Patent Publication Number: US-2021166484-A1

Title: Xr device and method for controlling the same

Description:
This application claims the benefit of Korean Patent Application No. 10-2019-0159215, filed on Dec. 3, 2019, which is hereby incorporated by reference as if fully set forth herein. 
     BACKGROUND OF THE INVENTION 
     Field of the Invention 
     The present disclosure relates to an extended reality (XR) device for providing augmented reality (AR) mode and virtual reality (VR) mode and a method of controlling the same. More particularly, the present disclosure is applicable to all of the technical fields of 5 th  generation (5G) communication, robots, self-driving, and artificial intelligence (AI). 
     Discussion of the Related Art 
     Virtual reality (VR) simulates objects or a background in the real world only in computer graphic (CG) images. Augmented reality (AR) is an overlay of virtual CG images on images of objects in the real world. Mixed reality (MR) is a CG technology of merging the real world with virtual objects. All of VR, AR and MR are collectively referred to shortly as extended reality (XR). 
     XR technology may be applied to a Head-Mounted Display (HMD), a Head-Up Display (HUD), eyeglasses-type glasses, a mobile phone, a tablet, a laptop, a desktop computer, a TV, digital signage, etc. A device to which XR technology is applied may be referred to as an XR device. 
     When a projection of the related art connects communication with an Internet-of-Things (IoT) device at home, it just projects information related to the IoT device on a projection plane but has a problem of failing to provide a user with various functions related to the IoT device. 
     SUMMARY OF THE INVENTION 
     Accordingly, the present disclosure is directed to an XR device and method for controlling the same that substantially obviate one or more problems due to limitations and disadvantages of the related art. 
     One object of one embodiment of the present disclosure is to provide an XR device and method for controlling the same, by which an operation of an external device is controllable through user&#39;s manipulations of control components in a manner of projecting a virtual User Interface (UI) including two or more control components for the operation control of the communication-connected external device on a projection plane. 
     Another object of one embodiment of the present disclosure is to provide an XR device and method for controlling the same, by which disposition of the control components are changed according to a state of the projection plane on which the virtual UI is projected. 
     Further object of one embodiment of the present disclosure is to provide an XR device and method for controlling the same, by which disposition of the control components are changed so as to enable the control components to be projected in a manner of avoiding an object existing at a position on which the virtual UI will be projected in the projection plane. 
     Another further object of one embodiment of the present disclosure is to provide an XR device and method for controlling the same, by which the control components are projected so as to prevent the control components from being viewed distortedly according to a material state of the projection plane. 
     Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings. 
     To achieve these objects and other advantages and in accordance with the purpose of the disclosure, as embodied and broadly described herein, an XR device according to one embodiment of the present disclosure may include a communication module communicating with at least one external device, a projection module projecting a virtual User Interface (UI) including a plurality of control components for operation control of the external device on a projection plane, a camera receiving an image including a touch action of a user on the control components projected on the projection plane, and a processor configured to control the external device to perform an operation related to the control component touched by the user based on the captured image, wherein the processor may be further configured to change disposition of the control components based on a state of the projection plane. 
     In another aspect of the present disclosure, as embodied and broadly described herein, a method of controlling an XR device having a transparent display according to another embodiment of the present disclosure may include connecting communication with at least one external device through a communication module, projecting a virtual User Interface (UI) including a plurality of control components for operation control of the external device on a projection plane through a projection module, receiving an image including a user&#39;s touch action on the control components projected on the projection plane through a camera, controlling the external device to perform an operation related to the control component touched by the user based on the captured image, and changing disposition of the control components projected on the projection plane based on a state of the projection plane. 
     It is to be understood that both the foregoing general description and the following detailed description of the present disclosure are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principle of the invention. 
         FIG. 1  is a block diagram illustrating an artificial intelligence (AI) device  1000  according to an embodiment of the present disclosure. 
         FIG. 2  is a block diagram illustrating an AI server  1120  according to an embodiment of the present disclosure. 
         FIG. 3  is a diagram illustrating an AI system according to an embodiment of the present disclosure. 
         FIG. 4  is a block diagram illustrating an extended reality (XR) device according to embodiments of the present disclosure. 
         FIG. 5  is a detailed block diagram illustrating a memory illustrated in  FIG. 4 . 
         FIG. 6  is a block diagram illustrating a point cloud data processing system. 
         FIG. 7  is a block diagram illustrating an XR device  1600  including a learning processor. 
         FIG. 8  is a flowchart illustrating a process of providing an XR service by an XR device  1600  of the present disclosure, illustrated in  FIG. 7 . 
         FIG. 9  is a diagram illustrating the outer appearances of an XR device and a robot. 
         FIG. 10  is a flowchart illustrating a process of controlling a robot by using an XR device. 
         FIG. 11  is a diagram illustrating a vehicle that provides a self-driving service. 
         FIG. 12  is a flowchart illustrating a process of providing an augmented reality/virtual reality (AR/VR) service during a self-driving service in progress. 
         FIG. 13  is a conceptual diagram illustrating an exemplary method for implementing an XR device using an HMD type according to an embodiment of the present disclosure. 
         FIG. 14  is a conceptual diagram illustrating an exemplary method for implementing an XR device using AR glasses according to an embodiment of the present disclosure 
         FIG. 15  is a diagram showing a case of implementing an XR device of an AR projector type according to one embodiment of the present disclosure. 
         FIG. 16  is a block diagram of an AR projector according to one embodiment of the present disclosure. 
         FIG. 17  is a flowchart of a projection control process of a virtual UI of an AR projector according to one embodiment of the present disclosure. 
         FIG. 18  is a diagram to describe a process for projecting a virtual UI according to one embodiment of the present disclosure. 
         FIG. 19  is a diagram to describe a process for projecting control components within a virtual UI in a manner of avoiding an object according to one embodiment of the present disclosure. 
         FIG. 20  is a diagram to describe a process for projecting some of control components within a virtual UI on an object according to one embodiment of the present disclosure. 
         FIG. 21  is a diagram showing a process for projecting some of control components within a virtual UI in a manner of avoiding a dangerous object according to one embodiment of the present disclosure. 
         FIG. 22  is a diagram to describe a process for enlarging and projecting some of control components within a virtual UI according to one embodiment of the present disclosure. 
         FIG. 23  is a diagram to describe a process for displaying a virtual UI on an external device having a screen according to one embodiment of the present disclosure. 
         FIG. 24  is a diagram to describe a process for projecting a virtual UI to control a non-screen external device located in a projection plane according to one embodiment of the present disclosure. 
         FIG. 25  is a diagram to describe a process for linking a virtual UI to an object according to one embodiment of the present disclosure. 
         FIG. 26  is a diagram to describe a process for changing a projection angle of a virtual UI depending on a user&#39;s location according to one embodiment of the present disclosure. 
         FIG. 27  is a diagram to describe a process for projecting a virtual UO on a material of a curved projection plane according to one embodiment of the present disclosure. 
         FIG. 28  is a diagram to describe a process for changing a projection position of a virtual UI depending on a material of a projection plane according to one embodiment of the present disclosure. 
         FIG. 29  is a diagram to describe a process for changing a display style of a virtual UI depending on a material color of a projection plane according to one embodiment of the present disclosure. 
     
    
    
     DESCRIPTION OF SPECIFIC EMBODIMENTS 
     Reference will now be made in detail to embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts, and a redundant description will be avoided. The terms “module” and “unit” are interchangeably used only for easiness of description and thus they should not be considered as having distinctive meanings or roles. Further, a detailed description of well-known technology will not be given in describing embodiments of the present disclosure lest it should obscure the subject matter of the embodiments. The attached drawings are provided to help the understanding of the embodiments of the present disclosure, not limiting the scope of the present disclosure. It is to be understood that the present disclosure covers various modifications, equivalents, and/or alternatives falling within the scope and spirit of the present disclosure. 
     The following embodiments of the present disclosure are intended to embody the present disclosure, not limiting the scope of the present disclosure. What could easily be derived from the detailed description of the present disclosure and the embodiments by a person skilled in the art is interpreted as falling within the scope of the present disclosure. 
     The above embodiments are therefore to be construed in all aspects as illustrative and not restrictive. The scope of the disclosure should be determined by the appended claims and their legal equivalents, not by the above description, and all changes coming within the meaning and equivalency range of the appended claims are intended to be embraced therein. 
     Artificial Intelligence (AI) 
     Artificial intelligence is a field of studying AI or methodologies for creating AI, and machine learning is a field of defining various issues dealt with in the AI field and studying methodologies for addressing the various issues. Machine learning is defined as an algorithm that increases the performance of a certain operation through steady experiences for the operation. 
     An artificial neural network (ANN) is a model used in machine learning and may generically refer to a model having a problem-solving ability, which is composed of artificial neurons (nodes) forming a network via synaptic connections. The ANN may 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 ANN may include an input layer, an output layer, and optionally, one or more hidden layers. Each layer includes one or more neurons, and the ANN may include a synapse that links between neurons. In the ANN, each neuron may output the function value of the activation function, for the input of signals, weights, and deflections through the synapse. 
     Model parameters refer to parameters determined through learning and include a weight value of a synaptic connection and deflection of neurons. A hyperparameter means a parameter to be set in the machine learning algorithm before learning, and includes a learning rate, a repetition number, a mini batch size, and an initialization function. 
     The purpose of learning of the ANN may be to determine 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 ANN. 
     Machine learning may be classified into supervised learning, unsupervised learning, and reinforcement learning according to learning methods. 
     Supervised learning may be a method of training an ANN in a state in which a label for training data is given, and the label may mean a correct answer (or result value) that the ANN should infer with respect to the input of training data to the ANN. Unsupervised learning may be a method of training an ANN in a state in which a label for training data is not given. Reinforcement learning may be a learning method in which an agent defined in a certain environment is trained to select a behavior or a behavior sequence that maximizes cumulative compensation in each state. 
     Machine learning, which is implemented by a deep neural network (DNN) including a plurality of hidden layers among ANNs, is also referred to as deep learning, and deep learning is part of machine learning. The following description is given with the appreciation that machine learning includes deep learning. 
     &lt;Robot&gt; 
     A robot may refer to a machine that automatically processes or executes a given task by its own capabilities. Particularly, a robot equipped with a function of recognizing an environment and performing an operation based on its decision may be referred to as an intelligent robot. 
     Robots may be classified into industrial robots, medical robots, consumer robots, military robots, and so on according to their usages or application fields. 
     A robot may be provided with a driving unit including an actuator or a motor, and thus perform various physical operations such as moving robot joints. Further, a movable robot may include a wheel, a brake, a propeller, and the like in a driving unit, and thus travel on the ground or fly in the air through the driving unit. 
     &lt;Self-Driving&gt; 
     Self-driving refers to autonomous driving, and a self-driving vehicle refers to a vehicle that travels with no user manipulation or minimum user manipulation. 
     For example, self-driving may include a technology of maintaining a lane while driving, a technology of automatically adjusting a speed, such as adaptive cruise control, a technology of automatically traveling along a predetermined route, and a technology of automatically setting a route and traveling along the route when a destination is set. 
     Vehicles may include a vehicle having only an internal combustion engine, a hybrid vehicle having both an internal combustion engine and an electric motor, 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. 
     Herein, a self-driving vehicle may be regarded as a robot having a self-driving function. 
     &lt;eXtended Reality (XR)&gt; 
     Extended reality is a generical term covering virtual reality (VR), augmented reality (AR), and mixed reality (MR). VR provides a real-world object and background only as a computer graphic (CG) image, AR provides a virtual CG image on a real object image, and MR is a computer graphic technology that mixes and combines virtual objects into the real world. 
     MR is similar to AR in that the real object and the virtual object are shown together. However, in AR, the virtual object is used as a complement to the real object, whereas in MR, the virtual object and the real object are handled equally. 
     XR may be applied to a head-mounted display (HMD), a head-up display (HUD), a portable phone, a tablet PC, a laptop computer, a desktop computer, a TV, a digital signage, and so on. A device to which XR is applied may be referred to as an XR device. 
       FIG. 1  is a block diagram illustrating an artificial intelligence (AI) device  1000  according to an embodiment of the present disclosure. 
     The AI device  1000  illustrated in  FIG. 10  may be configured as a stationary device or a mobile device, such as a TV, a projector, a portable phone, a smartphone, a desktop computer, a laptop computer, a digital broadcasting terminal, a personal digital assistant (PDA), a portable multimedia player (PMP), a navigation device, a tablet PC, a wearable device, a set-top box (STB), a digital multimedia broadcasting (DMB) receiver, a radio, a washing machine, a refrigerator, a digital signage, a robot, or a vehicle. 
     Referring to  FIG. 1 , the AI device  1000  may include a communication unit  1010 , an input unit  1020 , a learning processor  1030 , a sensing unit  1040 , an output unit  1050 , a memory  1070 , and a processor  1080 . 
     The communication unit  1010  may transmit and receive data to and from an external device such as another AI device or an AI server by wired or wireless communication. For example, the communication unit  1010  may transmit and receive sensor information, a user input, a learning model, and a control signal to and from the external device. 
     Communication schemes used by the communication unit  1010  include global system for mobile communication (GSM), CDMA, LTE, 5G, wireless local area network (WLAN), wireless fidelity (Wi-Fi), Bluetooth™, radio frequency identification (RFID), infrared data association (IrDA), ZigBee, near field communication (NFC), and so on. Particularly, the 5G technology described. 
     The input unit  1020  may acquire various types of data. The input unit  1020  may 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 thus a signal acquired from the camera or the microphone may be referred to as sensing data or sensor information. 
     The input unit  1020  may acquire training data for model training and input data to be used to acquire an output by using a learning model. The input unit  1020  may acquire raw input data. In this case, the processor  1080  or the learning processor  1030  may extract an input feature by preprocessing the input data. 
     The learning processor  1030  may train a model composed of an ANN by using training data. The trained ANN may be referred to as a learning model. The learning model may be used to infer a result value for new input data, not training data, and the inferred value may be used as a basis for determination to perform a certain operation. 
     The learning processor  1030  may perform AI processing together with a learning processor of an AI server. 
     The learning processor  1030  may include a memory integrated or implemented in the AI device  1000 . Alternatively, the learning processor  1030  may be implemented by using the memory  1070 , an external memory directly connected to the Al device  1000 , or a memory maintained in an external device. 
     The sensing unit  1040  may acquire at least one of internal information about the AI device  1000 , ambient environment information about the AI device  1000 , and user information by using various sensors. 
     The sensors included in the sensing unit  1040  may include a proximity sensor, an illumination sensor, an accelerator sensor, a magnetic sensor, a gyro sensor, an inertial sensor, a red, green, blue (RGB) sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, an optical sensor, a microphone, a light detection and ranging (LiDAR), and a radar. 
     The output unit  1050  may generate a visual, auditory, or haptic output. 
     Accordingly, the output unit  1050  may include a display unit for outputting visual information, a speaker for outputting auditory information, and a haptic module for outputting haptic information. 
     The memory  1070  may store data that supports various functions of the AI device  1000 . For example, the memory  1070  may store input data acquired by the input unit  1020 , training data, a learning model, a learning history, and so on. 
     The processor  1080  may determine at least one executable operation of the AI device  100  based on information determined or generated by a data analysis algorithm or a machine learning algorithm. The processor  1080  may control the components of the AI device  1000  to execute the determined operation. 
     To this end, the processor  1080  may request, search, receive, or utilize data of the learning processor  1030  or the memory  1070 . The processor  1080  may control the components of the AI device  1000  to execute a predicted operation or an operation determined to be desirable among the at least one executable operation. 
     When the determined operation needs to be performed in conjunction with an external device, the processor  1080  may generate a control signal for controlling the external device and transmit the generated control signal to the external device. 
     The processor  1080  may acquire intention information with respect to a user input and determine the user&#39;s requirements based on the acquired intention information. 
     The processor  1080  may acquire the intention information corresponding to the user input by using at least one of a speech to text (STT) engine for converting a 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 ANN, at least part of which is trained according to the machine learning algorithm. At least one of the STT engine or the NLP engine may be trained by the learning processor, a learning processor of the AI server, or distributed processing of the learning processors. For reference, specific components of the AI server are illustrated in  FIG. 2 . 
     The processor  1080  may collect history information including the operation contents of the AI device  1000  or the user&#39;s feedback on the operation and may store the collected history information in the memory  1070  or the learning processor  1030  or transmit the collected history information to the external device such as the AI server. The collected history information may be used to update the learning model. 
     The processor  1080  may control at least a part of the components of AI device  1000  so as to drive an application program stored in the memory  1070 . Furthermore, the processor  1080  may operate two or more of the components included in the AI device  1000  in combination so as to drive the application program. 
       FIG. 2  is a block diagram illustrating an AI server  1120  according to an embodiment of the present disclosure. 
     Referring to  FIG. 2 , the AI server  1120  may refer to a device that trains an ANN by a machine learning algorithm or uses a trained ANN. The AI server  1120  may include a plurality of servers to perform distributed processing, or may be defined as a 5G network. The AI server  1120  may be included as part of the AI device  1100 , and perform at least part of the AI processing. 
     The AI server  1120  may include a communication unit  1121 , a memory  1123 , a learning processor  1122 , a processor  1126 , and so on. 
     The communication unit  1121  may transmit and receive data to and from an external device such as the AI device  1100 . 
     The memory  1123  may include a model storage  1124 . The model storage  1124  may store a model (or an ANN  1125 ) which has been trained or is being trained through the learning processor  1122 . 
     The learning processor  1122  may train the ANN  1125  by training data. The learning model may be used, while being loaded on the AI server  1120  of the ANN, or on an external device such as the AI device  1110 . 
     The learning model may be implemented in hardware, software, or a combination of hardware and software. If all or part of the learning model is implemented in software, one or more instructions of the learning model may be stored in the memory  1123 . 
     The processor  1126  may infer a 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. 3  is a diagram illustrating an AI system according to an embodiment of the present disclosure. 
     Referring to  FIG. 3 , in the AI system, at least one of an AI server  1260 , a robot  1210 , a self-driving vehicle  1220 , an XR device  1230 , a smartphone  1240 , or a home appliance  1250  is connected to a cloud network  1200 . The robot  1210 , the self-driving vehicle  1220 , the XR device  1230 , the smartphone  1240 , or the home appliance  1250 , to which AI is applied, may be referred to as an AI device. 
     The cloud network  1200  may refer to a network that forms part of cloud computing infrastructure or exists in the cloud computing infrastructure. The cloud network  1200  may be configured by using a 3G network, a 4G or LTE network, or a 5G network. 
     That is, the devices  1210  to  1260  included in the AI system may be interconnected via the cloud network  1200 . In particular, each of the devices  1210  to  1260  may communicate with each other directly or through a BS. 
     The AI server  1260  may include a server that performs AI processing and a server that performs computation on big data. 
     The AI server  1260  may be connected to at least one of the AI devices included in the AI system, that is, at least one of the robot  1210 , the self-driving vehicle  1220 , the XR device  1230 , the smartphone  1240 , or the home appliance  1250  via the cloud network  1200 , and may assist at least part of AI processing of the connected AI devices  1210  to  1250 . 
     The AI server  1260  may train the ANN according to the machine learning algorithm on behalf of the AI devices  1210  to  1250 , and may directly store the learning model or transmit the learning model to the AI devices  1210  to  1250 . 
     The AI server  1260  may receive input data from the AI devices  1210  to  1250 , infer a result value for received input data by using the learning model, generate a response or a control command based on the inferred result value, and transmit the response or the control command to the AI devices  1210  to  1250 . 
     Alternatively, the AI devices  1210  to  1250  may infer the result value for the input data by directly using the learning model, and generate the response or the control command based on the inference result. 
     Hereinafter, various embodiments of the AI devices  1210  to  1250  to which the above-described technology is applied will be described. The AI devices  1210  to  1250  illustrated in  FIG. 3  may be regarded as a specific embodiment of the AI device  1000  illustrated in  FIG. 1 . 
     &lt;AI+XR&gt; 
     The XR device  1230 , to which AI is applied, may be configured as a HMD, a HUD provided in a vehicle, a TV, a portable phone, a smartphone, a computer, a wearable device, a home appliance, a digital signage, a vehicle, a fixed robot, a mobile robot, or the like. 
     The XR device  1230  may acquire information about a surrounding space or a real object by analyzing 3D point cloud data or image data acquired from various sensors or an external device and thus generating position data and attribute data for the 3D points, and may render an XR object to be output. For example, the XR device  1230  may output an XR object including additional information about a recognized object in correspondence with the recognized object. 
     The XR device  1230  may perform the above-described operations by using the learning model composed of at least one ANN. For example, the XR device  1230  may recognize a real object from 3D point cloud data or image data by using the learning model, and may provide information corresponding to the recognized real object. The learning model may be trained directly by the XR device  1230  or by the external device such as the AI server  1260 . 
     While the XR device  1230  may operate by generating a result by directly using the learning model, the XR device  1230  may operate by transmitting sensor information to the external device such as the AI server  1260  and receiving the result. 
     &lt;AI+Robot+XR&gt; 
     The robot  1210 , to which AI and XR are applied, may be implemented as a guide robot, a delivery robot, a cleaning robot, a wearable robot, an entertainment robot, a pet robot, an unmanned flying robot, a drone, or the like. 
     The robot  1210 , to which XR is applied, may refer to a robot to be controlled/interact within an XR image. In this case, the robot  1210  may be distinguished from the XR device  1230  and interwork with the XR device  1230 . 
     When the robot  1210  to be controlled/interact within an XR image acquires sensor information from sensors each including a camera, the robot  1210  or the XR device  1230  may generate an XR image based on the sensor information, and the XR device  1230  may output the generated XR image. The robot  1210  may operate based on the control signal received through the XR device  1230  or based on the user&#39;s interaction. 
     For example, the user may check an XR image corresponding to a view of the robot  1210  interworking remotely through an external device such as the XR device  1210 , adjust a self-driving route of the robot  1210  through interaction, control the operation or driving of the robot  1210 , or check information about an ambient object around the robot  1210 . 
     &lt;AI+Self-Driving+XR&gt; 
     The self-driving vehicle  1220 , to which AI and XR are applied, may be implemented as a mobile robot, a vehicle, an unmanned flying vehicle, or the like. 
     The self-driving driving vehicle  1220 , to which XR is applied, may refer to a self-driving vehicle provided with a means for providing an XR image or a self-driving vehicle to be controlled/interact within an XR image. Particularly, the self-driving vehicle  1220  to be controlled/interact within an XR image may be distinguished from the XR device  1230  and interwork with the XR device  1230 . 
     The self-driving vehicle  1220  provided with the means for providing an XR image may acquire sensor information from the sensors each including a camera and output the generated XR image based on the acquired sensor information. For example, the self-driving vehicle  1220  may include an HUD to output an XR image, thereby providing a passenger with an XR object corresponding to a real object or an object on the screen. 
     When the XR object is output to the HUD, at least part of the XR object may be output to be overlaid on an actual object to which the passenger&#39;s gaze is directed. When the XR object is output to a display provided in the self-driving vehicle  1220 , at least part of the XR object may be output to be overlaid on the object within the screen. For example, the self-driving vehicle  1220  may output XR objects corresponding to objects such as a lane, another vehicle, a traffic light, a traffic sign, a two-wheeled vehicle, a pedestrian, a building, and so on. 
     When the self-driving vehicle  1220  to be controlled/interact within an XR image acquires sensor information from the sensors each including a camera, the self-driving vehicle  1220  or the XR device  1230  may generate the XR image based on the sensor information, and the XR device  1230  may output the generated XR image. The self-driving vehicle  1220  may operate based on a control signal received through an external device such as the XR device  1230  or based on the user&#39;s interaction. 
     VR, AR, and MR technologies of the present disclosure are applicable to various devices, particularly, for example, a HMD, a HUD attached to a vehicle, a portable phone, a tablet PC, a laptop computer, a desktop computer, a TV, and a signage. The VR, AR, and MR technologies may also be applicable to a device equipped with a flexible or rollable display. 
     The above-described VR, AR, and MR technologies may be implemented based on CG and distinguished by the ratios of a CG image in an image viewed by the user. 
     That is, VR provides a real object or background only in a CG image, whereas AR overlays a virtual CG image on an image of a real object. 
     MR is similar to AR in that virtual objects are mixed and combined with a real world. However, a real object and a virtual object created as a CG image are distinctive from each other and the virtual object is used to complement the real object in AR, whereas a virtual object and a real object are handled equally in MR. More specifically, for example, a hologram service is an MR representation. 
     These days, VR, AR, and MR are collectively called XR without distinction among them. Therefore, embodiments of the present disclosure are applicable to all of VR, AR, MR, and XR. 
     For example, wired/wireless communication, input interfacing, output interfacing, and computing devices are available as hardware (HW)-related element techniques applied to VR, AR, MR, and XR. Further, tracking and matching, speech recognition, interaction and user interfacing, location-based service, search, and AI are available as software (SW)-related element techniques. 
     Particularly, the embodiments of the present disclosure are intended to address at least one of the issues of communication with another device, efficient memory use, data throughput decrease caused by inconvenient user experience/user interface (UX/UI), video, sound, motion sickness, or other issues. 
       FIG. 4  is a block diagram illustrating an extended reality (XR) device according to embodiments of the present disclosure. The XR device  1300  includes a camera  1310 , a display  1320 , a sensor  1330 , a processor  1340 , a memory  1350 , and a communication module  1360 . Obviously, one or more of the modules may be deleted or modified, and one or more modules may be added to the modules, when needed, without departing from the scope and spirit of the present disclosure. 
     The communication module  1360  may communicate with an external device or a server, wiredly or wirelessly. The communication module  1360  may use, for example, Wi-Fi, Bluetooth, or the like, for short-range wireless communication, and for example, a 3GPP communication standard for long-range wireless communication. LTE is a technology beyond 3GPP TS 36.xxx Release 8. Specifically, LTE beyond 3GPP TS 36.xxx Release 10 is referred to as LTE-A, and LTE beyond 3GPP TS 36.xxx Release 13 is referred to as LTE-A pro. 3GPP 5G refers to a technology beyond TS 36.xxx Release 15 and a technology beyond TS 38.XXX Release 15. Specifically, the technology beyond TS 38.xxx Release 15 is referred to as 3GPP NR, and the technology beyond TS 36.xxx Release 15 is referred to as enhanced LTE. “xxx” represents the number of a technical specification. LTE/NR may be collectively referred to as a 3GPP system. 
     The camera  1310  may capture an ambient environment of the XR device  1300  and convert the captured image to an electric signal. The image, which has been captured and converted to an electric signal by the camera  1310 , may be stored in the memory  1350  and then displayed on the display  1320  through the processor  1340 . Further, the image may be displayed on the display  1320  by the processor  1340 , without being stored in the memory  1350 . Further, the camera  110  may have a field of view (FoV). The FoV is, for example, an area in which a real object around the camera  1310  may be detected. The camera  1310  may detect only a real object within the FoV. When a real object is located within the FoV of the camera  1310 , the XR device  1300  may display an AR object corresponding to the real object. Further, the camera  1310  may detect an angle between the camera  1310  and the real object. 
     The sensor  1330  may include at least one sensor. For example, the sensor  1330  includes a sensing means such as a gravity sensor, a geomagnetic sensor, a motion sensor, a gyro sensor, an accelerator sensor, an inclination sensor, a brightness sensor, an altitude sensor, an olfactory sensor, a temperature sensor, a depth sensor, a pressure sensor, a bending sensor, an audio sensor, a video sensor, a global positioning system (GPS) sensor, and a touch sensor. Further, although the display  1320  may be of a fixed type, the display  1320  may be configured as a liquid crystal display (LCD), an organic light emitting diode (OLED) display, an electroluminescent display (ELD), or a micro LED (M-LED) display, to have flexibility. Herein, the sensor  1330  is designed to detect a bending degree of the display  1320  configured as the afore-described LCD, OLED display, ELD, or M-LED display. 
     The memory  1350  is equipped with a function of storing all or a part of result values obtained by wired/wireless communication with an external device or a service as well as a function of storing an image captured by the camera  1310 . Particularly, considering the trend toward increased communication data traffic (e.g., in a 5G communication environment), efficient memory management is required. In this regard, a description will be given below with reference to  FIG. 5 . 
       FIG. 5  is a detailed block diagram illustrating a memory illustrated in  FIG. 4 . With reference to  FIG. 5 , a swap-out process between a random access memory (RAM) and a flash memory according to an embodiment of the present disclosure will be described. 
     When swapping out AR/VR page data from a RAM  1410  to a flash memory  1420 , a controller  1430  may swap out only one of two or more AR/VR page data of the same contents among AR/VR page data to be swapped out to the flash memory  1420 . 
     That is, the controller  1430  may calculate an identifier (e.g., a hash function) that identifies each of the contents of the AR/VR page data to be swapped out, and determine that two or more AR/VR page data having the same identifier among the calculated identifiers contain the same contents. Accordingly, the problem that the lifetime of an AR/VR device including the flash memory  1420  as well as the lifetime of the flash memory  1420  is reduced because unnecessary AR/VR page data is stored in the flash memory  1420  may be overcome. 
     The operations of the controller  1430  may be implemented in software or hardware without departing from the scope of the present disclosure. More specifically, the memory illustrated in  FIG. 14  is included in a HMD, a vehicle, a portable phone, a tablet PC, a laptop computer, a desktop computer, a TV, a signage, or the like, and executes a swap function. 
     A device according to embodiments of the present disclosure may process 3D point cloud data to provide various services such as VR, AR, MR, XR, and self-driving to a user. 
     A sensor collecting 3D point cloud data may be any of, for example, a LiDAR, a red, green, blue depth (RGB-D), and a 3D laser scanner. The sensor may be mounted inside or outside of a HMD, a vehicle, a portable phone, a tablet PC, a laptop computer, a desktop computer, a TV, a signage, or the like. 
       FIG. 6  is a block diagram illustrating a point cloud data processing system. 
     Referring to  FIG. 6 , a point cloud processing system  1500  includes a transmission device which acquires, encodes, and transmits point cloud data, and a reception device which acquires point cloud data by receiving and decoding video data. As illustrated in  FIG. 6 , point cloud data according to embodiments of the present disclosure may be acquired by capturing, synthesizing, or generating the point cloud data (S 1510 ). During the acquisition, data (e.g., a polygon file format or standard triangle format (PLY) file) of 3D positions (x, y, z)/attributes (color, reflectance, transparency, and so on) of points may be generated. For a video of multiple frames, one or more files may be acquired. Point cloud data-related metadata (e.g., metadata related to capturing) may be generated during the capturing. The transmission device or encoder according to embodiments of the present disclosure may encode the point cloud data by video-based point cloud compression (V-PCC) or geometry-based point cloud compression (G-PCC), and output one or more video streams (S 1520 ). V-PCC is a scheme of compressing point cloud data based on a 2D video codec such as high efficiency video coding (HEVC) or versatile video coding (VVC), G-PCC is a scheme of encoding point cloud data separately into two streams: geometry and attribute. The geometry stream may be generated by reconstructing and encoding position information about points, and the attribute stream may be generated by reconstructing and encoding attribute information (e.g., color) related to each point. In V-PCC, despite compatibility with a 2D video, much data is required to recover V-PCC-processed data (e.g., geometry video, attribute video, occupancy map video, and auxiliary information), compared to G-PCC, thereby causing a long latency in providing a service. One or more output bit streams may be encapsulated along with related metadata in the form of a file (e.g., a file format such as ISOBMFF) and transmitted over a network or through a digital storage medium (S 1530 ). 
     The device or processor according to embodiments of the present disclosure may acquire one or more bit streams and related metadata by decapsulating the received video data, and recover 3D point cloud data by decoding the acquired bit streams in V-PCC or G-PCC (S 1540 ). A renderer may render the decoded point cloud data and provide content suitable for VR/AR/MR/service to the user on a display (S 1550 ). 
     As illustrated in  FIG. 6 , the device or processor according to embodiments of the present disclosure may perform a feedback process of transmitting various pieces of feedback information acquired during the rendering/display to the transmission device or to the decoding process (S 1560 ). The feedback information according to embodiments of the present disclosure may include head orientation information, viewport information indicating an area that the user is viewing, and so on. Because the user interacts with a service (or content) provider through the feedback process, the device according to embodiments of the present disclosure may provide a higher data processing speed by using the afore-described V-PCC or G-PCC scheme or may enable clear video construction as well as provide various services in consideration of high user convenience. 
       FIG. 7  is a block diagram illustrating an XR device  1600  including a learning processor. Compared to  FIG. 4 , only a learning processor  1670  is added, and thus a redundant description is avoided because  FIG. 4  may be referred to for the other components. 
     Referring to  FIG. 7 , the XR device  1600  may be loaded with a learning model. The learning model may be implemented in hardware, software, or a combination of hardware and software. If the whole or part of the learning model is implemented in software, one or more instructions that form the learning model may be stored in a memory  1650 . 
     According to embodiments of the present disclosure, a learning processor  1670  may be coupled communicably to a processor  1640 , and repeatedly train a model including ANNs by using training data. An ANN is an information processing system in which multiple neurons are linked in layers, modeling an operation principle of biological neurons and links between neurons. An ANN is a statistical learning algorithm inspired by a neural network (particularly the brain in the central nervous system of an animal) in machine learning and cognitive science. Machine learning is one field of AI, in which the ability of learning without an explicit program is granted to a computer. Machine learning is a technology of studying and constructing a system for learning, predicting, and improving its capability based on empirical data, and an algorithm for the system. Therefore, according to embodiments of the present disclosure, the learning processor  1670  may infer a result value from new input data by determining optimized model parameters of an ANN. Therefore, the learning processor  1670  may analyze a device use pattern of a user based on device use history information about the user. Further, the learning processor  1670  may be configured to receive, classify, store, and output information to be used for data mining, data analysis, intelligent decision, and a machine learning algorithm and technique. 
     According to embodiments of the present disclosure, the processor  1640  may determine or predict at least one executable operation of the device based on data analyzed or generated by the learning processor  1670 . Further, the processor  1640  may request, search, receive, or use data of the learning processor  1670 , and control the XR device  1600  to perform a predicted operation or an operation determined to be desirable among the at least one executable operation. According to embodiments of the present disclosure, the processor  1640  may execute various functions of realizing intelligent emulation (i.e., knowledge-based system, reasoning system, and knowledge acquisition system). The various functions may be applied to an adaptation system, a machine learning system, and various types of systems including an ANN (e.g., a fuzzy logic system). That is, the processor  1640  may predict a user&#39;s device use pattern based on data of a use pattern analyzed by the learning processor  1670 , and control the XR device  1600  to provide a more suitable XR service to the UE. Herein, the XR service includes at least one of the AR service, the VR service, or the MR service. 
       FIG. 8  is a flowchart illustrating a process of providing an XR service by an XR device  1600  of the present disclosure, illustrated in  FIG. 7 . 
     According to embodiments of the present disclosure, the processor  1670  may store device use history information about a user in the memory  1650  (S 1710 ). The device use history information may include information about the name, category, and contents of content provided to the user, information about a time at which a device has been used, information about a place in which the device has been used, time information, and information about use of an application installed in the device. 
     According to embodiments of the present disclosure, the learning processor  1670  may acquire device use pattern information about the user by analyzing the device use history information (S 1720 ). For example, when the XR device  1600  provides specific content A to the user, the learning processor  1670  may learn information about a pattern of the device used by the user using the corresponding terminal by combining specific information about content A (e.g., information about the ages of users that generally use content A, information about the contents of content A, and content information similar to content A), and information about the time points, places, and number of times in which the user using the corresponding terminal has consumed content A. 
     According to embodiments of the present disclosure, the processor  1640  may acquire the user device pattern information generated based on the information learned by the learning processor  1670 , and generate device use pattern prediction information (S 1730 ). Further, when the user is not using the device  1600 , if the processor  1640  determines that the user is located in a place where the user has frequently used the device  1600 , or it is almost time for the user to usually use the device  1600 , the processor  1640  may indicate the device  1600  to operate. In this case, the device according to embodiments of the present disclosure may provide AR content based on the user pattern prediction information (S 1740 ). 
     When the user is using the device  1600 , the processor  1640  may check information about content currently provided to the user, and generate device use pattern prediction information about the user in relation to the content (e.g., when the user requests other related content or additional data related to the current content). Further, the processor  1640  may provide AR content based on the device use pattern prediction information by indicating the device  1600  to operate (S 1740 ). The AR content according to embodiments of the present disclosure may include an advertisement, navigation information, danger information, and so on. 
       FIG. 9  is a diagram illustrating the outer appearances of an XR device and a robot. 
     Component modules of an XR device  1800  according to an embodiment of the present disclosure have been described before with reference to the previous drawings, and thus a redundant description is not provided herein. 
     The outer appearance of a robot  1810  illustrated in  FIG. 9  is merely an example, and the robot  1810  may be implemented to have various outer appearances according to the present disclosure. For example, the robot  1810  illustrated in  FIG. 18  may be a drone, a cleaner, a cook root, a wearable robot, or the like. Particularly, each component of the robot  1810  may be disposed at a different position such as up, down, left, right, back, or forth according to the shape of the robot  1810 . 
     The robot  1810  may be provided, on the exterior thereof, with various sensors to identify ambient objects. Further, to provide specific information to a user, the robot  1810  may be provided with an interface unit  1811  on top or the rear surface  1812  thereof. 
     To sense movement of the robot  1810  and an ambient object, and control the robot  1810 , a robot control module  1850  is mounted inside the robot  1810 . The robot control module  1850  may be implemented as a software module or a hardware chip with the software module implemented therein. The robot control module  1850  may include a deep learner  1851 , a sensing information processor  1852 , a movement path generator  1853 , and a communication module  1854 . 
     The sensing information processor  1852  collects and processes information sensed by various types of sensors (e.g., a LiDAR sensor, an IR sensor, an ultrasonic sensor, a depth sensor, an image sensor, and a microphone) arranged in the robot  1810 . 
     The deep learner  1851  may receive information processed by the sensing information processor  1851  or accumulative information stored during movement of the robot  1810 , and output a result required for the robot  1810  to determine an ambient situation, process information, or generate a moving path. 
     The moving path generator  1852  may calculate a moving path of the robot  1810  by using the data calculated by the deep learner  8151  or the data processed by the sensing information processor  1852 . 
     Because each of the XR device  1800  and the robot  1810  is provided with a communication module, the XR device  1800  and the robot  1810  may transmit and receive data by short-range wireless communication such as Wi-Fi or Bluetooth, or 5G long-range wireless communication. A technique of controlling the robot  1810  by using the XR device  1800  will be described below with reference to  FIG. 10 . 
       FIG. 10  is a flowchart illustrating a process of controlling a robot by using an XR device. 
     The XR device and the robot are connected communicably to a 5G network (S 1901 ). Obviously, the XR device and the robot may transmit and receive data by any other short-range or long-range communication technology without departing from the scope of the present disclosure. 
     The robot captures an image/video of the surroundings of the robot by means of at least one camera installed on the interior or exterior of the robot (S 1902 ) and transmits the captured image/video to the XR device (S 1903 ). The XR device displays the captured image/video (S 1904 ) and transmits a command for controlling the robot to the robot (S 1905 ). The command may be input manually by a user of the XR device or automatically generated by AI without departing from the scope of the disclosure. 
     The robot executes a function corresponding to the command received in step S 1905  (S 1906 ) and transmits a result value to the XR device (S 1907 ). The result value may be a general indicator indicating whether data has been successfully processed or not, a current captured image, or specific data in which the XR device is considered. The specific data is designed to change, for example, according to the state of the XR device. If a display of the XR device is in an off state, a command for turning on the display of the XR device is included in the result value in step S 1907 . Therefore, when an emergency situation occurs around the robot, even though the display of the remote XR device is turned off, a notification message may be transmitted. 
     AR/VR content is displayed according to the result value received in step S 1907  (S 1908 ). 
     According to another embodiment of the present disclosure, the XR device may display position information about the robot by using a GPS module attached to the robot. 
     The XR device  1300  described with reference to  FIG. 4  may be connected to a vehicle that provides a self-driving service in a manner that allows wired/wireless communication, or may be mounted on the vehicle that provides the self-driving service. Accordingly, various services including AR/VR may be provided even in the vehicle that provides the self-driving service. 
       FIG. 11  is a diagram illustrating a vehicle that provides a self-driving service. 
     According to embodiments of the present disclosure, a vehicle  2010  may include a car, a train, and a motor bike as transportation means traveling on a road or a railway. According to embodiments of the present disclosure, the vehicle  2010  may include all of an internal combustion engine vehicle provided with an engine as a power source, a hybrid vehicle provided with an engine and an electric motor as a power source, and an electric vehicle provided with an electric motor as a power source. 
     According to embodiments of the present disclosure, the vehicle  2010  may include the following components in order to control operations of the vehicle  2010 : a user interface device, an object detection device, a communication device, a driving maneuver device, a main electronic control unit (ECU), a drive control device, a self-driving device, a sensing unit, and a position data generation device. 
     Each of the user interface device, the object detection device, the communication device, the driving maneuver device, the main ECU, the drive control device, the self-driving device, the sensing unit, and the position data generation device may generate an electric signal, and be implemented as an electronic device that exchanges electric signals. 
     The user interface device may receive a user input and provide information generated from the vehicle  2010  to a user in the form of a UI or UX. The user interface device may include an input/output (I/O) device and a user monitoring device. The object detection device may detect the presence or absence of an object outside of the vehicle  2010 , and generate information about the object. The object detection device may include at least one of, for example, a camera, a LiDAR, an IR sensor, or an ultrasonic sensor. The camera may generate information about an object outside of the vehicle  2010 . The camera may include one or more lenses, one or more image sensors, and one or more processors for generating object information. The camera may acquire information about the position, distance, or relative speed of an object by various image processing algorithms. Further, the camera may be mounted at a position where the camera may secure an FoV in the vehicle  2010 , to capture an image of the surroundings of the vehicle  1020 , and may be used to provide an AR/VR-based service. The LiDAR may generate information about an object outside of the vehicle  2010 . The LiDAR may include a light transmitter, a light receiver, and at least one processor which is electrically coupled to the light transmitter and the light receiver, processes a received signal, and generates data about an object based on the processed signal. 
     The communication device may exchange signals with a device (e.g., infrastructure such as a server or a broadcasting station), another vehicle, or a terminal) outside of the vehicle  2010 . The driving maneuver device is a device that receives a user input for driving. In manual mode, the vehicle  2010  may travel based on a signal provided by the driving maneuver device. The driving maneuver device may include a steering input device (e.g., a steering wheel), an acceleration input device (e.g., an accelerator pedal), and a brake input device (e.g., a brake pedal). 
     The sensing unit may sense a state of the vehicle  2010  and generate state information. The position data generation device may generate position data of the vehicle  2010 . The position data generation device may include at least one of a GPS or a differential global positioning system (DGPS). The position data generation device may generate position data of the vehicle  2010  based on a signal generated from at least one of the GPS or the DGPS. The main ECU may provide overall control to at least one electronic device provided in the vehicle  2010 , and the drive control device may electrically control a vehicle drive device in the vehicle  2010 . 
     The self-driving device may generate a path for the self-driving service based on data acquired from the object detection device, the sensing unit, the position data generation device, and so on. The self-driving device may generate a driving plan for driving along the generated path, and generate a signal for controlling movement of the vehicle according to the driving plan. The signal generated from the self-driving device is transmitted to the drive control device, and thus the drive control device may control the vehicle drive device in the vehicle  2010 . 
     As illustrated in  FIG. 11 , the vehicle  2010  that provides the self-driving service is connected to an XR device  2000  in a manner that allows wired/wireless communication. The XR device  2000  may include a processor  2001  and a memory  2002 . While not shown, the XR device  2000  of  FIG. 11  may further include the components of the XR device  1300  described before with reference to  FIG. 4 . 
     If the XR device  2000  is connected to the vehicle  2010  in a manner that allows wired/wireless communication. The XR device  2000  may receive/process AR/VR service-related content data that may be provided along with the self-driving service, and transmit the received/processed AR/VR service-related content data to the vehicle  2010 . Further, when the XR device  2000  is mounted on the vehicle  2010 , the XR device  2000  may receive/process AR/VR service-related content data according to a user input signal received through the user interface device and provide the received/processed AR/VR service-related content data to the user. In this case, the processor  2001  may receive/process the AR/VR service-related content data based on data acquired from the object detection device, the sensing unit, the position data generation device, the self-driving device, and so on. According to embodiments of the present disclosure, the AR/VR service-related content data may include entertainment content, weather information, and so on which are not related to the self-driving service as well as information related to the self-driving service such as driving information, path information for the self-driving service, driving maneuver information, vehicle state information, and object information. 
       FIG. 12  is a flowchart illustrating a process of providing an augmented reality/virtual reality (AR/VR) service during a self-driving service in progress. 
     According to embodiments of the present disclosure, a vehicle or a user interface device may receive a user input signal (S 2110 ). According to embodiments of the present disclosure, the user input signal may include a signal indicating a self-driving service. According to embodiments of the present disclosure, the self-driving service may include a full self-driving service and a general self-driving service. The full self-driving service refers to perfect self-driving of a vehicle to a destination without a user&#39;s manual driving, whereas the general self-driving service refers to driving a vehicle to a destination through a user&#39;s manual driving and self-driving in combination. 
     It may be determined whether the user input signal according to embodiments of the present disclosure corresponds to the full self-driving service (S 2120 ). When it is determined that the user input signal corresponds to the full self-driving service, the vehicle according to embodiments of the present disclosure may provide the full self-driving service (S 2130 ). Because the full self-driving service does not need the user&#39;s manipulation, the vehicle according to embodiments of the present disclosure may provide VR service-related content to the user through a window of the vehicle, a side mirror of the vehicle, an HMD, or a smartphone (S 2130 ). The VR service-related content according to embodiments of the present disclosure may be content related to full self-driving (e.g., navigation information, driving information, and external object information), and may also be content which is not related to full self-driving according to user selection (e.g., weather information, a distance image, a nature image, and a voice call image). 
     If it is determined that the user input signal does not correspond to the full self-driving service, the vehicle according to embodiments of the present disclosure may provide the general self-driving service (S 2140 ). Because the FoV of the user should be secured for the user&#39;s manual driving in the general self-driving service, the vehicle according to embodiments of the present disclosure may provide AR service-related content to the user through a window of the vehicle, a side mirror of the vehicle, an HMD, or a smartphone (S 2140 ). 
     The AR service-related content according to embodiments of the present disclosure may be content related to full self-driving (e.g., navigation information, driving information, and external object information), and may also be content which is not related to self-driving according to user selection (e.g., weather information, a distance image, a nature image, and a voice call image). 
     While the present disclosure is applicable to all the fields of 5G communication, robot, self-driving, and AI as described before, the following description will be given mainly of the present disclosure applicable to an XR device with reference to following figures. 
       FIG. 13  is a conceptual diagram illustrating an exemplary method for implementing an XR device using an HMD type according to an embodiment of the present disclosure. The above-mentioned embodiments may also be implemented in HMD types shown in  FIG. 13 . 
     The HMD-type XR device  100   a  shown in  FIG. 13  may include a communication unit  110 , a control unit  120 , a memory unit  130 , an input/output (I/O) unit  140   a , a sensor unit  140   b , a power-supply unit  140   c , etc. Specifically, the communication unit  110  embedded in the XR device  10   a  may communicate with a mobile terminal  100   b  by wire or wirelessly. 
       FIG. 14  is a conceptual diagram illustrating an exemplary method for implementing an XR device using AR glasses according to an embodiment of the present disclosure. The above-mentioned embodiments may also be implemented in AR glass types shown in  FIG. 14 . 
     Referring to  FIG. 14 , the AR glasses may include a frame, a control unit  200 , and an optical display unit  300 . 
     Although the frame may be formed in a shape of glasses worn on the face of the user  10  as shown in  FIG. 14 , the scope or spirit of the present disclosure is not limited thereto, and it should be noted that the frame may also be formed in a shape of goggles worn in close contact with the face of the user  10 . 
     The frame may include a front frame  110  and first and second side frames. 
     The front frame  110  may include at least one opening, and may extend in a first horizontal direction (i.e., an X-axis direction). The first and second side frames may extend in the second horizontal direction (i.e., a Y-axis direction) perpendicular to the front frame  110 , and may extend in parallel to each other. 
     The control unit  200  may generate an image to be viewed by the user  10  or may generate the resultant image formed by successive images. The control unit  200  may include an image source configured to create and generate images, a plurality of lenses configured to diffuse and converge light generated from the image source, and the like. The images generated by the control unit  200  may be transferred to the optical display unit  300  through a guide lens P 200  disposed between the control unit  200  and the optical display unit  300 . 
     The controller  200  may be fixed to any one of the first and second side frames. For example, the control unit  200  may be fixed to the inside or outside of any one of the side frames, or may be embedded in and integrated with any one of the side frames. 
     The optical display unit  300  may be formed of a translucent material, so that the optical display unit  300  can display images created by the control unit  200  for recognition of the user  10  and can allow the user to view the external environment through the opening. 
     The optical display unit  300  may be inserted into and fixed to the opening contained in the front frame  110 , or may be located at the rear surface (interposed between the opening and the user  10 ) of the opening so that the optical display unit  300  may be fixed to the front frame  110 . For example, the optical display unit  300  may be located at the rear surface of the opening, and may be fixed to the front frame  110  as an example. 
     Referring to the XR device shown in  FIG. 14 , when images are incident upon an incident region S 1  of the optical display unit  300  by the control unit  200 , image light may be transmitted to an emission region S 2  of the optical display unit  300  through the optical display unit  300 , images created by the controller  200  can be displayed for recognition of the user  10 . 
     Accordingly, the user  10  may view the external environment through the opening of the frame  100 , and at the same time may view the images created by the control unit  200 . 
     As described above, although the present disclosure can be applied to all the 5G communication technology, robot technology, autonomous driving technology, and 
     Artificial Intelligence (AI) technology, following figures illustrate various examples of the present disclosure applicable to multimedia devices such as XR devices, digital signage, and TVs for convenience of description. However, it will be understood that other embodiments implemented by those skilled in the art by combining the examples of the following figures with each other by referring to the examples of the previous figures are also within the scope of the present disclosure. 
     Specifically, the multimedia device to be described in the following figures can be implemented as any of devices each having a display function without departing from the scope or spirit of the present disclosure, so that the multimedia device is not limited to the XR device and corresponds to the user equipment (UE) mentioned in  FIGS. 1 to 14  and the multimedia device shown in the following figures can additionally perform 5G communication. 
     Particularly, as a device capable of a projector function of projecting to display an image on a projection body is enough for a multimedia device that will be described with reference to the accompanying drawings, the multimedia device is non-limited by an XR device. 
     An XR device and method of controlling the same according to one embodiment of the present disclosure, which facilitate a user to use two or more control components by changing disposition of the control components depending on a state of a projection plane on which a virtual UI including the control components for the operation control of a communication-connected external device, will be described in detail with reference to  FIGS. 15 to 29  as follows. 
     In some implementations, an XR device  2500  according to the present disclosure may include any device, to which XR technologies and image projecting functions are applied, such as an AR projector, a Head-Mounted Display (HMD), a Head-Up Display (HUD), eyeglass-type AR glasses, a smartphone, a tablet PC, a laptop, a desktop, a TV, a digital signage, etc. 
     The following description will be made on the assumption that the XR device  2500  according to the present disclosure includes an AR projector. 
       FIG. 15  is a diagram showing a case of implementing an XR device of an AR projector type according to one embodiment of the present disclosure. 
       FIG. 16  is a block diagram of an XR device of an AR glass type for controlling an IoT device according to one embodiment of the present disclosure. 
     Referring to  FIG. 15  and  FIG. 16 , an AR projector  2500  of the present disclosure includes a display  2510 , a communication module  2520 , a projection module  2530 , a 3D sensor  2540 , a camera  2550 , a memory  2560 , and a processor  2570 . 
     The display  2510  includes a touchscreen type, and may display informations processed by the AR projector  2500  visually or an environment setting window of the AR projector  2500 . 
     If the communication module  2520  connects communication with at least one external device by wire or wireless by being paired with the at least one external device, it transceives signals with the corresponding external device. 
     Here, according to the present disclosure, the external device may include an Internet-of-Things (IoT) device. If so, the AR projector  2500  may play a role as an IoT hub device configured to control the IoT device. 
     Namely, the AR projector  2500  may receive device information of an IoT device from at least one IoT device that is a control target, create a virtual UI including two or more control components for controlling operations of the IoT device based on the received device information, and project the virtual UI on a projection plane through the projection module  2530 . 
     For example, if the external device is a multimedia device capable of reproducing a multimedia, the virtual UI may include control components for controlling at least one of operations including start of the multimedia, pause, next multimedia output, previous multimedia output, sound volume up/down, broadcast channel up/down, etc. 
     If an IoT application for controlling the at least one IoT device is installed and then executed, the AR projector  2500  connects communication with at least one IoT device registered at the IoT application and displays a list of the connected at least one IoT device. If a specific IoT device is selected from the list, the AR projector  2500  may project a virtual UI, which is to control an operation of the selected specific IoT device among virtual Uls provided by the application, on the projection plane. 
     The AR projector  2500  may receive status information indicating an operational status of the IoT device from the IoT device and project a virtual UI including the received status information. 
     For example, the status information may include at least one of information related to a currently operating function of the IoT device, an amount of power used by the IoT device for a preset period, and information related to an event currently occurring in the IoT device. 
     The AR projector  2500  may receive information, which is currently outputted from the IoT device, from the IoT device and project a virtual UI including the received information. The information may include at least one of a screen image of a specific function, a multimedia image, and a website image. 
     Meanwhile, the above-described communication module  2520  may include at least one of a mobile communication module, a wireless internet module, and a short-range communication module. 
     The mobile communication module transceives wireless signals with at least one of a base station, an IoT device, and a server on a mobile communication network established according to the technology standards or communication systems for mobile communications (e.g., GSM (Global System for Mobile communication), CDMA (Code Division Multi Access), WCDMA (Wideband CDMA), HSDPA (High Speed Downlink Packet Access), LTE (Long Term Evolution), 5G ( 5 th Generation)). The wireless signals may include a voice call signal, a video call signal, and data of various types according to text/multimedia message transceiving. The mobile communication module may perform communication with an IoT device through at least one of mobile communication networks provided by the aforementioned communication systems. 
     The wireless internet mobile refers to a module for a wireless Internet access and may be built in or outside the AR projector  2500 . The wireless internet module is configured to transceive wireless signals on communication networks according to the wireless Internet technologies. 
     The wireless internet technologies include, for example, WLAN (Wireless LAN), WiFi (Wireless Fidelity) Direct, DLNA (Digital Living Network Alliance), Wibro (Wireless broadband), Wimax (World Interoperability for Microwave Access), HSDPA (High Speed Downlink Packet Access), LTE (Long Term Evolution), etc. The wireless internet module  113  transceives data according to at least one wireless internet technology in a range including internet technologies failing to be listed in the above description. 
     From the perspective that a wireless internet access by Wibro, HSDPA, GSM, CDMA, WCDMA, LTE, or the like is achieved through a mobile communication network, the wireless internet module performing the wireless internet access through the mobile communication network may be understood as a sort of the mobile communication module. The wireless internet module may perform communication with an IoT device through at least one of the communication networks provided by the aforementioned wireless internet technologies. 
     The short range communication module is provided for short range communication and may support short range communication using at least one of Bluetooth, RFID (Radio Frequency Identification), Infrared Data Association (IrDA), UWB (Ultra Wideband), ZigBee, NFC (Near Field Communication), Wi-Fi (Wireless-Fidelity), Wi-Fi Direct, etc. The short range communication module may perform communication with an IoT device through at least one of the communication networks provided by the aforementioned communication technologies. 
     The projection module  2530  projects a virtual UI, which includes the aforementioned control components, on a projection plane using light of a light source. 
     The 3D sensor  2540  is a sensor configured to scan a space of a projection plane on which the virtual UI is projected and sense a state of the projection plane, and may sense at least one state of a presence or non-presence of at least one object in a projection angle projected on the projection plane, a distance to the projection plane, a flat degree of the projection plane, and a curved extent of the projection plane. 
     The camera  2550  captures an image including a user&#39;s touch action on the control components within the virtual UI projected on the projection plane. 
     The memory  2560  is capable of a program related to an operation of the AR projector  2500 , at least one application, an operating system, and various data such as user&#39;s personal data and the like, and may store virtual Uls for controlling operations of IoT devices according to the present disclosure. 
     The processor  2570   2570  controls overall operations of the AR projector  2500  according to the present disclosure. A process for changing dispositions of control components according to a state of a projection plane, on which a virtual UI including the control components for the operation control of an IoT device is projected, is described in detail with reference to  FIGS. 17 to 29  as follows. 
       FIG. 17  is a flowchart of a projection control process of a virtual UI of an AR projector according to one embodiment of the present disclosure. 
     Referring to  FIG. 17 , the processor  2570  connects communication with at least one IoT device through the communication module  2520  [S 2610 ], and projects a virtual UI configured with control components for the operation control of the IoT device on a projection plane through the projection module  2530  [S 2620 ]. 
     The processor  2570  captures an image containing a user&#39;s touch action on the control components projected on the projection plane through the camera  2550  [S 2630 ], and then controls the IoT device to perform an operation related to the control component touched by the user [S 2640 ]. 
     Subsequently, the processor  2570  senses a state of the projection plane on which the virtual UI is projected through the 3D sensor  2540 , and then changes the disposition of the control components based on the sensed state of the projection plane [S 2650 ]. 
     Namely, the processor  2570  senses at least one state of a presence or non-presence of at least one object in a projection angle projected on the projection plane, a distance to the projection plane, a flat degree of the projection plane, and a curved extent of the projection plane through the 3D sensor  2540 , and may change the disposition of the control components based on the sensing result. 
     In some implementations, the step S 2650  may be performed after the step S 2620  as well. 
     Hereinafter, a process for changing the disposition of the control components based on the sensed state of the projection plane is described in detail with reference to  FIGS. 18 to 29 . 
       FIG. 18  is a diagram to describe a process for projecting a virtual UI according to one embodiment of the present disclosure. 
     Referring to  FIG. 18 , if communication with an IoT device  2410  is connected [ FIG. 18 ( a ) ], the processor  2570  may project a virtual UI  2700  including control components  2710 ,  2720  and  2730  for the operation control of the IoT device  2410  on a projection plane  2700 P through the projection module  2530  [ FIG. 18 ( b ) ]. 
     In doing so, as shown in  FIG. 18 ( a ) , if an input of a preset motion gesture is detected from a user based on an image received through the camera  2550 , the processor  2570  may control the virtual UI  2700  to be projected. 
     For example,  FIG. 18  shows that the IoT device  2410  is a TV, and that a first control component  2710  for the sound volume up/down control, a second control component  2720  for the power on/off control of the TV  2410 , and a third control component  2730  for the broadcast channel switching are included in the virtual UI  2700 . Of course, the types of the first to third control components  2710 ,  2720  and  2730  are just exemplary. And, all the control components corresponding to keys provided to a remote controller for the control of the TV may be included in the virtual UI  2700 . 
       FIG. 19  is a diagram to describe a process for projecting control components within a virtual UI in a manner of avoiding an object according to one embodiment of the present disclosure. 
     Referring to  FIG. 19 , the processor  2570  scans a position, on which a virtual UI for the operation control of the IoT device  2410  will be projected, within a projection plane  2700 P through the 3D sensor  2540 . As a result of the scan, if it is sensed that an object  2800  other than a user&#39;s hand exists at the position on which the virtual UI will be projected, the processor  2570  may change the disposition of control components  2710 ,  2720  and  2730  within the virtual UI so as to enable the control components  2710 ,  2720  and  2730  to be projected in a manner of avoiding the object  2800 . 
     For example,  FIG. 19  shows that the first control component  2710  among the control components  2710 ,  2720  and  2730  is separated and disposed in a manner of avoiding the object  2800 . 
     In addition, if the object exists at the position on which the virtual UI will be projected, the processor  2570  may determine whether the control components  2710 ,  2720  and  2730  are projective entirely or in part, and then project the control components  2710 ,  2720  and  2730  on the object entirely or in part according to a result of the determination. 
     Namely, based on the sensing result of the projection plane  2700 P of the 3D sensor  2540 , if it is determined that a surface of the object  2800  is not flat within a preset reference, the processor  2570  may control the control component  2710  among the control components  2710 ,  2720  and  2730  to be separated and projected by avoiding the object  2800 . 
     On the contrary, based on the sensing result of the projection plane  2700 P of the 3D sensor  2540 , if it is determined that a surface of the object  2800  is flat within a preset reference, the processor  2570  may control the control components  2710 ,  2720  and  2730  to projected on the object  2800  entirely or in part. 
     The processor  2570  measures a surface reflectance off the object through the 3D sensor  2540  (or s surface reflection measurement sensor provided to an AR projector). As the measured surface reflectance of the object is lower than a preset reference value, if a material of the object is sensed as a transparent material such as glass or plastic, the control components  2710 ,  2720  and  2730  can pass through the object. Hence, the processor  2570  may change the disposition of the control components so that the control components can be projected entirely or in part by avoiding the object. 
       FIG. 20  is a diagram to describe a process for projecting some of control components within a virtual UI on an object according to one embodiment of the present disclosure. 
     Referring to  FIG. 20 , the processor  2570  scans a position, on which a virtual UI for the operation control of the IoT device  2410  will be projected, within a projection plane  2700 P through the 3D sensor  2540 . As a result of the scan, if it is sensed that an object  2900  other than a user&#39;s hand exists at the position on which the virtual UI will be projected, the processor  2570  determines whether a surface of the object  2900  is flat within a range of a preset reference through the 3D sensor  2540 . 
     If it is determined that the surface of the object  2900  is flat within a range of the preset reference through the 3D sensor  2540 , the processor  2570  controls the control components  2710 ,  2720  and  2730  to be projected and displayed on the object  2900  entirely or in part. 
     In doing so, when the object  2900  is an object with prescribed thickness, if some  2710  of the control components  2710 ,  2720  and  2730  is projected on the object  2900 , there may be a height difference between the control component  2710  and the rest of the control components  2720  and  2730 , whereby the control components  2710 ,  2720  and  2730  may be viewed distortedly. 
     Therefore, the processor  2570  may control the control component  2710 , which overlaps with the object  2900 , among the control components  2710 ,  2720  and  2730  to be projected on the object  2710  by being separated from the rest of the control components  2720  and  2730 . 
       FIG. 21  is a diagram showing a process for projecting some of control components within a virtual UI in a manner of avoiding a dangerous object according to one embodiment of the present disclosure. 
     Referring to  FIG. 21 , the processor  2570  scans a position, on which a virtual UI for the operation control of the IoT device  2410  will be projected, within a projection plane  2700 P through the 3D sensor  2540 . As a result of the scan, if it is sensed that an object  2420  other than a user&#39;s hand exists at the position on which the virtual UI will be projected, the processor  2570  determines whether the object  2420  is a dangerous object. 
     For one example, the processor  2570  recognizes the object  2420  in the image captured by the camera  2550 . If the recognized object  2420  corresponds to a preset dangerous object, the processor  2570  may regard the object  2420  as a dangerous object. 
     For another example, when the object  2420  is an IoT device, if an operational status of the IoT device satisfies a preset condition based on the IoT device&#39;s operational status information received from the IoT device, the processor  2570  may regard the IoT device as a dangerous object. 
     For example, when the IoT device is an IoT coffee port, if water temperature information of the IoT coffee port  2420  received through the communication module  2520  belongs to a preset temperature range (e.g., a water temperature range enough to scald a user), the processor  2570  may regard the IoT coffee port  2420  as a dangerous object. 
     As described above, if the object  2420  is determined as a dangerous object, the processor  2570  may change disposition of the control components  2710 ,  2720  and  2730  so that the control components  2710 ,  2720  and  2730  within the virtual UI can be projected by avoiding the object  2420 . 
     For example,  FIG. 21  shows that the first control component  2710 , of which position overlaps with the object  2420 , among the control components  2710 ,  2720  and  2730  is separated and disposed by avoiding the object  2800 . 
       FIG. 22  is a diagram to describe a process for enlarging and projecting some of control components within a virtual UI according to one embodiment of the present disclosure. 
     Referring to  FIG. 22 , the processor  2570  sense 4 s a distance to a projection plane  2700 P through the 3D sensor  2540 , and may adjust a projection size of some  2710  of the control components  2710 ,  2720  and  2730  based on the sensed distance. 
     Namely, the projection plane  2700 P may include a first region on which the control component  2710  among the control components  2710 ,  2720  and  2730  is projected and a second region on which the second and third control components  2720  and  2730  are projected. 
     In this case, if determining that there is a distance difference between the first and second regions based on the sensing result of the 3D sensor  2540 , the processor  2570  may adjust a projection size of the first control component  2710  projected on the first region and or projection sizes of the second and third control components  2720  and  2730  differently based on the distance difference. 
     For example, as shown in  FIG. 22 ( a ) , the projection plane  2700 P may include a first region and a second region. in this case, an object  3100  on which the first control component  2710  among the control components  2710 ,  2720  and  2730  can be projected is put in the first region. And, the second and third control components  2720  and  2730  are projected on the second region while any object is not put in the second region. 
     Here, a size of the first control component  2710  projected on the object  3100  in the first region becomes smaller than a size of each of the second and third control components  2720  and  2730  projected on the second region having no object put therein due to a height of the object  3100 . 
     Therefore, as shown in  FIG. 22 ( b ) , according to the distance difference between the first and second regions due to the height of the object  3100 , the processor  2570  may project the first control component  2710  on the object  3100  in the first region in a manner of enlarging a size of the first control component  2710  to be larger than the second and third control components  2720  and  2730  projected on the second region. 
     Namely, as if the control components  2710 ,  2720  and  2730  are projected on a plane (i.e., a flat surface), the processor  2570  corrects a size and position of the first control component  2710  by the distance difference generated due to the height of the object  3100 . 
       FIG. 23  is a diagram to describe a process for displaying a virtual UI on an external device having a screen according to one embodiment of the present disclosure. 
     Referring to  FIG. 23 ( a ) , the processor  2570  scans a position, on which a virtual UI  2700  for the operation control of the IoT device  2410  will be projected, within a projection plane  2700 P through the 3D sensor  2540 . As a result of the scan, if it is sensed that an object  2430  other than a user&#39;s hand exists at the position on which the virtual UI will be projected, the processor  2570  may change the disposition of control components  2710 ,  2720  and  2730  within the virtual UI so that the control components  2710 ,  2720  and  2730  can be projected by avoiding the object  2430 . 
     For example,  FIG. 23 ( a )  shows that the first control component  2710  among the control components  2710 ,  2720  and  2730  is separated and disposed in a manner of avoiding the object  2800 . 
     In this case, when communication is connected between the object  2430  and the AR projector  2500 , if the object  2430  is an external device  2430  having a screen  2431 , as shown in  FIG. 23 ( b ) , the processor  2570  may control the virtual UI  2700  including the control components  2710 ,  2720  and  2730  to be displayed on the screen  2431  of the external device  2430 . 
     Specifically, when the external device  2430  having the screen  2431  is recognized through the camera  2550 , if a first motion of a user gripping the external device  2430  is sensed, the processor  2570  may control the projection module  2530  to stop a projection operation of the virtual UI  2700  and control the external device  2430  to display the virtual UI  2700  on the screen  2431  [ FIG. 23 ( b ) ]. 
     In doing so, the processor  2570  provides graphic data corresponding to the virtual UI  2700  to the external device  2430  through the communication module  2520 , thereby controlling the external device  2430  to display the virtual UI  2700  on the screen  2431 . 
     In some implementations, the first motion may include a motion that the user grips the external device  2430  and then lifts it up from the projection plane  2700 P. 
     In order to display information indicating an operational status of the IoT device  2410  on the external device  2430  as well as the graphic data corresponding to the virtual UI  2700 , the processor  2570  may transmit graphic data corresponding to the operational status information to the external device  2430  as well. For example, the operational status information may include at least one of information related to a currently operating function of the IoT device  2410 , an amount of power used by the IoT device  2410  for a preset period, and information related to an event currently occurring in the IoT device  2410 . 
     The processor  2570  may receive information, which is currently outputted from the IoT device  2410 , from the IoT device  2410  and transmit graphic data corresponding to the received information to the external device  2430  as well as the graphic data corresponding to the virtual UI  2700  and the graphic data corresponding to the operational status information. 
     If sensing a second motion of the user gripping the external device  2430  through the camera  2550 , the processor  2570  may control the external device  2430  to stop displaying the virtual UI  2700  displayed on the screen  2431  and control the projection module  2530  to project the virtual UI  2700  on the projection plane  2700 P again. 
     Specifically, if sensing that the motion of the user griping the external device  2430  is changed into the second motion from the first motion through the camera  2550 , the processor  2570  may control the external device  2430  to stop displaying the virtual UI  2700  displayed on the screen  2431  and control the projection module  2530  to project the virtual UI  2700  on the projection plane  2700 P again. 
     Here, the second motion may include a motion of switching a state that the external device  2430  is lifted up from the projection plane P by the user to a state that the external device  2430  is put down on the projection plane  2700 P again. 
     In this case, if the external device  2430  is put at a specific position of the projection plane  2700 P, the processor  2570  may control the control components  2710 ,  2720  and  2730  of the virtual UI  2700  to be disposed by avoiding the external device  2430 . 
       FIG. 24  is a diagram to describe a process for projecting a virtual UI to control a non-screen external device located in a projection plane according to one embodiment of the present disclosure. 
     Referring to  FIG. 24 , the processor  2570  recognizes an object  2440  put on a projection plane  2700 P and may control a virtual UI  3300  related to the recognized object  2440  to be projected on the projection plane. 
     Here, the object  2440  may include a non-screen external device  2440  communication-connectible with the AR projector  2500 . For example, the external device  2440  having no screen may include a wireless speaker, an air cleaner, a humidifier, etc. 
     If recognizing the non-screen external device  2440  through the camera  2550 , the processor  2570  searches the memory  2560  for the virtual UI  3300  of the recognized external device  2440  and may project the found virtual UI  3300  on the projection plane  2700 P. 
     Here, the virtual UI  3300  of the external device  2440  may include at least one of two or more control components  3310 ,  3320  and  3330  for the operation control of the external device  2440 , operational status information of the external device  2440 , and information related to sound currently outputted from the external device  2440 . The operational status information may include at least one of information related to a currently operating function of the external device  2440 , an amount of power used by the external device  2440  for a preset period, and information related to an event currently occurring in the external device  2440 . 
       FIG. 25  is a diagram to describe a process for linking a virtual UI to an object according to one embodiment of the present disclosure. 
     Referring to  FIG. 25 ( a ) , while a virtual UI  3400  of an IoT device  2410  is projected by avoiding an object  2450  put in a projection plane  2700 P, if a user&#39;s motion gesture that the virtual UI  3400  is moved to the object  2450  is recognized through the camera  2550 , the processor  2570  saves an image of the recognized object  2450  to the memory  2560  in a manner of mapping the image and the virtual UI  3400  to each other. 
     Here, the virtual UI  3400  may include two or more control components for the operation control of the IoT device  2410 , operational status information of the IoT device  2410 , and a content currently outputted from the IoT device  2410 . The operational status information may include information related to a currently operating function of the IoT device  2410 , an amount of power used by the IoT device  2410  for a preset period, and information related to an event currently occurring in the IoT device  2410 . And, the content may include at least one of information, video, music, and text outputted from the IoT device  2410 . 
     Thereafter, referring to  FIG. 25 ( b ) , if recognizing the object  2450  again through the camera  2550 , the processor  2570  projects the virtual UI  3400  mapped to the image of the recognized object  2450  in the memory  2560  to the projection plane again. 
     Namely, after the user has moved the currently projected virtual UI  3400  to the object  2450 , if the object  2450  is recognized again through the camera  2550 , the AR projector  2500  projects the virtual UI  3400  on the object  2450 , thereby providing it to the user. 
       FIG. 26  is a diagram to describe a process for changing a projection angle of a virtual UI depending on a user&#39;s location according to one embodiment of the present disclosure. 
     Referring to  FIG. 26 ( a ) , an AR projector  2500  is projecting a virtual UI in a forward direction to a projection plane  3500 . And, a user is located not in the forward direction to the projection plane  3500  but on one side of the AR projector  2500 . 
     In this case, when the user looks at the virtual UI projected on the projection plane  3500 , there is a problem that the virtual UI looks distortedly due to the user&#39;s location toward the projection plane  3500 . 
     Therefore, as shown in  FIG. 26 ( b ) , if recognizing the user while projecting the virtual UI on the projection plane  3500 , the processor  2570  obtains a location of the recognized user and may change a projection angle of the virtual UI so that the virtual UI projected on the projection plane  3500  can be viewed in a forward direction from the user&#39;s location. Here, the camera  2550  may include a military-wave camera capable of user&#39;s location recognition. 
       FIG. 27  is a diagram to describe a process for projecting a virtual UO on a material of a curved projection plane according to one embodiment of the present disclosure. 
     Referring to  FIG. 27 ( a ) , before a virtual UI  3610  is projected on a projection plane  3600 , the processor  2570  senses depth information on a surface of the projection plane  3600  through the 3D sensor  2540  and analyzes a curved state of the surface of the projection plane  3600  based on the sensed depth information. 
     Based on the analyzed curved state, if the surface of the projection plane  3600  is determined as curved more than a preset reference, as shown in  FIG. 27 ( b ) , the processor  2570  projects the virtual UI  3610  in a manner of correcting the virtual UI  3610  so as not to be distorted by the curved surface of the projection plane  3600 . 
     For example, as shown in  FIG. 27 ( a ) , if the virtual UI  3610  is projected on the projection plane  3610  having a rounded surface, the virtual UI  3610  is distorted in a manner of being stretched horizontally due to the rounded surface. 
     Therefore, referring to  FIG. 27 ( b ) , although the projection plane  3610  has the rounded surface, the processor  2570  corrects the shape of the virtual UI  3610  so as to be viewed without distortion. 
       FIG. 28  is a diagram to describe a process for changing a projection position of a virtual UI depending on a material of a projection plane according to one embodiment of the present disclosure. 
     Referring to  FIG. 28 , before projecting a virtual UI  3710  on a projection plane  3700 , the processor  2570  measures a surface reflectance of a whole region of the projection plane  3700  through the 3D sensor  2540  (or a surface reflection measurement sensor provided to an AR projector). 
     As a result of the measurement of the surface reflectance, if a surface reflectance of a first region  3700 A of the projection plane  3700  corresponds to a transparent material lower than a preset reference and a surface reflectance of a second region  3700 B of the projection plane  3700  corresponds to a non-transparent material lower than the preset reference, the processor  2570  controls the virtual UI  3710  to be projected on the second region  3700 B of the non-transparent material by avoiding the first region  3700 A of the transparent material. 
     Finally,  FIG. 29  is a diagram to describe a process for changing a display style of a virtual UI depending on a material color of a projection plane according to one embodiment of the present disclosure. 
     Referring to  FIG. 29 , before projecting a virtual UI  3810  on a projection plane  3800 , the processor  2570  senses a material color of the projection plane  3800  through the camera  2550  and may change a display style of the virtual UI  3810  based on the sensed material color of the projection plane  3800 . 
     For one example, the processor  2570  changes a color of the virtual UI  3810  into a color contrary to the sensed material color of the projection plane  3800 , thereby enabling the virtual UI  3810  to be seen well in the projection plane  3810 . 
     For another example, the processor  2570  changes a color of the virtual UI  3810  into a color matching with the sensed material color of the projection plane  3800 , thereby enabling the virtual UI  3810  to be seen in harmony with the projection plane  3810 . 
     According to one of various embodiments of the present disclosure, depending on a state of a projection plane on which a virtual UI including two or more control components for the operation control of a communication-connected external device is projected, the disposition of the control components is changed, whereby a user may conveniently use the control components. 
     According to another one of various embodiments of the present disclosure, when an object exists at a location on which the virtual UI will be projected in a projection plane, the control components are projected in a manner of avoiding the object, whereby a user may conveniently use the control components without removing the object from the projection plane. 
     Although the present specification has been described with reference to the accompanying drawing, it will be apparent to those skilled in the art that the present specification can be embodied in other specific forms without departing from the spirit and essential characteristics of the specification. The scope of the specification should be determined by reasonable interpretation of the appended claims and all change which comes within the equivalent scope of the specification are included in the scope of the specification.