ROBOT SYSTEM AND CONTROL METHOD OF THE SAME

A robot system includes a mobile robot configured to travel by driving wheels, a user interface, via which user service information and user information are input, and a controller configured to select one of at least two paths including a path including a moving walkway by using the user information and generate a map of a selected path, if the user service information and the user information are input via the user interface, and move the mobile robot to the path of a generated map.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of priority to Korean Patent Application No. 10-2019-0114004, filed in the Korean Intellectual Property Office on Sep. 17, 2019, the entire contents of which are incorporated herein by reference.

FIELD OF THE DISCLOSURE

The present disclosure relates to a robot system and a control method of the same.

Robots are machines that automatically process given tasks or operate with their own capabilities. The application fields of robots are generally classified into industrial robots, medical robots, aerospace robots, and underwater robots. Recently, communication robots that can communicate with humans by voices or gestures have been increasing.

Recently, guidance robots for providing various types of guide services in airports or government offices or porter robots such as delivery robots for carrying goods are increasing.

Robots may be mobile robots moving along set movement paths and the movement paths of the mobile robots may include a moving walkway.

The moving walkway may include a conveyor belt and a machine capable of slowly moving inclined roads or flat surfaces.

When a mobile robot stops after entering a moving walkway, the mobile robot may can save power while being located on the moving walkway. A user who moves around the mobile robot along with the mobile robot may enter the moving walkway and move by the moving walkway.

In addition, when the mobile robot enters the moving walkway and then moves on the moving walkway, the mobile robot may move faster when moving outside the moving walkway.

SUMMARY

An object of the present disclosure is to provide a robot system capable of moving a mobile robot along an optimal traveling path, to which user information is applied, and a method of controlling the same.

According to an embodiment, a robot system includes a mobile robot configured to travel by driving wheels, a user interface, via which user service information and user information are input, and a controller configured to select one of at least two paths including a path including a moving walkway by using the user information and generate a map of a selected path, if the user service information and the user information are input via the user interface, and move the mobile robot to the path of a generated map.

The user service information may include at least one of a request for a guide service provided by the mobile robot and a user's consent to use of the moving walkway.

The user information may include at least one of a user's age, a health level or baggage information.

The at least two paths may include a first traveling path including the moving walkway and a second traveling path which does not include the moving walkway.

The controller may select one of the first traveling path and the second traveling path by using a first traveling distance of the first traveling path, a second traveling distance of the second traveling path and the user information as factors and generate the map.

The controller may move the mobile robot to a traveling path having the shorter traveling distance between the first traveling distance and the second traveling distance, if the user service information is input and the user information is not input.

The controller may calculate a first reference value according to the first traveling distance and a second reference value according to the second traveling distance, and correct the first reference value according to the user information.

The controller may move the mobile robot to a traveling path having the smaller reference value between the corrected first reference value and the second reference value.

The user interface may include a touch interface, via which a user inputs a user's age, baggage information and a health level.

The user interface may include a microphone configured to recognize speech of a user.

The user interface may include a sensor configured to sense an object possessed by a user.

A method of controlling a robot system includes inputting user service information and user information via a user interface, selecting one of at least two paths including a path including a moving walkway using the user information and generating a map, if the user service information and the user information are input, and moving the mobile robot to a path of the generated map.

The user service information may include at least one of a request for a guide service provided by the mobile robot and a user's consent to use of the moving walkway.

The inputting may include an inquiry process of inquiring about a consent to use of a guide service provided by the mobile robot and a user's consent to use of the moving walkway via an output interface.

The user information may include at least one of a user's age, a health level or baggage information.

The inputting may include inputting the user information via a touch interface or a microphone or recognizing an object possessed by a user using a sensor.

The at least two paths may include a first traveling path including the moving walkway and a second traveling path which does not include the moving walkway.

The controller may select one of the first traveling path and the second traveling path by using a first traveling distance of the first traveling path, a second traveling distance of the second traveling path and the user information as factors and generate the map.

The moving may include moving the mobile robot to a traveling path having the shorter traveling distance between the first traveling distance and the second traveling distance, if the user information is not input via the user interface.

The moving includes calculating a first reference value according to the first traveling distance and a second reference value according to the second traveling distance, correcting the first reference value according to the user information, and comparing a corrected first reference value with the second reference value.

The moving may include moving the mobile robot to a traveling path having the smaller reference value between the corrected first reference value and the second reference value.

The corrected first reference value when a user is older may be less than the corrected first reference value when a user is younger.

The corrected first reference value when baggage is present may be less than the corrected first reference value when baggage is absent.

The corrected first reference value when a health condition is uncomfortable may be less than the corrected first reference value when a health condition is healthy.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

A robot may refer to a machine that automatically processes or operates a given task by its own ability. In particular, a robot having a function of recognizing an environment and performing a self-determination operation may be referred to as an intelligent robot.

Robots may be classified into industrial robots, medical robots, home robots, military robots, and the like according to the use purpose or field.

The robot includes a driving unit may include an actuator or a motor and may perform various physical operations such as moving a robot joint. In addition, a movable robot may include a wheel, a brake, a propeller, and the like in a driving unit, and may travel on the ground through the driving unit or fly in the air.

Artificial intelligence refers to the field of studying artificial intelligence or methodology for making artificial intelligence, and machine learning refers to the field of defining various issues dealt with in the field of artificial intelligence and studying methodology for solving the various issues. Machine learning is defined as an algorithm that enhances the performance of a certain task through a steady experience with the certain task.

An artificial neural network (ANN) is a model used in machine learning and may mean a whole model of problem-solving ability which is composed of artificial neurons (nodes) that form a network by synaptic connections. The artificial neural network can be defined by a connection pattern between neurons in different layers, a learning process for updating model parameters, and an activation function for generating an output value.

The artificial neural network may include an input layer, an output layer, and optionally one or more hidden layers. Each layer includes one or more neurons, and the artificial neural network may include a synapse that links neurons to neurons. In the artificial neural network, each neuron may output the function value of the activation function for input signals, weights, and deflections input through the synapse.

The purpose of the learning of the artificial neural network may be to determine the model parameters that minimize a loss function. The loss function may be used as an index to determine optimal model parameters in the learning process of the artificial neural network.

Machine learning may be classified into supervised learning, unsupervised learning, and reinforcement learning according to a learning method.

The supervised learning may refer to a method of learning an artificial neural network in a state in which a label for learning data is given, and the label may mean the correct answer (or result value) that the artificial neural network must infer when the learning data is input to the artificial neural network. The unsupervised learning may refer to a method of learning an artificial neural network in a state in which a label for learning data is not given. The reinforcement learning may refer to a learning method in which an agent defined in a certain environment learns to select a behavior or a behavior sequence that maximizes cumulative compensation in each state.

Machine learning, which is implemented as a deep neural network (DNN) including a plurality of hidden layers among artificial neural networks, is also referred to as deep learning, and the deep learning is part of machine learning. In the following, machine learning is used to mean deep learning.

Self-driving refers to a technique of driving for oneself, and a self-driving vehicle refers to a vehicle that travels without an operation of a user or with a minimum operation of a user. For example, the self-driving may include a technology for maintaining a lane while driving, a technology for automatically adjusting a speed, such as adaptive cruise control, a technique for automatically traveling along a predetermined route, and a technology for automatically setting and traveling a route when a destination is set.

The vehicle may include a vehicle having only an internal combustion engine, a hybrid vehicle having an internal combustion engine and an electric motor together, and an electric vehicle having only an electric motor, and may include not only an automobile but also a train, a motorcycle, and the like.

At this time, the self-driving vehicle may be regarded as a robot having a self-driving function.FIG. 1is a view illustrating an AI device constituting a robot system according to an embodiment.

Referring toFIG. 1, the AI device100may include a communication unit110, an input unit120, a learning processor130, a sensing unit140, an output unit150, a memory170, and a processor180.

The communication unit110may transmit and receive data to and from external devices such as other AI devices100ato100eand the AI server500by using wire/wireless communication technology. For example, the communication unit110may transmit and receive sensor information, a user input, a learning model, and a control signal to and from external devices.

The communication technology used by the communication unit110includes GSM (Global System for Mobile communication), CDMA (Code Division Multi Access), LTE (Long Term Evolution), 5G, WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Bluetooth™, RFID (Radio Frequency Identification), Infrared Data Association (IrDA), ZigBee, NFC (Near Field Communication), and the like. The input unit120may acquire various kinds of data.

At this time, the input unit120may include a camera for inputting a video signal, a microphone for receiving an audio signal, and a user input unit for receiving information from a user. The camera or the microphone may be treated as a sensor, and the signal acquired from the camera or the microphone may be referred to as sensing data or sensor information.

The input unit120may acquire a learning data for model learning and an input data to be used when an output is acquired by using learning model. The input unit120may acquire raw input data. In this case, the processor180or the learning processor130may extract an input feature by preprocessing the input data. The learning processor130may learn a model composed of an artificial neural network by using learning data. The learned artificial neural network may be referred to as a learning model. The learning model may be used to an infer result value for new input data rather than learning data, and the inferred value may be used as a basis for determination to perform a certain operation. At this time, the learning processor130may perform AI processing together with the learning processor540of the AI server500.

At this time, the learning processor130may include a memory integrated or implemented in the AI device100. Alternatively, the learning processor130may be implemented by using the memory170, an external memory directly connected to the AI device100, or a memory held in an external device.

The sensing unit140may acquire at least one of internal information about the AI device100, ambient environment information about the AI device100, and user information by using various sensors.

Examples of the sensors included in the sensing unit140may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, an optical sensor, a microphone, a lidar, and a radar.

The output unit150may generate an output related to a visual sense, an auditory sense, or a haptic sense.

At this time, the output unit150may include a display unit for outputting time information, a speaker for outputting auditory information, and a haptic module for outputting haptic information. The memory170may store data that supports various functions of the AI device100. For example, the memory170may store input data acquired by the input unit120, learning data, a learning model, a learning history, and the like.

The processor180may determine at least one executable operation of the AI device100based on information determined or generated by using a data analysis algorithm or a machine learning algorithm. The processor180may control the components of the AI device100to execute the determined operation.

To this end, the processor180may request, search, receive, or utilize data of the learning processor130or the memory170. The processor180may control the components of the AI device100to execute the predicted operation or the operation determined to be desirable among the at least one executable operation. When the connection of an external device is required to perform the determined operation, the processor180may generate a control signal for controlling the external device and may transmit the generated control signal to the external device. The processor180may acquire intention information for the user input and may determine the user's requirements based on the acquired intention information.

The processor180may acquire the intention information corresponding to the user input by using at least one of a speech to text (STT) engine for converting speech input into a text string or a natural language processing (NLP) engine for acquiring intention information of a natural language.

At least one of the STT engine or the NLP engine may be configured as an artificial neural network, at least part of which is learned according to the machine learning algorithm. At least one of the STT engine or the NLP engine may be learned by the learning processor130, may be learned by the learning processor540of the AI server500, or may be learned by their distributed processing.

The processor180may collect history information including the operation contents of the AI apparatus100or the user's feedback on the operation and may store the collected history information in the memory170or the learning processor130or transmit the collected history information to the external device such as the AI server500. The collected history information may be used to update the learning model.

The processor180may control at least part of the components of AI device100so as to drive an application program stored in memory170. Furthermore, the processor180may operate two or more of the components included in the AI device100in combination so as to drive the application program.

FIG. 2is a view illustrating an AI server of a robot system according to an embodiment. Referring toFIG. 2, the AI server500may refer to a device that learns an artificial neural network by using a machine learning algorithm or uses a learned artificial neural network. The AI server500may include a plurality of servers to perform distributed processing, or may be defined as a 5G network. At this time, the AI server500may be included as a partial configuration of the AI device100, and may perform at least part of the AI processing together.

The AI server500may include a communication unit510, a memory530, a learning processor540, a processor520, and the like.

The communication unit510can transmit and receive data to and from an external device such as the AI device100.

The memory530may include a model storage unit531. The model storage unit531may store a learning or learned model (or an artificial neural network531a) through the learning processor540.

The learning processor540may learn the artificial neural network531aby using the learning data. The learning model may be used in a state of being mounted on the AI server500of the artificial neural network, or may be used in a state of being mounted on an external device such as the AI device100.

The learning model may be implemented in hardware, software, or a combination of hardware and software. If all or part of the learning models are implemented in software, one or more instructions that constitute the learning model may be stored in memory530.

The processor520may infer the result value for new input data by using the learning model and may generate a response or a control command based on the inferred result value.

FIG. 3is a view illustrating an AI system to which a robot system according to an embodiment is applied. Referring toFIG. 3, in the AI system1, at least one of an AI server500, a robot100a,a self-driving vehicle100b,an XR device100c,a smartphone100d,or a home appliance100eis connected to a cloud network10. The robot100a,the self-driving vehicle100b,the XR device100c,the smartphone100d,or the home appliance100e,to which the AI technology is applied, may be referred to as AI devices100ato100e.

The cloud network10may refer to a network that forms part of a cloud computing infrastructure or exists in a cloud computing infrastructure. The cloud network10may be configured by using a 3G network, a 4G or LTE network, or a 5G network.

That is, the devices100ato100eand500configuring the AI system1may be connected to each other through the cloud network10. In particular, each of the devices100ato100eand500may communicate with each other through a base station, but may directly communicate with each other without using a base station. The AI server500may include a server that performs AI processing and a server that performs operations on big data.

The AI server500may be connected to at least one of the AI devices constituting the AI system1, that is, the robot100a,the self-driving vehicle100b,the XR device100c,the smartphone100d,or the home appliance100ethrough the cloud network10, and may assist at least part of AI processing of the connected AI devices100ato100e.

At this time, the AI server500may learn the artificial neural network according to the machine learning algorithm instead of the AI devices100ato100e,and may directly store the learning model or transmit the learning model to the AI devices100ato100e.

At this time, the AI server500may receive input data from the AI devices100ato100e,may infer the result value for the received input data by using the learning model, may generate a response or a control command based on the inferred result value, and may transmit the response or the control command to the AI devices100ato100e.

Alternatively, the AI devices100ato100emay infer the result value for the input data by directly using the learning model, and may generate the response or the control command based on the inference result.

Hereinafter, various embodiments of the AI devices100ato100eto which the above-described technology is applied will be described. The AI devices100ato100eillustrated inFIG. 3may be regarded as a specific embodiment of the AI device100illustrated inFIG. 1.

The robot100a,to which the AI technology is applied, may be implemented as a guide robot, a carrying robot, a cleaning robot, a wearable robot, an entertainment robot, a pet robot, an unmanned flying robot, or the like.

The robot100amay include a robot control module for controlling the operation, and the robot control module may refer to a software module or a chip implementing the software module by hardware.

The robot100amay acquire state information about the robot100aby using sensor information acquired from various kinds of sensors, may detect (recognize) surrounding environment and objects, may generate map data, may determine the route and the travel plan, may determine the response to user interaction, or may determine the operation.

The robot100amay use the sensor information acquired from at least one sensor among the lidar, the radar, and the camera so as to determine the travel route and the travel plan.

The robot100amay perform the above-described operations by using the learning model composed of at least one artificial neural network. For example, the robot100amay recognize the surrounding environment and the objects by using the learning model, and may determine the operation by using the recognized surrounding information or object information. The learning model may be learned directly from the robot100aor may be learned from an external device such as the AI server500.

At this time, the robot100amay perform the operation by generating the result by directly using the learning model, but the sensor information may be transmitted to the external device such as the AI server500and the generated result may be received to perform the operation.

The robot100amay use at least one of the map data, the object information detected from the sensor information, or the object information acquired from the external apparatus to determine the travel route and the travel plan, and may control the driving unit such that the robot100atravels along the determined travel route and travel plan.

The map data may include object identification information about various objects arranged in the space in which the robot100amoves. For example, the map data may include object identification information about fixed objects such as walls and doors and movable objects such as pollen and desks. The object identification information may include a name, a type, a distance, and a position.

In addition, the robot100amay perform the operation or travel by controlling the driving unit based on the control/interaction of the user. At this time, the robot100amay acquire the intention information of the interaction due to the user's operation or speech utterance, and may determine the response based on the acquired intention information, and may perform the operation.

The robot100a,to which the AI technology and the self-driving technology are applied, may be implemented as a guide robot, a carrying robot, a cleaning robot, a wearable robot, an entertainment robot, a pet robot, an unmanned flying robot, or the like.

The robot100a,to which the AI technology and the self-driving technology are applied, may refer to the robot itself having the self-driving function or the robot100ainteracting with the self-driving vehicle100b.

The robot100ahaving the self-driving function may collectively refer to a device that moves for itself along the given movement line without the user's control or moves for itself by determining the movement line by itself.

The robot100aand the self-driving vehicle100bhaving the self-driving function may use a common sensing method so as to determine at least one of the travel route or the travel plan. For example, the robot100aand the self-driving vehicle100bhaving the self-driving function may determine at least one of the travel route or the travel plan by using the information sensed through the lidar, the radar, and the camera.

The robot100athat interacts with the self-driving vehicle100bexists separately from the self-driving vehicle100band may perform operations interworking with the self-driving function of the self-driving vehicle100bor interworking with the user who rides on the self-driving vehicle100b.

At this time, the robot100ainteracting with the self-driving vehicle100bmay control or assist the self-driving function of the self-driving vehicle100bby acquiring sensor information on behalf of the self-driving vehicle100band providing the sensor information to the self-driving vehicle100b,or by acquiring sensor information, generating environment information or object information, and providing the information to the self-driving vehicle100b.

Alternatively, the robot100ainteracting with the self-driving vehicle100bmay monitor the user boarding the self-driving vehicle100b,or may control the function of the self-driving vehicle100bthrough the interaction with the user. For example, when it is determined that the driver is in a drowsy state, the robot100amay activate the self-driving function of the self-driving vehicle100bor assist the control of the driving unit of the self-driving vehicle100b.The function of the self-driving vehicle100bcontrolled by the robot100amay include not only the self-driving function but also the function provided by the navigation system or the audio system provided in the self-driving vehicle100b.

Alternatively, the robot100athat interacts with the self-driving vehicle100bmay provide information or assist the function to the self-driving vehicle100boutside the self-driving vehicle100b.For example, the robot100amay provide traffic information including signal information and the like, such as a smart signal, to the self-driving vehicle100b,and automatically connect an electric charger to a charging port by interacting with the self-driving vehicle100blike an automatic electric charger of an electric vehicle.

FIG. 4is a view showing a plurality of traveling paths of a robot according to an embodiment.

The robot system may include a mobile robot200.

The mobile robot200may include driving wheels and may travel along a traveling path.

The mobile robot200may include a traveling mechanism connected to the driving wheels to rotate the driving wheels, and the traveling mechanism may include a driving source such as a motor and may further include at least one power transmission member for transmitting the driving force of the driving source to the driving wheels.

When the motor is driven, the driving wheels may be rotated forward and backward and the mobile robot200may be moved forward or backward.

The mobile robot200may include a steering mechanism capable of changing a forward movement direction or a backward movement direction, and the mobile robot200may be moved while turning left or right along the traveling path.

The mobile robot200may configure a robot having a self-driving function. The mobile robot200may be used in an airport, a government office, a hotel, a mart, a department store, etc. and may be a guidance robot for providing a variety of information to a user, a porter robot for carrying user's goods, or a boarding robot in which a user directly rides.

The mobile robot200may move to a destination E along with a user and guide the user to the destination E.

When the destination E is determined by the user, etc., the mobile robot200may move along traveling paths P1and P2to the destination E.

The mobile robot200may move along a traveling path selected from the plurality of traveling paths P1and P2along which the mobile robot200may move.

The plurality of traveling paths P1and P2may include a traveling path having a shortest time from a starting point A to the destination E and a traveling path having a shortest distance from the starting point A to the destination E.

Each of the plurality of traveling paths P1and P2may include at least one waypoint B, C and D, through which the mobile robot200departing from the starting point A passes before reaching the destination E.

The plurality of traveling paths P1and P2may be classified depending on whether a moving walkway MW is included.

The plurality of traveling paths P1and P2may include a first traveling path P1including a moving walkway and at least one second traveling path P2which does not include a moving walkway.

Referring toFIG. 5, the example of the first traveling path P1may be a path passing through the moving walkway MW while passing through a pair of waypoints B and D or may be a path from the starting point A to the destination E through the waypoints B, C and D.

In addition, referring toFIG. 5, the example of the second traveling path P2may be a path which does not pass through the moving walkway MW or may be a path from the starting point A to the destination E through the midways B and C.

The robot system may select a specific traveling path from among the plurality of traveling paths P1and P2based on at least one factor, and move the mobile robot200to the selected traveling path.

Such a factor may include an actual traveling distance from the starting point A to the destination E, a user's condition (e.g., user's age, health level, presence/absence or weight of baggage, etc.) or a user's request.

The robot system may include an output unit150for requesting input of user service information and input of user information from a user. The output unit151may include a display or a speaker, and the output unit151may inquire of the user about the user service information and the user information.

The robot system may include a user interface capable of inputting the user service information and the user information and may include a controller for moving the mobile robot200.

The user service information may include a request for a guide service provided by the mobile robot200and a user's consent to use of the moving walkway.

In addition, the user information may include user's age, health level, baggage information, etc.

An example of the user interface may be an interface of various devices (e.g., a terminal such as a smartphone100dor a computing device such as a desktop, a laptop or a tablet PC) communicating with the robot100adirectly or via a cloud network10. In this case, the user may input the user information in advance before the mobile robot200is used.

Another example of the user interface may be a robot interface installed in the mobile robot200.

If the user interface is a robot interface installed in the mobile robot200, the user interface may configure the robot100aalong with the mobile robot200, and the user may approach the mobile robot200to input the user information.

Hereinafter, it is assumed that the user interface is an input unit120which is installed in the mobile robot200, for example. For convenience, the user interface is denoted by the same reference numeral as the input unit120. However, the user interface of the present embodiment is not limited to the input unit120installed in the mobile robot200.

The user may input a request for a guide service provided by the mobile robot200and a user's consent to use of the moving walkway via the user interface120.

The user may input a user's age, baggage information and health level via the user interface120.

An example of the user interface102may include a touch interface121such as a touchscreen for allowing the user to perform touch input. The touch interface121may transmit touch input to the controller when touch of the user is sensed.

Another example of the user interface120may include a microphone122capable of receiving speech of the user. The microphone122may configure a speech recognition module including a speech recognition circuit and transmit the user information recognized by the speech recognition module to the controller.

The robot100aor various devices (e.g., a terminal, a computing device, etc.) may inquire of a user who wants to use the mobile robot1200via a speaker or a display about a user's age, baggage information and health level.

The user may input the user information such as the user's age, the baggage information and health level via the touch interface or provide the user information such as the user's age, the baggage information and health level as an answer by voice.

Another example of the user interface120may include a sensor for sensing an object (e.g., an identification card, etc.) possessed by the user. Such a sensor may include a scanner123.

The scanner123may scan the identification (ID) card such as a passport possessed by the user.

The ID card capable of being sensed by the scanner123is not limited to the ID card such as the passport, and may include a card via which the user is authorized to use the mobile robot200. The type of the ID card is not limited if the user information such as user's age, baggage information and a health level is stored.

The sensor may recognize the user information via a barcode included in the ID card and transmit a result of recognition to the controller.

Various devices such as a terminal or a computing device or the mobile robot200may guide the user to put the ID card onto the scanner123via the speaker or the display.

When the user puts the ID card onto the scanner123, the user information contained in the ID card may be recognized via the scanner123and the scanned result may be transmitted to the controller.

The user's age input via the user interface120may be 45, 50, 72, etc., for example.

The baggage information input via the user interface120may be information on presence/absence of the baggage or the weight (Kg) of the baggage.

The health level input via the user interface120may be information arbitrarily input by the user, such as very healthy, healthy, uncomfortable or very uncomfortable, or information on presence/absence of a disease or the type of a disease.

An example of the controller may include a processor180installed in the mobile robot200to control the mobile robot200.

Another example of the controller may include processors of the various devices (e.g., the terminal such as the smartphone100d,the computing device such as a desktop, a laptop, a tablet PC, etc.).

Another example of the controller may be a server500.

When the controller is installed in the mobile robot200, the controller may configure the robot100aalong with the mobile robot200.

Hereinafter, it is assumed that the controller includes a processor installed in the mobile robot200, for example. For convenience, the controller is denoted by the same reference numeral as the processor180. However, the controller of the present embodiment is not limited to the processor180installed in the mobile robot200.

When the user service information is input, the controller180may generate a map by selecting one of at least two paths including a path having a moving walkway (MW) and move the mobile robot200to the path of the generated map.

At least two paths may include the first traveling path P1including the moving walkway MW and the second traveling path P2which does not include the moving walkway MW.

The controller180may select the first traveling path P1including the moving walkway MW or the second traveling path P2which does not include the moving walkway MW and move the mobile robot200to the selected path.

The controller180may use the user information when the paths P1or P2is selected, and select a path in consideration of the user information.

There is a plurality of factors used to select the first traveling path P1or the second traveling path P2and the plurality of factors may include a first traveling distance (first factor) of the first traveling path including the moving walkway MW. The plurality of factors may further include a second traveling distance (second factor) of the second traveling path which does not include the moving walkway. The plurality of factors may include the user information (third factor) input via the user interface120.

The controller180may select one of the first traveling path P1and the second traveling path P2according to the first factor, the second factor and the third factor. The controller180may generate the map of the selected path and move the mobile robot200to the path of the generated map.

Even if the starting point A and the destination E are the same, the mobile robot200may move to the first traveling path P1or the second traveling path P2according to the user information.

The user may input the destination E via the user interface120and input a traveling start command.

The destination E may be a location (or a target) directly input by the user via the input unit120.

The destination E be a location (or a target) determined by the mobile robot200according to a user's inquiry after the user inquires of the mobile robot200about the destination E.

The controller180may search for the plurality of traveling paths P1and P2via map data stored in the memory170or map data transmitted from the server500or the terminal and one of the plurality of traveling paths P1and P2searched by the controller180may be a traveling path including the moving walkway.

The user may request to start a guide service from the mobile robot200by touching the input unit120or inputting a speech command, and the mobile robot200may select the first traveling path P1or the second traveling path P2from among the plurality of traveling paths P1and P2and move to the destination E along the selected path.

When the user information is input, the controller180may select one of the first traveling path and the second traveling path in consideration of the first traveling distance (the first factor), the second traveling distance (the second factor) and the user information, and move the mobile robot200to the selected traveling path.

When the user information is not input, the controller180may move the mobile robot200to the shorter traveling distance between the first traveling distance and the second traveling distance.

FIG. 5is a view showing a first traveling distance of a first traveling path and a second traveling distance of a second traveling path shown inFIG. 4,FIG. 6is a view showing a first traveling distance of a first traveling path before correction and a second traveling distance of a second traveling path shown inFIG. 4, andFIG. 7is a view showing an example of a first traveling distance of a first traveling path after correction and a second traveling distance of a second traveling path shown inFIG. 4.

InFIGS. 5 to 7, the first traveling path is denoted by a dotted line and the second traveling path is denoted by a solid line.

The controller180may calculate a first reference value according to the first traveling distance L1+L2+L3+L5and a second reference value according to the second traveling distance L1+L4+L5.

The first reference value is determined based on the respective locations of the starting point A, the plurality of waypoints B, D and C and the destination E, and may be variable value which may be changed by the user information.

The second reference value is not changed by the user information, and may be a fixed value determined by the respective locations of the starting point A, at least one waypoints B and C and the destination E.

As shown inFIG. 5, an example of the first traveling distance L1+L2+L3+L5of the first traveling path P1may be a sum of a distance L1from the starting point A to the first waypoint B, a distance L2from the first waypoint B to the second waypoint D through the moving walkway MW, a distance L3from the second waypoint D to the third waypoint C, and a distance L5from the third waypoint C to the destination E.

As shown inFIG. 5, an example of the second traveling distance L1+L4+L5of the second traveling path P2may be a sum of the distance L1from the starting point A to the first waypoint B, a distance L4from the first waypoint B to the third waypoint C and the distance L5from the third waypoint C to the destination E.

The controller180may correct the first reference value according to the user information.

The controller180may move the mobile robot200to a traveling path having the smaller reference value between the corrected first reference value and the second reference value.

For convenience of description, it is assumed that the distance L1from the starting point A to the first waypoint B is 5 m, the distance L2from the first waypoint B to the second waypoint D is 15 m, the distance L3from the second waypoint D to the third waypoint C is 1 m, the distance L4from the first waypoint B to the third waypoint C is 15 m, and the distance L5from the third waypoint C to the destination E is 5 m.

As shown inFIG. 6, the first reference distance before correction of the first traveling distance L1+L2+L3+L5may be 26 which is 5+15+1+5, and the second reference value of the second traveling distance L1+L4+L5may be 25 which is 5+15+5.

The first reference value of the first traveling distance L1+L2+L3+L5may be corrected by the user information, and the distance L2from the first waypoint B to the second waypoint D may be corrected to another value which is not 15 m.

As shown inFIG. 7, an example of correction of the first reference value may be determined by presence/absence of baggage. For example, when the user inputs presence of baggage, the distance L2from the first waypoint B to the second waypoint D may be adjusted to 10 m, instead of 15 m. In this case, the first reference value after correction of the first traveling distance L1+L2+L3+L5may be 21 which is 5+10+1+5.

In this case, the controller180may compare 21 which is the corrected first reference value with 25 which is the fixed second reference value, and select the first traveling path P1having the smaller reference value as a traveling path, along which the mobile robot200will move, and move the mobile robot200to the first traveling path P1.

As shown inFIG. 8, another example of correction of the first reference value may be determined by the health level of the user. For example, when the user inputs uncomfortable as the health level, the distance L2from the first waypoint B to the second waypoint D may be adjusted to 5 m instead of 15 m. In this case, the first reference value after correction of the first traveling distance L1+L2+L3+L5may be 16 which is 5+5+1+5.

In this case, the controller180may compare 16 which is the corrected first reference value with 25 which is the fixed second reference value, select the first traveling path P1having the smaller reference value as a traveling path, along which the mobile robot200will move, and move the mobile robot200to the first traveling path P1.

In another example of correction of the first reference value, it is possible to use a specific equation, to which a customer' age, presence/absence of baggage, and a health level are applied, and to correct the first reference value by subtracting a weight calculated by the specific equation from the distance L2from the first waypoint B to the second waypoint D.

For example, the weight may be max(Z,(X+Y)/2). X may be max(0,min(1, user's age−50)/20)). Y may be a value selected from among 0 to 1 with respect to the weight of baggage input via the user interface120. Z may be 0 when the health level of the user is healthy and may be 1 when the health level of the user is uncomfortable.

X may be 0 if the user's age is less than 50 and may be 1 if the user's age is equal to or greater than 70.

Y may be 0 if the user does not have baggage and may be 1 when the baggage of the user is 20 Kg, and a value from 0 to 1 may be selected in proportion to the weight of the baggage of the user.

The controller180may determine the weight as in the above example and the weight determined from the distance L2from the first waypoint B to the second waypoint D may be subtracted.

The controller180may move the mobile robot200to the first traveling path P1if the first reference value after correction is less than the second reference value, and move the mobile robot200to the second traveling path P2if the second reference value is less than the first reference after correction.

FIG. 9is a flowchart illustrating a method of controlling a robot system according to an embodiment.

The method of controlling the robot system may control the robot system including the mobile robot200traveling by the driving wheels201and the user interface120, via which the user information is input.

The method of controlling the robot system may include input steps S1and S2and movement steps S3, S4, S5and S6.

Input steps S1and S2may be steps of inputting the user service information and the user information via the user interface120.

The user service information may include a request for a guide service provided by the mobile robot and a user's consent to use of the moving walkway.

Input steps S1and S2may include an inquiry process S1in which the robot100ainquires of the user about various types of inquiries via the output unit150such as a display or a speaker.

During the inquiry process S1, the output unit150may inquire of the user whether to use a guide service (that is, a consent to use of the guide service) and the user may input a request for the guide service provided by the mobile robot via the user interface120.

During the inquiry process S1, the output unit150may inquire of the user whether to use the moving walkway MW (that is, a consent to use of the moving walkway), and the user may input a consent to use of the moving walkway MW via the user interface120or a refusal to use of the moving walkway MW.

With respect to the inquiry of the inquiry process S1, the user may input the use of the moving walkway MW as well as the request for the guide service and the output unit150may request input of the user information from the user.

The user information may be information on the condition of the user who will use the mobile robot200.

The user information may include a user's age, a health level (e.g., healthy or uncomfortable), baggage information (e.g., presence/absence or weight of baggage), etc.

During the input step, the user information may be input via the touch interface121or the microphone122.

During the input step, an object (e.g., an ID card such as a passport) possessed by the user may be recognized by the sensor123, and the controller180may acquire the user information by the object possessed by the user.

The user may input a user's age, a health level (e.g., healthy or uncomfortable), baggage information (e.g., presence/absence or weight of baggage), etc. via the user interface120, and the input process S2in which the robot receives such input may be performed.

Meanwhile, when the user inputs non-use of the moving walkway MW with respect to the inquiry of the inquiry process S1, the method of controlling the robot system may move the mobile robot200to the second traveling path P2which does not include the moving walkway MW without performing the input process S2(S1and S6).

The method of controlling the robot system may perform the input process S2without performing the inquiry process S1.

The movement steps S3, S4, S5and S6may be steps of selecting one of the first traveling path P1and the second traveling path P2and moving the robot to the selected traveling path.

During the movement step, the controller180may select one of the first traveling path P1and the second traveling path P2, using the first traveling distance (the first factor) of the first traveling path P1including the moving walkway MW, the second traveling distance (the second factor) of the second traveling path P2which does not include the moving walkway MW and the user information (the third factor) input via the user interface120as factors.

During the movement step, the controller180may calculate the first reference value according to the first traveling distance and the second reference value according to the second traveling distance and correct the first reference value according to the user information (S3).

The corrected first reference value when the user is older may be less than the corrected first reference value when the user is younger.

The corrected first reference value when baggage is present may be less than the corrected first reference value when baggage is absence.

The corrected first reference value when the health condition is uncomfortable may be less than the corrected first reference value when the health condition is healthy.

During the movement step, the controller180may compare the corrected first reference value with the second reference value (S4).

During the movement step, the controller180may move the mobile robot200to a traveling path having the smaller reference value between the corrected first reference value and the second reference value (S3, S4, S5and S6).

Meanwhile, when the user information is not input via the user interface120, during the movement step, the controller180may move the mobile robot200to a traveling path having the shorter traveling distance between the first traveling distance and the second traveling distance (S2, S4, S5and S6).

According to the embodiment of the present disclosure, the robot may move along the first traveling path including the moving walkway using the user's age, the health information, baggage, etc. Therefore, it is possible to provide the user with optimal convenience.

In addition, it is possible to simply and rapidly input and process the user information via a touch interface, a microphone or a sensor.

In addition, it is possible to guide a user who needs to use the moving walkway to a path capable of minimizing an actual walking distance of the user even if the total traveling distance increases.

In addition, it is possible to guide a user who does not need to use the moving walkway to a shortest path, thereby decreasing congestion of the moving walkway.

The foregoing description is merely illustrative of the technical idea of the present invention and various changes and modifications may be made by those skilled in the art without departing from the essential characteristics of the present invention.

Therefore, the embodiments disclosed in the present disclosure are intended to illustrate rather than limit the technical idea of the present invention, and the scope of the technical idea of the present invention is not limited by these embodiments.

The scope of protection of the present invention should be construed according to the following claims, and all technical ideas falling within the equivalent scope to the scope of protection should be construed as falling within the scope of the present invention.