408  may correspond to one or more positional and orientational coordinates of a head of the user  114  that may be captured by the headgear  302 C, while performing the task. In an embodiment, the head pose  408  may be captured by a motion sensor  408 A associated with the headgear  302 C. The motion sensor  408 A of the headgear  302 C may include suitable logic, circuitry, and/or interfaces that may be configured to detect motion information including the one or more positional and orientational coordinates of the head of the user  114 , for each of the first plurality of poses performed for the task. For example, the motion information may include at least one of, an angular rate or an angular orientation that may act on the motion sensor  408 A during a movement (such as the second set of poses of the first plurality of poses) of the user  114  performed using the headgear  302 C. The motion sensor  408 A may generate the second set of signals that may correspond to the one or more positional and orientational coordinates of the second set of poses of the headgear  302 C. Examples of the motion sensor  408 A may include, but not limited to, an infrared sensor, an ultrasonic sensor, a microwave sensor, a tomographic sensor, a Passive Infra-Red (PIR) sensor, a camera, and the like. 
     The object pose  410  may be associated with the object  406 . In an embodiment, the object pose  410  may correspond to one or more positional and orientational coordinates of the object  406 , while performing the task. In an embodiment, the electronic apparatus  102  may utilize the head pose  408  to determine the object pose  410 . For example, in case the object  406  is disposed on the object table  406 A, an eye gaze from the user  114  may usually precede the first plurality of poses of the wearable device  104  to perform the task (such as picking the object  406 ). The eye gaze of the user  114  on the object  406  may be detected by the head pose  408  and the second set of signals (related to such head pose  408 ) may be transmitted to the electronic apparatus  102  through the headgear  302 C. Thus, based on the head pose  408 , the electronic apparatus  102  may determine the object pose  410  based on the received second set of signals included in the first plurality of signals. In another embodiment, the object pose  410  may also be directly measured from the force sensor associated with the second set of sensors  306 . 
     It may be noted that, the first pose  404 A and the second pose  404 B shown in  FIG.  4    is presented merely as an example for the first plurality of poses  404 A- 404 B. The first plurality of poses  404 A- 404 B may include only one pose or more than one pose to perform the task, without a deviation from scope of the disclosure. For the sake of brevity, only two poses (such as the first pose  404 A and the second pose  404 B) have been shown in  FIG.  4   . However, in some embodiments, there may be more than two poses to perform the task using the wearable device  104 , without limiting the scope of the disclosure. 
       FIG.  5    is a sequence diagram that illustrates exemplary operations for construction of a database by the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure.  FIG.  5    is explained in conjunction with elements from  FIG.  1   ,  FIG.  2   ,  FIGS.  3 A- 3 B , and  FIG.  4   . With reference to  FIG.  5   , there is shown an exemplary process flow  500  for the construction of the database by the electronic apparatus  102 . In an embodiment, the operations in the exemplary process flow  500  may be handled by the electronic apparatus  102  or the circuitry  202  associated with the electronic apparatus  102 . 
     At  502 , the first plurality of signals may be received. In an embodiment, the electronic apparatus may be configured to receive the first plurality of signals from the first plurality of sensors  104 A associated with the wearable device  104 . The first plurality of signals may correspond to each of the first plurality of poses (such as the first plurality of poses  404 A- 404 B shown in  FIG.  4   ) performed for the task using the wearable device  104 . The first plurality of signals may be generated with the first plurality of sensors  104 A (such as the first set of sensors  304  and the second set of sensors  306  on the wearable device  104  shown in  FIGS.  3 A- 3 B and  4   ) for different poses performed by the user  114  for the task (for example shown in  FIG.  4    to pick the object  406 ). For example, the first plurality of signals may correspond to at least one of effector pose information  502 A, head pose information  502 B, grasp force information  502 C, and object pose information  502 D. 
     The effector pose information  502 A may be associated with the first set of poses of the at least one part  402  of the wearable device  104 . In an embodiment, the effector pose information  502 A may include the one or more positional and orientational coordinates (or pose) of the at least one effector  402 A of the wearable device  104 . The head pose information  502 B may be associated with the head pose  408  of the user  114  wearing the headgear  302 C (shown in  FIG.  4   ). In an embodiment, the head pose information  502 B may correspond to the one or more positional and orientational coordinates of the head of the user  114 , that may be captured by the headgear  302 , while performing the task. The grasp force information  502 C may be associated with the grasp force that may be applied by the at least one part  402  of the wearable device  104  on the object  406  to perform the task (for example, the grasp force applied to hold the object  406 ). The object pose information  502 D may be associated with the object pose  410  of the object  406 . In an embodiment, the object pose  410  may correspond to the one or more positional and orientational coordinates of the object  406 , while performing the task. In other words, the object pose information  502 D may indicate the pose of the object  406  while performing the first plurality of poses (such as the first pose  404 A and the second pose  404 B shown in  FIG.  4   ) of the task (for example picking the object  406 ). 
     At  504 , the predefined model may be applied. In an embodiment, the electronic apparatus  102  may be configured to apply the predefined model on the first set of signals of the first plurality of signals for each of the first plurality of poses  404 A- 404 B. The first set of signals may correspond to the one or more positional and orientational coordinates of the at least one effector  402 A of the wearable device  104 . In other words, the first set of signals may be generated by at least one of the first plurality of sensors  104 A that may be configured to detect the pose (or positions and/or orientations) of the at least one part  402  of the wearable device  104 . Thus, the first set of signals may correspond to the effector pose information  502 A as shown in  FIG.  5   . In an embodiment, the predefined model may include the first algorithm and the second algorithm. 
     At  504 A, the first algorithm may be applied. In an embodiment, the electronic apparatus  102  may be configured to apply the first algorithm on the first set of signals of the first plurality of signals to determine joint angle data for the robotic manipulator  110  (shown in  FIG.  1   ) to perform the task. In an embodiment, the first algorithm may relate to the inverse kinematics algorithm, where the inverse kinematics algorithm may analyze the first set of signals to determine the joint angle data, for the robotic manipulator  110  to perform the task. In an embodiment, the inverse-kinematics algorithm may include a mathematical formulation (such as the iterative Newton-Raphson method or the Gradient-based optimization) that may be applied on the one or more positional and orientational coordinates associated with the first set of signals to determine the joint angle data for the robotic manipulator  110 . For example, in order to apply either the iterative Newton-Raphson method or the Gradient-based optimization of the inverse kinematics algorithm, the electronic apparatus  102  may determine a Jacobian matrix associated with each of the one or more positional coordinates of the at least one effector  402 A of the wearable device  104 . 
     The Jacobian matrix (which may be denoted by a letter “J”) may relate to a matrix of at least one of: a linear velocity V n , and an angular velocity ω n  for each of the one or 
               Angular   ⁢         Velocity   ⁢         ξ     =       (             Linear   ⁢         Velocity     ,           V   n                 Angular   ⁢         Velocity     ,           ω   n           )     =     (           V   xn               V   yn               V   zn               ω   xn               ω   yn               ω   zn           )             
more positional and orientational coordinates of the at least one effector  402 A of the wearable device  104 . The “n” may denote the number of effectors of the robotic manipulator  110 . Based on the Jacobian matrix, the electronic apparatus  102  may determine an angular velocity ξ for an end effector of the robotic manipulator  110 . For example, a mathematical relation between the angular velocity ξ for the end effector of the robotic manipulator  110  and the angular velocity ω n  for each of the one of more positional and orientational coordinates of the at least effector of the robotic manipulator is mathematically expressed as mentioned below:
 
     From the above-mentioned mathematical expression, it may be noted that the V xn , V yn , and V zn , may relate to linear velocities for the at least one effector of the robotic manipulator  110  in the X-axis, Y-axis, and Z-axis, respectively. It may be further noted that the ω xn , ω yn , and ω zn , may relate to angular velocities for the at least one effector of the robotic manipulator  110  in the X-axis, Y-axis, and Z-axis, respectively. 
     In an embodiment, the electronic apparatus  102  may further determine a joint velocity {dot over (q)} for each of the one or more positional and orientational coordinates of the at least one effector  402 A. The joint velocity {dot over (q)} may be a vector that may describe a relative angular velocity of one segment joint to another joint. For example, the joint velocity {dot over (q)} may be mathematically expressed as below.
 
ω n =J{dot over (q)}
 
     From the above-mentioned mathematical expression, it may be noted that the joint velocity {dot over (q)} may be determined based on Jacobian matrix “J” and at least one of the angular velocities (such as the ω xn , ω yn , and ω zn ). Hence, based on the application of the inverse kinematics algorithm, the electronic apparatus may determine the joint angle data that relates to at least one of: the Joint linear velocity (such as V xn , V yn , and V zn ), the Joint angular velocity (such as ω xn , ω yn , and ω zn ), or the Joint velocity {dot over (q)}, for the at least one effector of the robotic manipulator  110 . 
     In an embodiment, the joint angle data may relate to information associated with angular orientations for each of the at least one effector of the robotic manipulator  110 . In one example, the joint angle data may relate to an angular configuration for each of the at least one effector of the robotic manipulator  110 . Based on such angular configuration for each of the at least one effector of the robotic manipulator  110 , the robotic manipulator  110  may control the at least one effector of the robotic manipulator  110  to execute the task. In another example, the joint angle data may relate to guidance information (such as, in case of the pick and place task, a guidance to select a shortest path to reach the object  406 ) for each of the at least one effector of the robotic manipulator  110 . Although the inverse-kinematics algorithm is a straight-forward deterministic method (such as the mathematical formulation to determine the joint angle data), the determined joint angle data may be specific to the number of joints or the structure associated with the robotic manipulator  110 . In order to convert the joint angle data to be invariant from the number of joints or the structure associated with the robotic manipulator  110 , the second algorithm may be applied on the joint angle data. 
     At  504 B, the second algorithm may be applied. In an embodiment, the electronic apparatus  102  may be configured to apply the second algorithm on the joint angle data to determine the arrow direction information that relates to the joint angle information for the robotic manipulator  110  to perform the task. In an embodiment, the electronic apparatus  102  may apply the second algorithm on the joint angle data, to transform the joint angle data into the arrow direction information. In an embodiment, the second algorithm may be the Bayesian Interaction Primitive (BIP) that may be applied on the joint angle data, to model the joint angle data, and transform the joint angle data into the arrow direction information, for the robotic manipulator  110  to perform the task. For example, the Bayesian Interaction Primitive (BIP) may include a statistical formulation (such as a conditional probability) that may be applied on the joint angle data to determine the arrow direction information. The determined arrow direction information may be invariant from the number of joints or the structure associated with the robotic manipulator  110 . Thus, the determined arrow direction information may be provided to any robotic manipulator irrespective of the number of joints or the structure associated with such robotic manipulator. In order to determine the arrow direction information that is invariant from the number of joints or the structure associated with the robotic manipulator  110 , the electronic apparatus  102  may deploy the statistical formulation (such as a Basis Function Decomposition) associated with the Bayesian Interaction Primitive (BIP). 
     The Basis Function Decomposition may be a process that may involve a conversion of the joint angle data that may be in a state space (such as time-dependent data) to the arrow direction information that may be in a time-invariant latent space (such as time-independent information). For example, the electronic apparatus  102  may receive the first plurality of signals from the first plurality of sensors  104 A associated with the wearable device  104  and also determine the object pose  410  based on the received head pose  408 . For each of the first plurality of signals and the determined object pose  410 , a value in the state space may be determined. The electronic apparatus  102  may further determine a weighted linear combination (such as a determination of weightage) for each of the value in the state space. Each of the values in the state space may be aggregated (such as grouped, or classified, or categorized, and the like) based on their weighted linear combination. The electronic apparatus  102  may further form a latent model based on the aggregated values of the state space. In the latent model, the electronic apparatus  102  may transform each of the aggregated values in the state space to each of aggregated values in the time-invariant space. The aggregation is further explained, for example, at  508  in  FIG.  5   . 
     At  506 , the arrow direction information may be determined. In an embodiment, the electronic apparatus  102  may determine the arrow direction information based on the application of the predefined model on the first set of signals for each of the first plurality of poses  404 A- 404 B performed for the task. The arrow direction information may indicate at least one additional degree-of-freedom (1-DOF) for the robotic manipulator  110  to form natural and consistent information, for the control of the robotic manipulator  110  to perform the task, even with the handheld device  108  that may be cost-effective. In an embodiment, the arrow direction information may relate to the joint angle information for the robotic manipulator  110  to perform the task. For example, based on the aggregated values in the time-invariant space of the latent model, the arrow direction information may be determined for the robotic manipulator  110 . As the aggregated values are in the time-invariant space, the determined arrow direction information is invariant from the number of joints or the structure associated with the robotic manipulator  110 . Thus, because of the time-invariant space of the latent model associated with the Bayesian Interaction Primitive, the electronic apparatus  102  may determine stable arrow direction information irrespective of the first plurality of poses of the wearable device  104 . In an embodiment, the arrow direction information may include a vector component that may correspond to directional information of the joint angle information. For example, the directional information may include information that may guide the robotic manipulator  110 . For instance, the directional information may include information to guide at least one of: the shoulder clavicle or the elbow associated with the robotic manipulator  110 . Details of such directional information are further explained, for example in  FIG.  6   . 
     In accordance with an embodiment, upon determination of the arrow direction, the second algorithm (such as BIP) of the predefined model may further compute weightage information associated with the first plurality of signals, the joint angle data, the joint angle information, and the arrow direction information for each of the plurality of poses (such as the first plurality of poses  404 A- 404 B). For example, the weightage information may relate to a weighted linear combination (such as a determination of individual weightage) for each of the first plurality of signals, the joint angle data, the joint angle information, and the arrow direction information for each of the plurality of poses (such as the first plurality of poses  404 A- 404 B). The electronic apparatus may then utilize the weightage information to aggregate (such as to group, or to classify, or to categorize, and the like) each value in the time-invariant state of the latent model. 
     At  508 , the determined arrow direction information may be aggregated. In an embodiment, based on the weightage information, the electronic apparatus  102  may be configured to aggregate (such as to group, or to classify, or to categorize, and the like) the determined arrow direction information with information about the first set of signals in the time-invariant state of the latent model to generate output information for each of the first plurality of poses  404 . In an embodiment, the electronic apparatus  102  may be configured to aggregate the determined arrow direction information with the information about the positional and orientational coordinates of the at least one effector  402 A of the first set of signals (i.e. which indicate the effector pose information  502 A), to generate the output information for each of the first plurality of poses  404 . In another embodiment, the electronic apparatus  102  may be further configured to aggregate the determined arrow direction information with the information about the first set of signals, and with the object information about the second set of signals, to generate the output information for each of the first plurality of poses. The object information may indicate at least one of: the head pose information  502 B, the grasp force information  502 C, and/or the object pose information  502 D shown in  FIG.  5   . For example, in order to generate the output information, the electronic apparatus  102  may apply an ensemble variant (such as a Monte Carlo Ensemble) of the Bayesian Interaction Primitive (BIP) on the weightage information associated with the determined arrow direction information and the first set of signals. The Monte Carlo Ensemble may be a two-step recursive filter that may include a prediction of the weightage information associated with the determined arrow direction information and the first set of signals for the aggregation, and update of the aggregated values in the latent model based on the prediction. The electronic apparatus  102  may also apply the BIP to determine a future phase (such as a look-ahead) prediction based on the aggregated weightage information. In case of look-ahead prediction, a confidence level (such as a probability of errors) may be less. However, in such look-ahead prediction of the electronic apparatus, the electronic apparatus  102  may transmit control instructions for the robotic manipulator  110  in real-time. 
     At  510 , the output information may be generated. In an embodiment, the electronic apparatus  102  may be configured to generate output information for each of the first plurality of poses  404 A- 404 B. For example, the output information may be generated based on the aggregation of the arrow direction information, information associated with the first set of signals (i.e. effector pose information  502 A) and the second set of signals (i.e., the object information that may indicate at least one of: the head pose information  502 B, the grasp force information  502 C, and/or the object pose information  502 D shown in  FIG.  5   ). For example, the output information may be an encoded data or compressed data for the combination of the arrow direction information, effector pose information  502 A, and the object information that may indicate at least one of: the head pose information  502 B, the grasp force information  502 C, and/or the object pose information  502 D. 
     At  512 , the generated output information may be stored. In an embodiment, the electronic apparatus  102  may be configured to control the memory  204  to store the generated output information for each of the first plurality of poses  404 A- 404 B performed for the task using the wearable device  104 . In an embodiment, the stored output information may include at least one of: arm configuration information associated with the upper portion  302 A of the wearable device  104 , or gait configuration information associated with the lower portion  302 B of the wearable device  104 . The at least one of the arm configuration information or the gait configuration information may relate to the joint angle information for the robotic manipulator to perform the task. For example, the arm configuration information may include information related to each arm (such as the at least one effector  402 A) in the upper portion  302 A of the wearable device  104 . In another example, the gait configuration information may include information related to each link (such as the at least one effector  402 B) in the lower portion  302 B of the wearable device  104  In accordance with an embodiment, the stored output information (as shown as  514 A in  FIG.  5   ) in the memory  204  for each of the first plurality of poses  404 A- 404 B may form a database  514 , as shown in  FIG.  5   . Therefore, the disclosed electronic apparatus  102  may control the memory  204  (the database  514 ) to store the output information (i.e. that may indicate the arrow direction information as an additional degrees-of-freedom (1-DOF) for each pose performed by the user  114  using the wearable device  104 . Such additional DOF may be retrieved or inferred from the database  514  by the disclosed electronic apparatus  102 , to control the robotic manipulator  110  to perform the task during the runtime, based on similar poses performed by the user  114  using the handheld device  108  (i.e. low-cost interface). Details of the retrieval of the output information from the database to control the robotic manipulator  110  are further described, for example, in  FIGS.  7  and  8   . 
       FIG.  6    is a diagram that illustrates an exemplary visualization of arrow direction information determined by the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure.  FIG.  6    is explained in conjunction with elements from  FIG.  1   ,  FIG.  2   ,  FIGS.  3 A- 3 B ,  FIG.  4   , and  FIG.  5   . With reference to  FIG.  6   , there is shown an exemplary visualization  600  of the arrow direction information included in the output information, generated for the database as described, for example, in  FIG.  5   . In the exemplary visualization  600 , there is shown an elbow arrow direction  602 A and a shoulder arrow direction  602 B. The determined arrow direction information may include elbow arrow direction information and shoulder arrow direction information. The elbow arrow direction information may be associated with an elbow  604  of the robotic manipulator  110 . For example, the elbow arrow direction information may indicate joint angle direction (such as the elbow arrow direction  602 A) for the elbow  604  of the robotic manipulator  110  for the execution of the task for a particular pose. The shoulder arrow direction information may be associated with a shoulder clavicle  606  of the robotic manipulator  110 . The shoulder arrow direction information may indicate joint angle direction (such as the shoulder arrow direction  602 B) for the shoulder clavicle  606  of the robotic manipulator  110  for the execution of the task for a particular pose. Description of the angular directions or movement of the elbow  604  and the shoulder clavicle  606  are further described, for example, in  FIG.  9   . 
       FIG.  7    is a diagram that illustrates an exemplary scenario to perform a task using a handheld device that is associated with the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure.  FIG.  7    is explained in conjunction with elements from  FIG.  1   ,  FIG.  2   ,  FIGS.  3 A- 3 B ,  FIG.  4   ,  FIG.  5   , and  FIG.  6   . With reference to  FIG.  7   , there is shown an exemplary scenario  700  to perform the task using the handheld device  108  that is associated with the electronic apparatus  102 . The handheld device  108  may include at least one part  702  that may be configured to perform a second plurality of poses  704 A- 704 B. The second plurality of poses  704 A- 704 B may include a first pose  704 A and a second pose  704 B as shown in  FIG.  7   . In an embodiment, the first pose  704 A and the second pose  704 B may be performed using the handheld device  108 . Based on the second plurality of poses  704 A- 704 B, the second plurality of sensors  108 A may be configured to generate the second plurality of signals for each of the second plurality of poses  704 A- 704 B performed for the task using the handheld device  108 . The second plurality of signals may include a third set of signals. In an embodiment, the third set of signals may relate to one or more positional and orientational coordinates of at least one part  702  of the handheld device  108 . 
     The at least one part  702  of the handheld device  108  may include at least one effector  702 A of the handheld device  108  that performs the third set of poses of the second plurality of poses  704 A- 704 B to generate the third set of signals. The third set of poses may be related to the at least one effector  702 A and may be a sub-set of the second plurality of poses  704 A- 704 B performed by the user  114  using the handheld device  108 . The generated third set of signals may correspond to the one or more positional and orientational coordinates of the third set of poses of the at least one effector  702 A of the handheld device  108 . For example, the at least one effector  702 A may be an end effector of the handheld device  108  that may be configured to perform the third set of poses. Based on the third set of poses of the end effector of the handheld device  108 , the third set of signals may be generated from at least one the second plurality of sensors  108 A. 
     As shown in  FIG.  7   , the first pose  704 A may correspond to an idle pose of the handheld device  108 . In the idle pose, the at least one part  702  of the handheld device  108  may be held by the user  114 . Based on the predefined task, the user  114  may perform the second pose  704 B, where the information about the task may be stored in the electronic apparatus  102 . For example, the task may relate to picking the object  406 . 
     The second pose  704 B, shown in  FIG.  7   , may correspond to an active pose of the handheld device  108 . In the active pose, the at least one part  702  of the handheld device  108  held by the user  114  may be moved in accordance with the second pose  704 B. For example, based on the information (for example instructions) stored about the task, the user  114  may perform the second pose  704 B (i.e., picking the handheld device  108  in such a way to mimic the picking task of the object  406  as shown in  FIG.  4   ). For example, when the second pose  704 B is performed, the second plurality of sensors  108 A may generate the one or more positional and orientational coordinates (i.e. as the third set of signals) of the at least one effector  702 A of the handheld device  108 . Simultaneously, when the second pose  404 B is performed, the second plurality of sensors  108 A may further detect at least one of: the grasp force, the head pose, or the object pose performed for the task using the handheld device  108  based on a movement of the at least one part  702  of the handheld device  108 . 
     The one or more positional and orientational coordinates of at least one effector  702 A may relate to a location of the at least one part  702  of the handheld device  108 . For example, when the user  114  performs the second pose  704 B using the handheld device  108 , the at least one part  702  of the handheld device  108  may be moved in six degrees-of-freedom (6-DOF) to perform the second pose  704 B. The one or more positional and orientational coordinates of the at least one effector  702 A related to the six degrees-of-freedom (6-DOF) may include, but not limited to, an allowability of movement of the at least one part  702  along the X-axis, Y-axis, Z-axis, a roll along the X-axis, a pitch along the Y-axis, and a yaw along the Z-axis. In an embodiment, the one or more positional and orientational coordinates of the at least one effector  702 A may be measured by at least one of the Motion sensor, or the Optical sensor, of the second plurality of sensors  108 A. 
     Further, based on the second plurality of poses  704 A- 704 B, the second plurality of sensors  108 A may be further configured to detect the fourth set of signals associated with the task performed using the handheld device  108 . In an embodiment, the fourth set of signals may correspond to at least one of: a grasp force information, a head pose, or an object pose performed for the task using the handheld device  108 . The grasp force information may include information associated with the grasp force that may be applied to the at least one effector  702 A of the handheld device  108  to perform the task (for example, to hold the handheld device  108 ). In an embodiment, the grasp force may be measured by the at least one of the force sensor in the second plurality of sensors  108 A. 
     The head pose  706  may indicate information associated with the headgear  302 C (shown in  FIG.  3 A ). In an embodiment, the head pose  706  may correspond to one or more positional and orientational coordinates of the head of the user  114  that may be captured by the headgear  302 C, while performing the task. In an embodiment, the head pose  706  may be captured by the motion sensor  408 A associated with the headgear  302 C. The motion sensor  408 A may generate the fourth set of signals that may correspond to the one or more positional and orientational coordinates of the fourth set of poses of the headgear  302 C. 
     The object pose  708  may be associated with a pose for the object  406  (as shown in  FIG.  4   ). In an embodiment, the object pose  708  may be determined based on the head pose  706 . For example, in case the object  406  is disposed on the object table  406 A (as shown in  FIG.  4   ), an eye gaze from the user  114  may usually precede the second plurality of poses of the handheld device  108  to perform the task (i.e., picking the handheld device  108  in such a way to mimic the picking task of the object  406  as shown in  FIG.  4   ). The eye gaze of the user  114  may be detected by the head pose  706  and the fourth set of signals (related to such head pose  706 ) may be transmitted to the electronic apparatus  102  through the headgear  302 C. Thus, based on the head pose  706 , the electronic apparatus  102  may determine the object pose  708 . In another embodiment, the object pose  708  may also be directly measured from the force sensor associated with the second plurality of sensors  108 A. 
     It may be noted that, the first pose  704 A and the second pose  704 B shown in  FIG.  7    is presented merely as an example for the second plurality of poses  704 A- 704 B. The second plurality of poses  704 A- 704 B may include only one pose or more than one pose to perform the task, without deviation from the scope of the disclosure. For the sake of brevity, only two poses (such as the first pose  704 A and the second pose  704 B) have been shown in  FIG.  7   . However, in some embodiments, there may be more than two poses using the handheld device  108 , without limiting the scope of the disclosure. 
       FIG.  8    is a sequence diagram that illustrates exemplary operations for a control of a robotic manipulator using a database associated with the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure.  FIG.  8    is explained in conjunction with elements from  FIG.  1   ,  FIG.  2   ,  FIGS.  3 A- 3 B ,  FIG.  4   ,  FIG.  5   ,  FIG.  6   , and  FIG.  7   . With reference to  FIG.  8   , there is shown an exemplary process flow  800  for a control of the robotic manipulator  110  using the database  514  associated with or constructed by the electronic apparatus  102 . In an embodiment, the operations in the exemplary process flow may be handled by the electronic apparatus  102  or the circuitry  202  associated with the electronic apparatus  102 . 
     At  802 , the second plurality of signals may be received. In an embodiment, the electronic apparatus  102  may receive the second plurality of signals from the second plurality of sensors  108 A associated with the handheld device  108 . The second plurality of signals may correspond to each of the second plurality of poses (such as the second plurality of poses  704 A- 704 B) performed for the task using the handheld device  108 . For example, the second plurality of signals may correspond to at least one of, effector pose information  802 A, grasp force information  802 B, head pose information  802 C, and object pose information  802 D, as shown for example, in  FIG.  8   . 
     The effector pose information  802 A may be associated with the third set of poses of the at least one part  702  of the handheld device  108 . In an embodiment, the effector pose information  802 A may indicate, the one or more positional and orientational coordinates of the at least one effector  702 A of the handheld device  108 . The effector pose information  802 A may be indicated by the third set of signals received from the one of the second plurality of sensors  108 A of the handheld device  108 . 
     The grasp force information  802 B may include information associated with the grasp force that may be applied to the at least one effector  702 A of the handheld device  108  to perform the task (for example, to hold the handheld device  108 ). In an embodiment, the grasp force information  802 B may be measured by the at least one of the force sensor in the second plurality of sensors  108 A. 
     The head pose information  802 C may indicate information associated with the headgear  302 C (shown in  FIG.  3 A ). In an embodiment, the head pose information  802 C may correspond to one or more positional and orientational coordinates of the head of the user  114  that may be captured by the headgear  302 C, while performing the task. In an embodiment, the head pose information  802 C may be captured by the motion sensor  408 A associated with the headgear  302 C. The motion sensor  408 A may generate the fourth set of signals that may correspond to the one or more positional and orientational coordinates of the fourth set of poses of the headgear  302 C. 
     The object pose information  802 D may be associated with a pose for the object  406  (as shown in  FIG.  4   ). In an embodiment, the object pose information  802 D may be determined based on the head pose information  802 C. For example, in case the object  406  is disposed on the object table  406 A (as shown in  FIG.  4   ), an eye gaze from the user  114  may usually precede the second plurality of poses of the handheld device  108  to perform the task (i.e., picking the handheld device  108  in such a way to mimic the picking task of the object  406  as shown in  FIG.  4   ). The eye gaze of the user  114  may be detected by the head pose information  802 C and such head pose information  802 C (i.e. fourth set of signals included in the second plurality of signals) may be transmitted to the electronic apparatus  102  through the headgear  302 C. Thus, based on the head pose information  802 C, the electronic apparatus  102  may determine the object pose information  802 D. In another embodiment, the object pose information  802 D may also be directly measured from the force sensor associated with the second plurality of sensors  108 A. 
     In an embodiment, the second plurality of sensors  108 A may detect at least one of motion information or force information associated with the at least one part  702  of the handheld device  108  for each of the second plurality of poses  704 A- 704 B performed for the task. The second plurality of sensors  108 A may further transmit the second plurality of signals indicating at least one of: the motion information or the force information to the electronic apparatus  102 . The detected motion information may be at least one of: the effector pose information  802 A, head pose information  802 C, or the object pose information  802 D, of the at least one part  702  of the handheld device  108 . The detected force information may be the grasp force information  802 B of the at least one part  702  of the handheld device  108 . 
     At  804 , information about the third set of signals for each of the second plurality of poses  704 A- 704 B may be compared with the output information stored in the database  514  (or the memory  204 ) at  512  in  FIG.  5   . In an embodiment, the electronic apparatus  102  may be configured to compare the information about the generated third set of signals for each of the second plurality of poses  704 A- 704 B, with the output information stored in the memory  204  including the database  514 . The output information may be related to the first set of signals for each of the first plurality of poses  404 A- 404 B associated with the wearable device  104  and may be generated as described, for example, in  FIG.  5   . 
     In an embodiment, the information about the third set of signals may correspond to the one or more positional and orientational coordinates (i.e. effector pose information  802 A) of the at least one effector  702 A of the handheld device  108 . The information about the third set of signals (i.e. effector pose information  802 A) may be compared with the output information stored in the memory  204  and related to the first set of signals (i.e. effector pose information  502 A as described, for example, at  502 - 508  in  FIG.  5   ) for each of the first plurality of poses  404 A- 404 B. In other words, the information about the third set of signals (i.e. effector pose information  802 A of the at least one effector  702 A of the handheld device  108 ) may be compared with the effector pose information  502 A of the at least one effector  402 A of the wearable device  104  included in the stored output information for each of the first plurality of poses  404 A- 404 B. The inclusion of the effector pose information  502 A in the output information for each of the first plurality of poses  404 A- 404 B is described, for example, in  508  and  510  in  FIG.  5   . In an embodiment, the electronic apparatus  102  may retrieve the output information from the memory  204  (or the database) stored for each of the first plurality of poses  404 A- 404 B of the task, to perform the comparison with the effector pose information  802 A. In an embodiment, the electronic apparatus  102  may perform the comparison to identify whether the effector pose information  502 A stored in the output information for a particular pose of the effector of the wearable device  104  matches with the effector pose information  802 A of the at least one effector  702 A of the handheld device  108 , or not. The comparison may be performed to determine the output information stored in the memory  204  (or the database  514 ) for which the effector pose information  802 A of the effector of the handheld device  108  matches with the effector pose information  502 A of the effector of the wearable device  104 . The match may further indicate that a particular or current pose performed by the effector of the handheld device  108  matches with similar pose performed by the effector of the wearable device  104  (i.e. indicated in the determined output information including the effector pose information  502 A). 
     At  806 , the output information may be retrieved based on the comparison. In an embodiment, the electronic apparatus  102  may retrieve, from the memory  204  (or the database  514 ), the stored output information that may be determined based on the comparison at  804  in  FIG.  8   . The retrieved output information from the memory  204  may indicate a match between the effector pose information  802 A (of the at least one effector  702 A of the handheld device  108 ), and the effector pose information  502 A (i.e. included in the determined output information) of the effector of the wearable device  104 . Thus, the retrieved output information may correspond to the third set of signals which indicate the effector pose information  802 A and included in the received second plurality of signals for a particular pose of the second plurality of poses  704 A- 704 B performed by the user  114  using the handheld device  108 . Similarly, the electronic apparatus  102  may be configured to determine and retrieve the output information for each of the second plurality of poses  704 A- 704 B based on the comparison (as described, for example, at  804 ). In an embodiment, the comparison (at  804 ) and the retrieval (at  806 ) of the stored output information may be referred as an inference process of the output information from the constructed database  514 , based on the second plurality of signals received from the handheld device  108  (i.e. at  802  in  FIG.  8   ). 
     At  808 , the arrow direction information may be extracted. In an embodiment, the electronic apparatus  102  may be configured to extract the arrow direction information from the retrieved output information (i.e. determined at  804  in  FIG.  8   ) for a particular pose of the second plurality of poses  704 A- 704 B performed using the handheld device  108  (as described, for example, in  FIG.  7   ). In an embodiment, the second plurality of signals received from the second plurality of sensors  108 A may correspond to six degrees-of-freedom (6-DOF) of the handheld device  108  (i.e. low-cost interface). The extracted arrow direction information from the database  514  may correspond to at least one degree-of-freedom (1-DOF), which may be different from the 6-DOF of the handheld device  108 . The at least one degree-of-freedom (1-DOF) indicated by the arrow direction information (i.e. extracted from the database  514 ) may be an additional degree-of-freedom (DOF) that may be required by the robotic manipulator  110  to perform the task, where only six degrees-of-freedom (6-DOF) poses are performed by the handheld device  108  for the task. Thus, the additional degree-of-freedom (DOF) extracted or inferred from the database  514  for a similar pose (i.e. performed by the wearable device  104 ) may supplement missing information (i.e. missing from 6-DOF of the handheld device  108 ) for the effective control of the robotic manipulator  110  (i.e. humanoid robot). The control of the robotic manipulator  110  using the handheld device  108  is further described, for example, in  FIG.  9   . The electronic apparatus  102  may similarly extract the arrow direction information from the retrieved output information (i.e. determined at  804  in  FIG.  8   ) for each of the second plurality of poses  704 A- 704 B performed using the handheld device  108  to control or teleoperate the robotic manipulator  110 . 
     In addition to the extraction of the arrow direction information, the electronic apparatus  102  may also extract the at least one of: the grasp force information  502 C, or the object pose information  502 D that may be stored in the output information (i.e. retrieved at  806 ) of the database  514 . Based on the at least one of: the grasp force information  502 C or the object pose information  502 D, the electronic apparatus  102  may reduce an error in extraction of the at least one additional degree-of-freedom (1-DOF) from the database  514  through the handheld device  108 . Further, the extracted at least one of: the grasp force information  502 C or the object pose information  502 D, may also be utilized to provide effective control instructions for the robotic manipulator  110  (i.e. humanoid robot). Details of the control of the robotic manipulator  110  using the handheld device  108  are further described, for example, in  FIG.  9   . 
     At  810 , a third algorithm may be applied on the extracted arrow direction information. In an embodiment, the electronic apparatus  102  may be configured to apply the third algorithm (for example, stored in the server  106  or in the memory  204 ), on the extracted arrow direction information to generate the control instructions for the robotic manipulator  110 . For example, the third algorithm may include an inverse kinematics algorithm. The electronic apparatus  102  may be configured to apply the inverse kinematics algorithm on the extracted arrow direction information to generate the control instructions for the robotic manipulator  110 . For example, the inverse kinematics algorithm may analyze the extracted arrow direction information to determine the control instructions including at least one additional degree-of-freedom (1-DOF), for the robotic manipulator  110  to perform the task. In an embodiment, the inverse-kinematics algorithm may include a mathematical formulation (such as the iterative Newton-Raphson method or the Gradient-based optimization) that may be applied on the extracted arrow direction information to determine the control instructions including at least one additional degree-of-freedom (1-DOF), for the robotic manipulator  110  to perform the task. Details of the control instructions for the robotic manipulator  110  are further described, for example in  FIG.  9   . 
     At  812 , the control instructions may be transmitted to the robotic manipulator  110  to execute the task. In an embodiment, the electronic apparatus  102  may be configured to transmit the control instructions to the robotic manipulator  110  to execute the task, based on the extracted arrow direction information (i.e. at least one additional degree-of-freedom (1-DOF)) and the received second plurality of signals (i.e. six degrees-of-freedom (6-DOF)) for each of the second plurality of poses  704 A- 704 B performed for the task using the handheld device  108 . The arrow direction information (i.e. described, for example, in  FIG.  6   ) may be extracted or inferred from the database  514  which is constructed based on the first plurality of poses  404 A- 404 B performed for the same task using the wearable device  104 , as described, in  FIGS.  4  and  5   . 
     At  814 , the robotic manipulator  110  may be controlled. In an embodiment, the electronic controller  110 A of the robotic manipulator  110  may be configured to control the robotic manipulator  110  based on the control instructions received from the electronic apparatus  102 . Description of the control of the robotic manipulator  110  is further described, for example, in  FIG.  9   . 
     In accordance with an embodiment, as described at  804  in  FIG.  8   , in case of mismatch between the information about the third set of signals (i.e. effector pose information  802 A of a particular pose of the effector of the handheld device  108 ) and the stored effector pose information  502 A in the output information for each of the first plurality of poses  404 A- 404 B performed by the effector of the wearable device  104 , the electronic apparatus  102  may retrieve the output information of nearest pose match from the database  514 . The mismatch between the effector pose information  802 A of the particular pose of the effector of the handheld device  108  with the effector pose information  502 A included in the stored output information in the database  514  may be referred as a failure of the inference process described at  804  and  806  of  FIG.  8   . For example, the nearest pose match may indicate nearest value of the positional and orientational coordinates of the at least one effector  402 A of the wearable device  104  (i.e. mentioned by the effector pose information  502 A in the stored output information in the database  514 ) which may match with the positional and orientational coordinates (i.e. effector pose information  802 A) of the at least one effector  702 A for a particular pose performed using the handheld device  108 . The nearest value of the positional and orientational coordinates of the at least one effector  402 A may refer to a different pose of the first plurality of poses  404 A- 404 B in the stored database  514 , which may be substantially similar to the particular pose (i.e. indicated in the third set of signals) performed by the effector of the handheld device  108 . The electronic apparatus  102  may further extract the arrow direction information (as described, for example, at  808 ) from the output information related to the nearest value of the positional and orientational coordinates of the at least one effector  402 A (i.e. effector pose information  502 A) of one of the first plurality of poses  404 A- 404 B performed by the effector of the wearable device  104 . 
     In some embodiments, the electronic apparatus  102  may identify, from the constructed database  514 , multiple nearest values of the positional and orientational coordinates of the at least one effector  402 A of the wearable device  104 , determine the output information, and extract the arrow direction information for each of the nearest value of the positional and orientational coordinates of the at least one effector  402 A (i.e. effector pose information  502 A). The determined output information and the extracted arrow direction information for each of the multiple nearest values may correspond to different poses of the effector of the wearable device  104  which may be substantially similar to the particular pose (i.e. indicated in the third set of signals) performed by the effector of the handheld device  108 . 
     The electronic apparatus  102  may be further configured to calculate mean information (i.e. mean or average value) of the arrow direction information for the multiple nearest values (i.e. effector pose information  502 A) in the retrieved output information corresponding to the different poses related to the first set of signals (i.e. which may indicate the effector pose information  502 A). The electronic apparatus  102  may further apply the third algorithm on the mean information of the arrow direction information to generate the control instructions for the control of the robotic manipulator  110 . Therefore, the disclosed electronic apparatus  102  may provide control instructions to the robotic manipulator  110  based on the calculation of the mean or average of the arrow direction information for the multiple nearest values of the positional and orientational coordinates of the at least one effector  402 A of the wearable device  104 , even though a particular or current pose of the effector of the handheld device  108  does not match with effector pose information  502 A stored in the database  514  for the first plurality of poses  404 A- 404 B of the wearable device  104 . 
       FIG.  9    is a diagram that illustrates an exemplary scenario for a control of a robotic manipulator using the electronic apparatus and the handheld device, in accordance with an embodiment of the disclosure.  FIG.  9    is explained in conjunction with elements from  FIG.  1   ,  FIG.  2   ,  FIGS.  3 A- 3 B ,  FIG.  4   ,  FIG.  5   ,  FIG.  6   ,  FIG.  7   , and  FIG.  8   . With reference to  FIG.  9   , there is shown an exemplary scenario  900  for the control of the robotic manipulator  110 . The exemplary scenario  900  shows a first pose  902 A and a second pose  902 B for the robotic manipulator  110 . In an embodiment, the first pose  902 A and the second pose  902 B may relate to the task associated with an object  906 . For example, the task may be to pick the object  906 . 
     The first pose  902 A may correspond to an idle pose of the robotic manipulator  110 . In the idle pose, the object  906  may be held by at least one effector  904  of the robotic manipulator  110 . The at least one effector  904  may further include a shoulder  904 A and an elbow  904 B. The shoulder  904 A and the elbow  904 B may be kinematically coupled with each other to form the at least one effector  904 . In an embodiment, the first pose  902 A of the robotic manipulator  110  may be controlled based on the first pose  704 A of the second plurality of poses  704 A- 704 B of the handheld device  108  and the control instructions provided by the electronic apparatus  102  based on the first pose  704 A. For example, in case the handheld device  108  is disposed at the first pose  704 A (such as the idle pose of the handheld device  108 ), the robotic manipulator  110  may also be disposed at the first pose  902 A (such as the idle pose of the robotic manipulator  110 ). 
     The second pose  902 B may correspond to an active pose of the robotic manipulator  110 . In the active pose, the object  906  may be moved to a location associated with the second pose  902 B, by at least one effector  904  of the robotic manipulator  110 . In an embodiment, the second pose  902 B of the robotic manipulator  110  may be controlled based on the second pose  704 B of the second plurality of poses  704 A- 704 B of the handheld device  108  and the control instructions provided by the electronic apparatus  102  based on the second pose  704 B. For example, in case the handheld device  108  is disposed at the second pose  704 B (such as the active pose of the handheld device  108 ), the electronic apparatus  102  may receive the second plurality of signals (i.e. related to the second pose  704 B) from the second plurality of sensors  108 A of the handheld device  108 , and may retrieve the output information corresponding to the received second pose  704 B from the database  514 , as described, for example, at  802 - 806  in  FIG.  8   . Further, the electronic apparatus may then apply the third algorithm (such as the inverse kinematics algorithm) to the extracted arrow direction information included in the retrieved output information to further generate the control instructions or signals for the robotic manipulator  110 , as described, for example, at  808 - 810  in  FIG.  8   . The electronic apparatus  102  may further transmit the generated control instructions to control the robotic manipulator  110  based on the second pose  704 B of the handheld device  108 . Based on the received control instructions from the electronic apparatus  102 , the electronic controller  110 A (i.e. shown in  FIG.  1   ) associated with the robotic manipulator  110 , may control the robotic manipulator  110  to move the at least one effector  904  to the location associated with or similar to the second pose  902 B (such as the active pose of the handheld device  108  held by the user  114 ). In an embodiment, the electronic apparatus  102  may transmit the control instructions to the robotic manipulator  110  in real-time without any lag in the transmission of the control instructions. For example, the control instructions may include the at least one additional degree-of-freedom (1-DOF) as the arrow direction information extracted from the constructed database  514 , and further include information/signals related to the six degrees-of-freedom (6-DOF) of the handheld device  108 , to control the robotic manipulator  110 . In another example, the control instructions may include at least one of: the head pose information  502 B, the grasp force information  502 C, or the object pose information  502 D extracted from the constructed database  514 , along with information/signals related to the six degrees-of-freedom (6-DOF) of the handheld device  108 , to control the robotic manipulator  110 . In yet another example, the control instructions may include the at least one additional degree-of-freedom (1-DOF) that may be extracted from the constructed database  514  as the arrow direction information, and further include the at least one of: the grasp force information  802 B, the head pose information  802 C, and the object pose information  802 C that may be directly received in the second plurality of signals from the handheld device  108 , to control the robotic manipulator  110 . 
     In another embodiment, the electronic apparatus  102  may receive the second plurality of signals from the second plurality of sensors  108 A associated with the handheld device  108 . The second plurality of signals may include the fourth set of signals as described, for example, in  FIG.  1   . The fourth set of signals may correspond to the object information, which may include at least one of: the grasp force, the head pose, or the object pose that may be performed for the task using the handheld device  108 . In an embodiment, the electronic apparatus  102  may compare information about the fourth set of signals for each of the second plurality of poses  704 A- 704 B, with the output information stored in the memory  204  of the database  514 . The output information may relate to the second set of signals (i.e. the object information associated with the wearable device  104 ) for each of the first plurality of poses  404 A- 404 B associated with the wearable device  104 . For example, the electronic apparatus  102  may compare the fourth set of signals with the second set of signals stored in the memory  204  including the database  514 . The four set of signals may correspond to the at least one of, the grasp force information  802 B, the head pose information  802 C, or the object pose information  802 D, which may be compared with the object information stored in the memory  204  including the database  514 . 
     The electronic apparatus  102  may further retrieve, from the memory  204  of the database  514 , the stored output information that may correspond to the fourth set of signals for each of the second plurality of poses  704 A- 704 B. The electronic apparatus  102  may further extract the at least one of the arrow direction information or the object information, from the retrieved output information for each of the second plurality of poses  704 A- 704 B (i.e. similar to extraction described at  808  in  FIG.  8   ). Based on the extracted arrow direction information or the object information, the electronic apparatus  102  may transmit the control instructions to the robotic manipulator  110  to execute the task based on the at least one of the extracted arrow direction information or the extracted object information, and based on the received second plurality of signals for each of the second plurality of poses  704 A- 704 B performed for the task using the handheld device  108 . 
     In accordance with an embodiment, the electronic apparatus  102  may further determine object trajectory information for the robotic manipulator  110  from the extracted object information, where the object trajectory information may be associated with the object  406  of the task. The object trajectory information may be based on at least one of: the second set of signals or the fourth set of signals, that corresponds to the task. In an embodiment, the object trajectory information may include information associated with a path of the at least one effector  904  of the robotic manipulator  110  to reach the object  406 . For example, the object trajectory information may relate to a shortest path for the at least one effector  904  of the robotic manipulator  110  to reach the object  406 . In another embodiment, the object trajectory information may further include information associated with a transmission path of the at least one effector  904  of the robotic manipulator  110 , to execute the task. For example, in case of pick and place task, the object trajectory information may relate to information associated with at least one of: picking the object  906  from a starting point, carrying the object  906  towards a destination point, and placing the object  906  at the destination point. 
     In an embodiment, the electronic apparatus  102  may further determine the grasp force information  802 B for the robotic manipulator  110  from the object information. The grasp force information  802 B may be associated with a force required to hold the object  906  for the task. The grasp force information  802 B may be based on at least one of: the second set of signals or the fourth set of signals, that corresponds to the task. 
     In an embodiment, the control instructions for the robotic manipulator  110  may include at least one of: arm configuration information, or gait configuration information for the robotic manipulator  110 . The at least one of the arm configuration information or the gait configuration information may relate to the joint angle information for the robotic manipulator  110  to perform the task. For example, the arm configuration information may include information related to each arm (such as the shoulder  904 A or the elbow  904 B), for the robotic manipulator  110 . In another example, the gait configuration information may include information related to each link (not shown) to control a gait (such as movement) of the robotic manipulator  110 . 
     In an embodiment, the electronic apparatus  102  may utilize the effector pose information  802 A to retrieve control instructions for the robotic manipulator. In another embodiment, the electronic apparatus  102  may utilize at least one of: the grasp force information  802 B, the head pose information  802 C, or the object pose information  802 D of the handheld device  108  to reduce errors in retrieving control instructions for the robotic manipulator  110 . The control instructions may correspond to at least one degree-of-freedom (1-DOF) as the inferred arrow direction information, which may be different from the 6-DOF of the handheld device  108 . The at least one degree-of-freedom (1-DOF) indicated by the control instructions may be an additional degree-of-freedom (1-DOF) that may be required by the robotic manipulator  110  to perform the task, where only six degrees-of-freedom (6-DOF) poses are performed by the handheld device  108  for the task. Thus, the control instructions including the additional degree-of-freedom (1-DOF) may supplement missing information (i.e. missing from 6-DOF of the handheld device  108 ) for the effective control of the robotic manipulator  110  (i.e. humanoid robot). 
     It may be noted here that the robotic manipulator  110  shown in  FIG.  9    is presented merely as an example. The present disclosure may also be applicable to other robotic manipulators (such as a robotic manipulator with two or more effector, or a bipedal robotic manipulator, and the like), without deviation from the scope of the disclosure. Further, one skilled in the art may understand the task (such as the pick and/or place task) and the poses (such as the first pose  902 A and the second pose  902 B) are presented merely as an example. The present disclosure may also be applicable to other tasks and other poses of the robotic manipulator  110 , without deviation from the scope of the disclosure. 
       FIG.  10    is a flowchart that illustrates exemplary operations for a construction of a database to control a robotic manipulator, in accordance with an embodiment of the disclosure. With reference to  FIG.  10   , there is shown a flowchart  1000 . The flowchart  1000  is described in conjunction with  FIGS.  1 ,  2 ,  3 A- 3 B,  4 ,  5 ,  6 ,  7 ,  8 , and  9   . The operations from  1002  to  1010  may be implemented, for example, by the electronic apparatus  102 , or the circuitry  202  of  FIG.  2   . The operations of the flowchart  1000  may start at  1002 . 
     At  1002 , the first plurality of signals may be received. In an embodiment, the electronic apparatus may be configured to receive the first plurality of signals from the first plurality of sensors  104 A associated with the wearable device  104 , as described, for example, in  FIGS.  1 ,  3 A,  3 B,  4   , and at  502  in  FIG.  5   . 
     At  1004 , the predefined model may be applied. In an embodiment, the electronic apparatus  102  may be configured to apply the predefined model on the first set of signals of the first plurality of signals for each of first plurality of poses (such as the first plurality of poses  404 A- 404 B). The predefined model may include the first algorithm (such as the inverse-kinematics algorithm) and the second algorithm (such as the Bayesian Interaction Primitive (BIP)), which may be applied on the first set of signals. The first set of signals may correspond to the one or more positional and orientational coordinates of at least one effector  402 A of the wearable device  104 , as described for example, in  FIGS.  1 ,  2   , and at  504  in  FIG.  5   . 
     At  1006 , the arrow direction information may be determined. In an embodiment, the electronic apparatus  102  may determine the arrow direction information based on the application of the predefined model on the first set of signals for each of the first plurality of poses  404 . The arrow direction information may relate to the joint angle information for the robotic manipulator  110  to perform the task, as described for example, in  FIGS.  1 ,  2 ,  6   , and at  506  in  FIG.  5   . 
     At  1008 , the determined arrow direction information may be aggregated with information about the first set of signals to generate the output information for each of the first plurality of poses. In an embodiment, the electronic apparatus  102  may be configured to aggregate the determined arrow direction information with information about the first set of signals to generate output information for each of the first plurality of poses  404 , as described for example, in  FIG.  1    and at  508  in  FIG.  5   . 
     At  1010 , the generated output information may be stored. In an embodiment, the electronic apparatus  102  may be configured to control the memory  204  (i.e. including the database  514 ) to store the generated output information for each of the first plurality of poses  404 A- 404 B performed for the task using the wearable device  104  as described for example, in  FIG.  1   , and at  510 ,  512  and  514  in  FIG.  5   . Control may pass to end. 
       FIG.  11    is a flowchart that illustrates exemplary operations for a control of a robotic manipulator through a database associated with the electronic apparatus of  FIG.  1   , in accordance with an embodiment of the disclosure. With reference to  FIG.  11   , there is shown a flowchart  1100 . The flowchart  1000  is described in conjunction with  FIGS.  1 ,  2 ,  3 A- 3 B,  4 ,  5 ,  6 ,  7 ,  8 ,  9 , and  10   . The operations from  1102  to  1108  may be implemented, for example, by the electronic apparatus  102 , or the circuitry  202  of  FIG.  2   . The operations of the flowchart  1000  may start at  1002 . 
     At  1102 , the second plurality of signals may be received. In an embodiment, the electronic apparatus  102  may receive the second plurality of signals from the second plurality of sensors  108 A associated with the handheld device  108 . The second plurality of signals may correspond to each of a second plurality of poses (such as the second plurality of poses  704 A- 704 B) performed for the task using the handheld device  108 , as described for example, in  FIGS.  1 ,  7   , and at  802  in  FIG.  8   . 
     At  1104 , the stored output information may be retrieved. In an embodiment, the electronic apparatus  102  may retrieve, from the memory  204  (i.e. the database  514 ), the stored output information that may correspond to the third set of signals of the received second plurality of signals for each of the second plurality of poses  704 A- 704 B. The third set of signals correspond to the one or more positional and orientational coordinates of the at least one effector  702 A of the handheld device  108 , as described for example, in  FIG.  1   , and at  804  and  806  in  FIG.  8   . 
     At  1106 , the arrow direction information may be extracted. In an embodiment, the electronic apparatus  102  may extract the arrow direction information from the retrieved output information for each of the second plurality of poses  704 A- 704 B, as described for example, in  FIG.  1   , and at  808  in  FIG.  8   . 
     At  1108 , the control instructions may be transmitted to the robotic manipulator  110 . In an embodiment, the electronic apparatus  102  may transmit the control instructions to the robotic manipulator  110  to execute the task based on the extracted arrow direction information and the received second plurality of signals for each of the second plurality of poses  704 A- 704 B performed for the task using the handheld device  108 , as described for example, in  FIG.  1   , at  810  and  812  in  FIG.  8   , and in  FIG.  9   . The control may pass to end. 
     Various embodiments of the disclosure may provide a non-transitory, computer-readable medium and/or storage medium, and/or a non-transitory machine readable medium and/or storage medium stored thereon, a set of instructions executable by a machine and/or a computer (for example the electronic apparatus  102 ) for the construction of the database  514 . The set of instructions may be executable by the machine and/or the computer (for example the electronic apparatus  102 ) to perform operations that may include reception of a first plurality of signals from a first plurality of sensors associated with a wearable device. The first plurality of signals may correspond to each of a first plurality of poses performed for the task using the wearable device. The operation may further include application of a predefined model on a first set of signals of the first plurality of signals for each of the first plurality of poses. The first set of signals may correspond to one or more positional and orientational coordinates of at least one part of the wearable device. The operations may further include determination of arrow direction information based on the application of the predefined model on the first set of signals for each of the first plurality of poses. The arrow direction information may relate to joint angle information for the robotic manipulator to perform the task. The operations may further include aggregation of the determined arrow direction information with information about the first set of signals to generate output information for each of the first plurality of poses. The operations may further include control of a memory to store the generated output information for each of the first plurality of poses performed for the task using the wearable device. 
     Various embodiments of the disclosure may further provide a non-transitory, computer-readable medium and/or storage medium, and/or a non-transitory machine readable medium and/or storage medium stored thereon, a set of instructions executable by a machine and/or a computer (for example the electronic apparatus  102 ) for the control of the robotic manipulator  110 . The set of instructions may be executable by the machine and/or the computer (for example the electronic apparatus  102 ) to perform operations that may include storage of output information for each of a first plurality of poses performed for a task using a wearable device. The output information may include arrow direction information associated with each of the first plurality of poses performed for the task. The operations may further include reception of a second plurality of signals from a second plurality of sensors associated with a handheld device. The second plurality of signals may correspond to each of a second plurality of poses performed for the task using the handheld device. The operations may further include retrieval of the stored output information corresponding to a third set of signals of the received second plurality of signals for each of the second plurality of poses. The third set of signals may correspond to one or more positional and orientational coordinates of at least one part of the handheld device. The operations may further include extraction of the arrow direction information from the retrieved output information for each of the second plurality of poses. The operations may further include transmission of control instructions to the robotic manipulator to execute the task based on the extracted arrow direction information and the received second plurality of signals for each of the second plurality of poses performed for the task using the handheld device. 
     The present disclosure may be realized in hardware, or a combination of hardware and software. The present disclosure may be realized in a centralized fashion, in at least one computer system, or in a distributed fashion, where different elements may be spread across several interconnected computer systems. A computer system or other apparatus adapted for carrying out the methods described herein may be suited. A combination of hardware and software may be a general-purpose computer system with a computer program that, when loaded and executed, may control the computer system such that it carries out the methods described herein. The present disclosure may be realized in hardware that includes a portion of an integrated circuit that also performs other functions. It may be understood that, depending on the embodiment, some of the steps described above may be eliminated, while other additional steps may be added, and the sequence of steps may be changed. 
     The present disclosure may also be embedded in a computer program product, which includes all the features that enable the implementation of the methods described herein, and which when loaded in a computer system is able to carry out these methods. Computer program, in the present context, means any expression, in any language, code or notation, of a set of instructions intended to cause a system with an information processing capability to perform a particular function either directly, or after either or both of the following: a) conversion to another language, code or notation; b) reproduction in a different material form. While the present disclosure has been described with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made, and equivalents may be substituted without departing from the scope of the present disclosure. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the present disclosure without departing from its scope. Therefore, it is intended that the present disclosure is not limited to the particular embodiment disclosed, but that the present disclosure will include all embodiments that fall within the scope of the appended claims.