Robot and travelling method enabling robot to move to exit in disaster situation

Abstract

A robot traveling in a space is disclosed. Instructions stored in the robot, when executed individually or collectively by at least one processor of the robot, may cause the robot to: when it is identified that a disaster situation has occurred in a space, identify, on the basis of map data, a path for the robot to move from a location of the robot to an exit of the space while passing through a plurality of landmarks installed in the space; acquire, on the basis of the map data, information about a direction and a moving distance of the robot to enable the robot to move along the path; and move along the path on the basis of the acquired direction, the acquired moving distance, and a direction and a moving distance of the robot detected through a sensor.

Description

Robot and driving method for robots to move to the exit in disaster situations

[0001] The present disclosure relates to a robot that travels in space and a method of driving the robot.

[0002] In addition to simple repetitive functions, robots can detect their surroundings in real time based on sensors, cameras, and other equipment, collect information, and drive autonomously. Such robots are currently being used in many fields.

[0003] For example, autonomous mobile robots (AMRs) are being utilized in various industries because they can increase efficiency and productivity.

[0004] A robot traveling through a space according to one embodiment may include a driving unit, a sensor for measuring the distance traveled by the robot, a memory for storing instructions, and at least one processor including a processing circuit. When the instructions are executed individually or collectively by the at least one processor, if the robot is identified as having a disaster situation in the space, the robot may identify a path for the robot to travel from the robot's location to the exit of the space by passing through a plurality of landmarks installed in the space based on map data stored in the memory. When the instructions are executed individually or collectively by the at least one processor, the robot may obtain information regarding the robot's direction and distance traveled for the robot to travel along the path based on the map data. When the instructions are executed individually or collectively by the at least one processor, the robot may control the driving unit to move the robot along the path based on the obtained direction, the obtained distance traveled, and the robot's direction and distance traveled detected through the sensor.

[0005] The above map data may include information regarding the location and shape of a plurality of landmarks in the space, a path for the robot to move to an exit while passing at least one landmark for each location in the space, and the direction and distance of the robot to move along the path.

[0006] When the above instructions are executed individually or collectively by the at least one processor, the robot may be controlled to move to the landmark closest to the robot's position among a plurality of landmarks based on the acquired direction and distance traveled, and to move sequentially along the landmarks on the path from the landmark to which the robot moved.

[0007] The sensor may include an inertial sensor and an encoder. When the instructions are executed individually or collectively by the at least one processor, the robot may move in the acquired direction based on the inertial sensor and move by the acquired distance based on the encoder.

[0008] When the above instructions are executed individually or collectively by the at least one processor, if it is identified that the robot cannot use the LiDAR sensor and camera of the robot in the disaster situation, the robot may be made to identify the path and move to the exit.

[0009] When the above instructions are executed individually or collectively by the at least one processor, if the robot is identified as having detected an obstacle while moving along the path, it may be made to move along the path to the exit while avoiding the obstacle.

[0010] When the above instructions are executed individually or collectively by the at least one processor, the robot may be made to move to the exit along the path after deviating from the path and returning to the path to avoid the obstacle when the obstacle is detected.

[0011] A driving method for a robot to move to an exit in a disaster situation according to one embodiment may include, when it is identified that the disaster situation has occurred in the space, an operation of identifying a path for the robot to move from the robot's location to the exit of the space by passing through a plurality of landmarks installed in the space based on map data. The driving method may include an operation of obtaining information regarding the direction and distance traveled of the robot to move along the path based on the map data. The driving method may include an operation for the robot to move along the path based on the obtained direction, the obtained distance traveled, and the direction and distance traveled of the robot detected through the robot's sensors.

[0012] In a non-transient computer-readable medium storing computer instructions that cause a robot to perform an operation when executed by at least one processor of a robot according to one embodiment, the operation may include, when the disaster situation is identified as having occurred in the space, identifying a path for the robot to move from the robot's location to the exit of the space by passing through a plurality of landmarks installed in the space based on map data. The operation may include, based on the map data, obtaining information regarding the direction and distance of the robot to move along the path. The operation may include, based on the obtained direction, the obtained distance, and the direction and distance of the robot detected through the robot's sensors, moving the robot along the path.

[0013] FIG. 1 shows an example of a robot according to one embodiment.

[0014] FIG. 2 shows an example of a block diagram of a robot according to one embodiment.

[0015] FIG. 3 shows an example of a block diagram of a robot according to one embodiment.

[0016] FIG. 4 is a diagram illustrating the operation of a robot moving to an exit according to one embodiment.

[0017] FIG. 5 shows an example of a path stored in map data and information for moving the path according to one embodiment.

[0018] FIG. 6 illustrates an example of a method in which a robot moves to an exit in a disaster situation using a path stored in map data and information for moving the path, according to one embodiment.

[0019] FIG. 7 is a diagram illustrating the movement of a robot avoiding obstacles according to one embodiment.

[0020] FIG. 8 shows an example of a robot performing avoidance driving according to one embodiment.

[0021] FIG. 9 is a diagram illustrating the operation of a robot moving to an exit according to one embodiment.

[0022] The present disclosure will be described in detail below with reference to the attached drawings.

[0023] The various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, phrases such as "A or B," "at least one of A and B," "at least one of A or B," "A, B or C," "at least one of A, B and C," and "at least one of A, B, or C" may each include any one of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used simply to distinguish said components from other said components and do not limit said components in any other aspect (e.g., importance or order). Where any (e.g., 1st) component is referred to as "coupled" or "connected" to another (e.g., 2nd) component, with or without the terms "functionally" or "communicationly," it means that said any component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component.

[0024] Throughout the specification, singular expressions include plural expressions unless the context clearly indicates otherwise. Wherever a part of the specification states that it "includes" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0025] The term “module” as used in the various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0026] FIG. 1 shows an example of a robot according to one embodiment.

[0027] Referring to FIG. 1, the robot (100) may be an autonomous mobile robot (AMR). The robot (100) can explore its surroundings to perceive the surrounding environment, and based on the perceived information, it can move autonomously within the space and perform tasks. For example, the robot (100) can transport goods in a warehouse, transport parts and materials in a factory, transport medicines, medical tools, and waste in a hospital, transport items in a hotel, or transport luggage at an airport.

[0028] In one embodiment, when the robot (100) identifies that a disaster situation has occurred in the space, it can move to an exit using a plurality of landmarks installed in the space.

[0029] The landmark may be a structure installed in space to plan a path for the robot (100) to move to an exit in the event of a disaster and to move along the path.

[0030] A disaster situation may include a situation in which a fire occurs in the space where the robot (100) is located. When a fire occurs, the use of the robot (100)’s LiDAR sensor or camera may be impossible due to smoke from the fire. In the present disclosure, so that the robot (100) can move to the exit even in such a situation, the robot (100) identifies a path to move to the exit by passing at least one landmark from its current location and moves to the exit by driving along the path based on odometry. Accordingly, the robot (100) can safely evacuate to the exit even in a disaster situation such as a fire, thereby preventing the explosion of the robot (100)’s battery due to the fire.

[0031] FIG. 2 shows an example of a block diagram of a robot according to one embodiment.

[0032] Referring to FIG. 2, the robot (100) may include at least one sensor (110) (hereinafter referred to as sensor (110)), a driving unit (120), at least one memory (130) (hereinafter referred to as memory (130)), and at least one processor (140) (hereinafter referred to as processor (140)).

[0033] The sensor (110) can generate electrical information that can be processed by the processor (140) and / or memory (130) from non-electronic information related to the robot (100). The sensor (110) can detect the operating state of the robot (100) or the external environmental state and generate electrical information corresponding to the state.

[0034] For example, the sensor (110) may include an inertial measurement unit (IMU) sensor. The inertial sensor may include at least one of a gyroscope, an accelerometer, and a magnetometer. The processor (140) can obtain the orientation angle (e.g., rotation direction and / or rotation angle), position change, and velocity of the robot (100) using data detected by the inertial sensor.

[0035] For example, the sensor (110) may include an encoder. The encoder can measure the number of rotations of a motor or wheel. The processor (140) can obtain the travel distance of the robot (100) using the data detected by the encoder.

[0036] The driving unit (120) can control the movement of the robot (100). For example, the driving unit (120) can move the robot (100), stop the robot (100) while it is moving, and control the movement speed and / or direction of movement of the robot (100).

[0037] For example, the driving type of the robot (100) can be a wheel type or a walking type.

[0038] The wheel type refers to the method by which the robot (100) moves through the rotation of a wheel. If the robot (100) is a wheel-type robot, the robot (100) may include one or more wheels. The driving unit (120) may include a device that generates power to rotate the wheel. For example, the driving unit (120) may be implemented as a gasoline engine, a diesel engine, an LPG (liquefied petroleum gas) engine, or an electric motor, depending on the fuel (or energy source) used. For example, the driving unit (120) can control the direction of movement and the speed of movement of the robot (100) by controlling the rotation direction and rotation speed of one or more wheels.

[0039] A walking type refers to the method by which a robot (100) moves through the movement of its legs. If the robot (100) is of a walking type (e.g., a bipedal robot, a tripedal robot, a quadrupedal robot, etc.), the robot (100) may include two or more legs that support the robot (100). The legs may include a plurality of links and joints connected to the links. The driving unit (120) may include a device that generates power to lift or lower the legs by rotating the links around the joints. For example, the driving unit (120) may be implemented by a motor and / or actuator, etc.

[0040] Memory (130) may store data necessary for the robot (100) to operate according to various embodiments of the present disclosure. Memory (130) may include one or more storage media (or one or more storage devices). For example, memory (130) may include a memory assembly comprising one or more storage media. For example, the one or more storage media may include a hard drive, a flash memory, a permanent memory such as ROM (read-only memory) (e.g., non-volatile memory), a semi-permanent memory such as RAM (random access memory) (e.g., volatile memory), any other suitable type of storage (or storage assembly), or any combination thereof. The memory (130) may include a cache memory, which is one or more different types of memory used to temporarily store data for a function or feature of the robot (100). As an example, the cache memory may be included within the processor (140). The memory (130) may be fixedly embedded in the robot (100) or incorporated into one or more suitable types of components (e.g., a SIM (subscriber identity module) card and / or an SD (secure digital) card) that can be repeatedly inserted into the robot (100) and removed from the electronic device (500).

[0041] Instructions may be stored in the memory (130). The processor (140) may perform the operation of the robot (100) according to various embodiments of the present disclosure by executing the instructions stored in the memory (130) individually or collectively. Additionally, programs and data for driving the robot (100) may be stored in the memory (130). For example, the memory (130) may store one or more software applications, such as operating system (or system) software applications, firmware software applications, driver software applications, plugin (e.g., add-in, add-on, and / or applet) software applications, and / or any other suitable software applications. For example, the one or more software applications may include instructions executable by the processor (140). For example, memory (130) can store instructions that can be called by an API (application programming interface). For example, memory (130) can store instructions within a library.

[0042] The processor (140) can control the overall operations of the robot (100). For example, the processor (140) can cause other components of the electronic device (100) to perform various operations by executing instructions stored in memory (130). For example, the processor (140) can control the operations of the robot (100) by operatively connecting the sensor (110), the driving unit (120), the memory (130), and the processor (140). Additionally, the processor (140) can control the operations of the robot (100) according to the present disclosure by executing one or more instructions stored in memory (130). The processor (140) may be composed of one or more processors.

[0043] The processor (140) may be implemented as one or more IC (integrated circuit (or circuitry)) chips and may perform various data processing operations. The processor (140) may include at least one electrical circuit and may process instructions (or programs, data, etc.) stored in memory (130) individually or collectively. The processor (140) may include a processor assembly comprising one or more processing circuits. The processor (140) may include any processing circuit that is operative to control the performance and operations of one or more components of the robot (100) (e.g., sensor (110), driving unit (120), and memory (130)). For example, the processor (140) (e.g., application processor (AP)) may be implemented as a system on chip (SoC) (e.g., a single chip or chipset). For example, the processor (140) may be implemented with a number of cores (or at least one core circuit), a number of chips, or a number of chipsets. For example, the processor (140) may include one or more processing circuits. For example, the processor (140) may include one or more processing circuits configured to perform the various functions of the present disclosure individually and / or collectively. As an example without limitation, at least a portion of the processor (140) may be included in a first chip of the robot (100), and at least another portion of the processor (140) may be included in a second chip of the robot (100) different from the first chip of the robot (100).

[0044] The processor (140) may include one or more of a CPU (Central Processing Unit), GPU (Graphics Processing Unit), APU (Accelerated Processing Unit), MIC (Many Integrated Core), DSP (Digital Signal Processor), NPU (Neural Processing Unit), hardware accelerator, or machine learning accelerator. The processor (140) may control one or any combination of other components of the robot (100) and may perform operations or data processing related to communication. The processor (140) may execute one or more programs or instructions stored in memory (130). For example, the processor (140) may perform a method according to one embodiment of the present disclosure by executing one or more instructions stored in memory (130).

[0045] When a method according to one embodiment of the present disclosure includes a plurality of operations, the plurality of operations may be performed by a single processor or by a plurality of processors. For example, when a first operation, a second operation, and a third operation are performed by a method according to one embodiment, the first operation, the second operation, and the third operation may all be performed by a first processor, or the first operation and the second operation may be performed by a first processor (e.g., a general-purpose processor) and the third operation may be performed by a second processor (e.g., an artificial intelligence dedicated processor).

[0046] The processor (140) may be implemented as a single-core processor including one core, or as one or more multicore processors including multiple cores (e.g., homogeneous multicore or heterogeneous multicore). When the processor (140) is implemented as a multicore processor, each of the multiple cores included in the multicore processor may include internal processor memory such as cache memory or on-chip memory, and a common cache shared by the multiple cores may be included in the multicore processor. Additionally, each of the multiple cores included in the multicore processor (or some of the multiple cores) may independently read and execute program instructions for implementing a method according to one embodiment of the present disclosure, or all (or some) of the multiple cores may be linked together to read and execute program instructions for implementing a method according to one embodiment of the present disclosure.

[0047] When a method according to one embodiment of the present disclosure includes a plurality of operations, the plurality of operations may be performed by one of the plurality of cores included in a multi-core processor, or may be performed by a plurality of cores. For example, when a first operation, a second operation, and a third operation are performed by a method according to one embodiment, the first operation, the second operation, and the third operation may all be performed by a first core included in a multi-core processor, or the first operation and the second operation may be performed by a first core included in a multi-core processor and the third operation may be performed by a second core included in a multi-core processor.

[0048] In the embodiments of the present disclosure, the processor may mean a system-on-chip (SoC) in which a processor and other electronic components are integrated, a single-core processor, a multi-core processor, or a core included in a single-core processor or a multi-core processor, wherein the core may be implemented as a CPU, GPU, APU, MIC, DSP, NPU, hardware accelerator, or machine learning accelerator, but the embodiments of the present disclosure are not limited thereto.

[0049] FIG. 3 shows an example of a block diagram of a robot according to one embodiment.

[0050] Referring to FIG. 3, the robot (100) may include a sensor (110), a driving unit (120), a memory (130), a processor (140), a communication interface (150), an input interface (160), an output interface (170), and a microphone (180). However, such configurations are exemplary, and it is understood that new configurations may be added or some configurations omitted in addition to such configurations when implementing the present disclosure. Meanwhile, detailed descriptions of configurations shown in FIG. 3 that overlap with configurations shown in FIG. 2 will be omitted.

[0051] The sensor (110) can detect the structure or objects of the space. Information obtained from the sensor (110) can be used to generate a map of the space. Objects may include various types of objects or obstacles around the robot (100).

[0052] As described in FIG. 2, the sensor (110) may include an inertial sensor (111) and an encoder (112). Additionally, the sensor (110) may include at least one of a camera (113), a LiDAR sensor (114), an obstacle detection sensor (115), and a driving detection sensor (116).

[0053] The camera (113) can capture images of the surroundings of the robot (100) (e.g., the front of the robot (100)). For example, the camera (113) may include an RGB camera, a depth camera, etc. The depth camera may be implemented in a stereo format or a Time of Flight (TOF) format, etc. The camera (113) can provide the acquired images to the processor (140).

[0054] The lidar sensor (114) emits a laser in a 360-degree direction, and when a laser reflected from an object is received, it can obtain geometry information about the space by analyzing the time difference for the laser to be reflected back from the object and the signal strength of the received laser. The geometry information may include the location, distance, direction, etc. of objects around the robot (100). The lidar sensor (114) can provide the detected information to the processor (140).

[0055] The obstacle detection sensor (115) can detect objects around the robot (100). For example, the obstacle detection sensor (115) may include at least one of an ultrasonic sensor, an infrared sensor, an RF (radio frequency) sensor, a geomagnetic sensor, and a PSD (Position Sensitive Device) sensor. The obstacle detection sensor (115) can detect objects present in front of, behind, to the side of, or on the movement path of the robot (100). The obstacle detection sensor (115) can provide information about the detected objects to one or more processors (140).

[0056] The communication interface (150) may include hardware components to support the transmission and / or reception of electrical signals between the robot (100) and an external electronic device. The external electronic device may include a server, a home appliance, a mobile device (e.g., a smartphone, a tablet PC, a wearable device, etc.).

[0057] For example, the communication interface (150) may include a communication circuit capable of performing data communication between a robot (100) and an electronic device using at least one of a data communication method including wired LAN, wireless LAN, Wi-Fi, Wi-Fi Direct, Bluetooth, ZigBee, WFD (Wi-Fi Direct), infrared communication (IrDA, infrared Data Association), BLE (Bluetooth Low Energy), NFC (Near Field Communication), Wibro (Wireless Broadband Internet), WiMAX (World Interoperability for Microwave Access), SWAP (Shared Wireless Access Protocol), WiGig (Wireless Gigabit Alliances, WiGig) and RF communication.

[0058] The input interface (160) includes circuitry. The input interface (160) can receive user input and transmit the user input to the processor (140). For example, the input interface (160) can receive various user inputs for setting or selecting various functions supported by the robot (100).

[0059] The input interface (160) may include various types of input devices.

[0060] According to one example, the input interface (160) may include a physical button. The physical button may include a function key or a dial button. The physical button may be implemented as one or more keys.

[0061] According to one example, the input interface (160) can receive user input using a touch method. For example, the input interface (160) can be implemented as a touch screen capable of performing the function of a display (171).

[0062] According to one example, the input interface (160) can receive user voice using a microphone. One or more processors (140) can perform functions corresponding to user voice using voice recognition. For example, one or more processors (140) can convert user voice into text data using a Speech To Text (STT) function, obtain control command data based on the text data, and perform functions corresponding to user voice based on the control command data. According to an embodiment, the STT function may be performed on an external server.

[0063] The output interface (170) may include a display (171) and a speaker (172).

[0064] The display (171) can display various screens. One or more processors (140) can display various notifications, messages, information, etc. related to the operation of the robot vacuum cleaner (100) on the display (11).

[0065] The display (171) may be implemented as a display including a self-emissive element or as a display including a non-emissive element and a backlight. For example, the display (171) may be implemented as various types of displays such as an LCD (Liquid Crystal Display), an OLED (Organic Light Emitting Diodes) display, an LED (Light Emitting Diodes) display, a micro LED display, a Mini LED display, a QLED (Quantum dot light-emitting diodes) display, etc.

[0066] The speaker (172) can output an audio signal. The processor (140) can output warning sounds, notification messages, response messages corresponding to user input, etc. related to the operation of the robot vacuum cleaner (100) through the speaker (172).

[0067] The microphone (180) can receive an acoustic signal. The microphone (180) can acquire sound output from an external object. The number of microphones may be one or more depending on the embodiment.

[0068] FIG. 4 is a diagram illustrating the operation of a robot moving to an exit according to one embodiment. A processor (140) may perform at least one of the operations of FIG. 4. When instructions stored in memory (130) are executed individually or collectively by the processor (140), the robot (100) may be made to perform the operations of FIG. 4.

[0069] In operation 410, the robot (100) can identify that a disaster situation has occurred in the space.

[0070] In one embodiment, the disaster situation may include a situation in which a fire occurs in the space where the robot (100) is located.

[0071] For example, the robot (100) can identify that a disaster has occurred if it receives a signal from an external electronic device indicating that a disaster has occurred through a communication interface (150). The external electronic device may be a server for remotely controlling and monitoring various devices (e.g., robots) in the space. According to an embodiment, the robot (100) can identify that a disaster has occurred if it detects a light emitted from a warning light installed in the space using a camera (113) or receives a warning sound generated in the space through a microphone (180).

[0072] In operation 410-N, the robot (100) may not perform subsequent operations if it is not identified that a disaster situation has occurred in the space. For example, if the robot (100) is not identified that a disaster situation has occurred in the space, it may perform operations in the space.

[0073] In operations 410-Y, 420, 430, when it is identified that a disaster situation has occurred in the space, the robot (100) identifies a path to move from the location of the robot (100) to the exit of the space by passing through a plurality of landmarks installed in the space based on map data, and can obtain information on the direction and distance of the robot (100) to move along the path based on map data.

[0074] For example, the path may be a path for the robot (100) to move from its current location to an exit while passing through at least one landmark installed in space.

[0075] In one embodiment, the map data may include information about the space. The memory (130) may store the map data. The map data may be used for the robot (100) to sense the surrounding environment, determine the location of the robot (100), and plan a path. For example, the map data may include information about the location of exits, the location of obstacles (e.g., walls, pillars, etc.), and the area where the robot (100) can move on the map. Additionally, the map data may include terrain information indicating the structure of the terrain of the space.

[0076] In one embodiment, map data may include information regarding the location and shape of a landmark. A landmark may be installed in space. A landmark may be a structure having a shape that can be distinguished by a point cloud or depth. While driving in space, the robot (100) may detect a plurality of landmarks in space using a camera (113) or a LiDAR sensor (114) and store information regarding the location and shape of the plurality of landmarks in the map data. For example, the location of a landmark may be expressed as coordinate values ​​(e.g., (x,y) coordinate values). The shape of a landmark may be expressed by a point cloud. A point cloud may be a set of points representing the surface of an object in three-dimensional space. The robot (100) may acquire a point cloud for a landmark using a depth camera.

[0077] In one embodiment, the map data may include a path for the robot (100) to move to an exit while passing at least one landmark for each location in space, and information for the robot (100) to move along said path. The information may include information regarding the direction and distance of the robot (100).

[0078] For example, the above path may include a first path and a second path.

[0079] The first path may be a path for moving from a location in space (e.g., (x,y) coordinate value) to the landmark closest to said location (hereinafter referred to as the first landmark).

[0080] Information for a robot (100) to move from a position to a first landmark along a first path may include the direction angle of the first landmark relative to the position and the distance between the position and the first landmark.

[0081] The second path may be a path for the robot (100) to move from the first landmark through at least one landmark to the exit. For example, the second path may be set such that the next landmark of a landmark on the second path has no obstacles between it and the landmark and is the landmark closest to the landmark. Additionally, if there are obstacles between the landmark and the landmarks adjacent to the landmark, the second path may be determined such that the landmark with the smallest obstacle between it and the landmark becomes the next landmark.

[0082] Information for a robot (100) to move from a first landmark to an exit along a second path, passing through at least one landmark, may include information regarding the direction angle of the next landmark relative to the landmark and the distance between the landmark and the next landmark for each landmark. The next landmark may be a landmark or an exit that the robot (100) moves from the landmark to along the second path.

[0083] In one embodiment, the robot (100) may identify a path to move to an exit while passing at least one landmark from a location in space, store the path in map data, obtain information about the direction and distance of the robot (100) to move along the path, and store the obtained information in map data.

[0084] For example, the robot (100) can identify the location of the robot (100) on a map using a camera (113) and / or a lidar sensor (114), and can identify the first landmark closest to the location of the robot (100) based on location information of a plurality of landmarks installed in space. According to an embodiment, the robot (100) may identify the first landmark using a camera (113) or a lidar sensor (114).

[0085] The robot (100) can identify a first path for moving to a first landmark from the position of the robot (100). For example, the robot (100) can identify the first path using map data. The robot (100) can obtain information for the robot (100) to move to the first landmark along the first path. The information may include the direction angle of the first landmark relative to the position of the robot (100) and the distance between the position and the first landmark. For example, the robot (100) can obtain the information using map data or by driving along the first path and using a sensor (110).

[0086] The robot (100) can identify a second path for the robot (100) to move from a first landmark past at least one landmark to an exit. For example, the robot (100) can identify the second path using map data. The robot (100) can obtain information for the robot (100) to move to an exit along the second path. The information may include, for each landmark, the direction angle of the next landmark relative to the landmark and the distance between the landmark and the next landmark. The next landmark may be a landmark or an exit from which the robot (100) moves from the landmark along the second path. For example, the robot (100) may obtain the information using map data or obtain the information using a sensor (110) while driving along the second path.

[0087] Referring to FIG. 5, the map (501) may include a plurality of landmarks (510a, 510b, 510c, 510d, 510e, 510f, 510g, 510h, 510i, 510j) and a plurality of obstacles (520a, 520b, 520c, 520d).

[0088] The robot (100) can identify the shortest path (550) to move from the robot's (100) location (530) to the exit (540) while passing through landmarks.

[0089] For example, the robot (100) can identify the nearest landmark (510e) to the location (530) of the robot (100) based on the map (501) and identify a path (551) from the location (530) to the landmark (510e). The robot (100) can store the path (551) in map data and store information in the map data for the robot (100) to move from the location (530) to the landmark (510e) along the path (551). For example, the information may include the orientation angle of the landmark (510e) relative to the location (530) and the distance between the location (530) and the landmark (510e).

[0090] For example, the robot (100) can identify a path (552) for the robot (100) to move from a landmark (510e) to an exit (540) while passing through landmarks, taking into account the distance between landmarks and / or obstacles between landmarks, and can store the path (552) in map data.

[0091] For example, the path from landmark (510e) to landmark (510i) includes a path where the robot (100) moves from landmark (510e) to landmark (510d) and then to landmark (510i), and a path where the robot (100) moves from landmark (510e) to landmark (510j) and then to landmark (510i). There is an obstacle (520d) between landmark (510j) and landmark (510i). Therefore, the robot (100) can identify the path (552) such that the path where the robot (100) moves from landmark (510e) to landmark (510d) and then to landmark (510i) is included in the path (552). The robot (100) can store information in the map data for the robot (100) to move from landmark (510e) to landmark (510i) along the said path. For example, the above information may include the direction angle of the landmark (510d) relative to the landmark (510e), the distance between the landmark (510e) and the landmark (510d), the direction angle of the landmark (510i) relative to the landmark (510d), and the distance between the landmark (510d) and the landmark (510i).

[0092] For example, the path where the robot (100) starts at landmark (510i), passes through landmark (510h), and moves to landmark (510g) is the shortest path to the exit (540) with no obstacles between the landmarks. Therefore, the robot (100) can identify the path (552) such that the path where the robot (100) moves from landmark (510i) to landmark (510h) and then moves to landmark (510g) is included in the path (552). The robot (100) can store information for the robot (100) to move from landmark (510i) to landmark (510g) along the said path in the map data. For example, the above information may include the direction angle of the landmark (510h) relative to the landmark (510i), the distance between the landmark (510i) and the landmark (510h), the direction angle of the landmark (510g) relative to the landmark (510h), and the distance between the landmark (510h) and the landmark (510g).

[0093] For example, the path from the landmark (510g) to the exit (540) includes a path where the robot (100) starts at the landmark (510g), moves in the order of landmark (510b), landmark (510a), and landmark (510f), and then moves to the exit (540); a path where the robot (100) starts at the landmark (510g), moves in the order of landmark (510a) and landmark (510f), and then moves to the exit (540); and a path where the robot (100) moves from the landmark (510g) to the landmark (510f) and then moves to the exit (540). There is an obstacle (520b) between the landmark (510g) and the landmark (510b), and there is an obstacle (520a) between the landmark (510g) and the landmark (510f). The size of the obstacle (520a) is smaller than the size of the obstacle (520b). Additionally, the path from the landmark (510g) through the landmark (510f) to the exit (540) is shorter than the remaining paths. Therefore, the robot (100) can identify the path (552) such that the path from the landmark (510g) to the landmark (510f) and then to the exit (540) is included in the path (552). The robot (100) can store information in the map data for the robot (100) to move from the landmark (510g) to the exit (540) along the path. For example, the information may include the direction angle of the landmark (510f) relative to the landmark (510g), the distance between the landmark (510g) and the landmark (510f), the direction angle of the exit (540) relative to the landmark (510f), and the distance between the landmark (510f) and the exit (540).

[0094] According to an embodiment, the robot (100) can select a path where there are no obstacles between landmarks. In the example described above, the robot (100) can identify a path (552) such that a path where there are no obstacles on the path (e.g., a path where the robot (100) starts at landmark (510g), moves in the order of landmark (510a) and landmark (510f), and then moves to the exit (540)) is included in the path (552).

[0095] In this way, the map data may include information regarding the path for the robot (100) to move from a location to an exit via at least one landmark, and the direction and distance of the robot (100) to move along the path, for each location of the robot (100).

[0096] In one embodiment, the robot (100) can obtain information for moving from the robot's (100) location to an exit and moving along the said path by using information stored in map data in the event of a disaster.

[0097] In the example described in FIG. 5, it is assumed that the robot (100) is at location (530) in a disaster situation. Based on map data, the robot (100) can obtain a path (551, 552) for moving from location (530) to the exit (540) while passing landmarks (510e, 510d, 510i, 510h, 510g, 510f). Additionally, based on map data, the robot (100) can obtain information for the robot (100) to move along the path (551, 552).

[0098] For example, the above information includes the direction angle of a landmark (510e) relative to a location (530) and the distance between the location (530) and the landmark (510e), the direction angle of a landmark (510d) relative to a landmark (510e) and the distance between the landmark (510e) and the landmark (510d), the direction angle of a landmark (510i) relative to a landmark (510d) and the distance between the landmark (510d) and the landmark (510i), the direction angle of a landmark (510h) relative to a landmark (510i) and the distance between the landmark (510i) and the landmark (510h), the direction angle of a landmark (510g) relative to a landmark (510h) and the distance between the landmark (510h) and the landmark (510g), the direction angle of a landmark (510f) relative to a landmark (510g) and the distance between the landmark (510g) and the landmark (510f), and relative to a landmark (510f). It may include the direction angle of the exit (540) and the distance between the landmark (510f) and the exit (540).

[0099] In operation 440, the robot (100) can control the driving unit (120) so that the robot (100) moves along a path based on the acquired direction, the acquired distance traveled, and the direction and distance traveled of the robot (100) detected through the sensor (110).

[0100] In one embodiment, the robot (100) can control the driving unit (120) so that, based on the acquired direction and distance traveled, the robot (100) moves to the landmark closest to the location of the robot (100), and sequentially moves along the landmarks on the path from the landmark to which the robot (100) moved.

[0101] For example, the robot (100) can move using an odometry method. Odometry may refer to a method of estimating a position from a starting position by measuring the distance the robot (100) has moved using an encoder. For example, the robot (100) can move in the direction obtained based on the inertial sensor (111) and move by the distance traveled based on the encoder (112).

[0102] Referring to FIG. 6, a disaster situation may occur while the robot (100) is at location (610). Location (610) is assumed to be the same as the location (530) described in FIG. 5. Based on map data (501), the robot (100) can obtain information (e.g., direction angle and distance traveled) to move to the exit (540) starting from location (610) and passing through landmarks (510e, 510d, 510i, 510h, 510g, 510f). The robot (100) can move to the exit (540) based on the information and information obtained through the sensor (110).

[0103] For example, the robot (100) can move from the location (610) toward the direction where the landmark (510e) is located by using information about the orientation angle of the landmark (510e) relative to the location (610) and data detected by the inertial sensor (111). The robot (100) can move by the distance between the location (610) and the landmark (510e) by using the distance between the location (610) and the landmark (510e) and data detected by the encoder (112). Accordingly, as shown in 621 of FIG. 6, the robot (100) can move from the location (610) toward the landmark (510e).

[0104] For example, the robot (100) can move from the landmark (510e) toward the direction where the landmark (510d) is located by using information about the orientation angle of the landmark (510d) relative to the landmark (510e) and data detected by the inertial sensor (111). The robot (100) can move by the distance between the landmark (510e) and the landmark (510d) by using the distance between the landmark (510e) and the landmark (510d) and data detected by the encoder (112). Accordingly, as shown in 622 of FIG. 6, the robot (100) can move from the landmark (510e) toward the landmark (510d).

[0105] For example, the robot (100) can move from the landmark (510d) toward the direction where the landmark (510i) is located by using information about the orientation angle of the landmark (510i) relative to the landmark (510d) and data detected by the inertial sensor (111). The robot (100) can move by the distance between the landmark (510d) and the landmark (510i) by using the distance between the landmark (510d) and the landmark (510i) and data detected by the encoder (112). Accordingly, as shown in 623 of FIG. 6, the robot (100) can move from the landmark (510d) toward the landmark (510i).

[0106] For example, the robot (100) can move from the landmark (510i) toward the direction where the landmark (510h) is located using information about the orientation angle of the landmark (510h) relative to the landmark (510i) and data detected by the inertial sensor (111). The robot (100) can move by the distance between the landmark (510i) and the landmark (510h) using the distance between the landmark (510i) and the landmark (510h) and data detected by the encoder (112). Accordingly, as shown in 624 of FIG. 6, the robot (100) can move from the landmark (510i) toward the landmark (510h).

[0107] For example, the robot (100) can move from the landmark (510h) toward the direction where the landmark (510g) is located using information about the orientation angle of the landmark (510g) relative to the landmark (510h) and data detected by the inertial sensor (111). The robot (100) can move by the distance between the landmark (510h) and the landmark (510g) using the distance between the landmark (510h) and the landmark (510g) and data detected by the encoder (112). Accordingly, as shown in 625 of FIG. 6, the robot (100) can move from the landmark (510h) toward the landmark (510g).

[0108] For example, the robot (100) can move from the landmark (510g) toward the direction where the landmark (510f) is located by using information regarding the orientation angle of the landmark (510f) relative to the landmark (510g) and data detected by the inertial sensor (111). The robot (100) can move by the distance between the landmark (510g) and the landmark (510f) and data detected by the encoder (112). Accordingly, as shown in 626 of FIG. 6, the robot (100) can move from the landmark (510g) toward the landmark (510f). Meanwhile, there is an obstacle (520a) between the landmark (510g) and the landmark (510f). The robot (100) can perform avoidance driving toward the obstacle, the specific details of which will be described later.

[0109] For example, the robot (100) can move from the landmark (510f) toward the direction where the exit (540) is located using information about the direction angle of the exit (540) relative to the landmark (510f) and data detected by the inertial sensor (111). The robot (100) can move by the distance between the landmark (510f) and the exit (540) using the distance between the landmark (510f) and the exit (540) and data detected by the encoder (112). Accordingly, as shown in 627 of FIG. 6, the robot (100) can move from the landmark (510f) toward the exit (540).

[0110] In this way, when a disaster occurs, the robot (100) can move to an exit by odometry-based driving. Accordingly, according to the present disclosure, the robot (100) can safely evacuate to an exit even when the camera (113) or lidar sensor (114) cannot be used due to smoke from a fire, thereby preventing the explosion of the robot's (100) battery and thus preventing property damage.

[0111] In one embodiment, when an obstacle is detected while the robot (100) is moving along a path, it can move along the path to an exit while avoiding the obstacle. For example, when an obstacle is detected, the robot (100) can move off the path, return to the path to avoid the obstacle, and move along the path to an exit.

[0112] FIG. 7 is a diagram illustrating the movement of a robot moving while avoiding obstacles according to one embodiment. A processor (140) may perform at least one of the movements of FIG. 7. Instructions stored in memory (130) may cause the robot (100) to perform the movements of FIG. 7 when executed individually or collectively by the processor (140).

[0113] In FIG. 7, the robot (100) can identify whether there is an obstacle in front using an obstacle detection sensor (115). For example, the robot (100) can identify whether there is an obstacle within a preset distance. For example, the preset distance may be set during the manufacturing or initial use of the robot (100), or may be set and changed by user input. As an example, the preset distance may be 1m. However, it is not limited thereto, and the preset distance may be various values.

[0114] In FIG. 7, the robot (100) can rotate 90 degrees and / or 180 degrees clockwise or counterclockwise using an inertial sensor (111). In FIG. 7, the robot (100) can move a preset distance (e.g., 1 m) using an encoder (112).

[0115] In operation 710, the robot (100) can identify whether there is an obstacle ahead while moving along a path to the exit. For example, the robot (100) can identify whether there is an obstacle within a preset distance (e.g., 1 m).

[0116] In operations 710-Y, 715, 720, the robot (100) rotates 90 degrees counterclockwise when an obstacle is detected, and can identify whether there is an obstacle in front after the rotation. For example, the robot (100) can identify whether there is an obstacle within a preset distance (e.g., 1 m).

[0117] In operations 720-Y, 740, and 745, the robot (100) can rotate 90 degrees clockwise when an obstacle is detected, and then rotate 90 degrees clockwise again after the rotation. In operation 750, the robot (100) can identify whether there is an obstacle in front after two rotations.

[0118] In operation 720-N, 725, if no obstacle is detected, the robot (100) may move a preset distance and then rotate 90 degrees clockwise. For example, the preset distance may be set at the time of manufacturing or initial use of the robot (100), or may be set and changed by user input. For example, the preset distance may be 1m. However, it is not limited thereto, and the preset distance may be various values.

[0119] In operation 730, the robot (100) can identify whether it is located on the initial path. The initial path may be the path the robot (100) was traveling on (e.g., a path to the exit). For example, the robot (100) can identify whether it is located on the initial path based on the orientation angle of the robot (100) detected based on the inertial sensor (111) and the distance traveled by the robot (100) detected based on the encoder (112).

[0120] In operation 730-N, 735, the robot (100) can identify whether there is an obstacle ahead if it is not located on the initial path. For example, the robot (100) can identify whether there is an obstacle within a preset distance (e.g., 1 m).

[0121] In operation 735-N, 725, 730, if no obstacle is detected, the robot (100) moves a preset distance and then rotates 90 degrees clockwise and can identify whether it is located on the initial path. In operation 735, if the robot (100) is not located on the initial path, it can identify whether there is an obstacle ahead.

[0122] In operation 735-Y, 715, 720, the robot (100) rotates 90 degrees counterclockwise when an obstacle is detected, and can identify whether there is an obstacle in front after the rotation.

[0123] In operation 720-Y, 745, 750, the robot (100) can rotate 90 degrees clockwise when an obstacle is detected, and then rotate 90 degrees clockwise again after rotation.

[0124] In operation 750, the robot (100) can identify whether there is an obstacle in front after turning twice. For example, the robot (100) can identify whether there is an obstacle within a preset distance (e.g., 1 m).

[0125] In operation 750-N, 755, if no obstacle is detected, the robot (100) may move a preset distance and then rotate 90 degrees counterclockwise. For example, the preset distance may be set at the time of manufacturing or initial use of the robot (100), or may be set and changed by user input. For example, the preset distance may be 1m. However, it is not limited thereto, and the preset distance may be various values.

[0126] In operation 760, the robot (100) can identify whether it is located on the initial path. The initial path may be the path the robot (100) was traveling on (e.g., the shortest path to the exit). For example, the robot (100) can identify whether it is located on the initial path based on the orientation angle of the robot (100) detected based on the inertial sensor (111) and the distance traveled by the robot (100) detected based on the encoder (112).

[0127] In operation 760-N, 765, the robot (100) can identify whether there is an obstacle ahead if it is not located on the initial path. For example, the robot (100) can identify whether there is an obstacle within a preset distance (e.g., 1 m).

[0128] In operation 765-N, 755, 760, if no obstacle is detected, the robot (100) moves a preset distance and then rotates 90 degrees counterclockwise and can identify whether it is located on the initial path. In operation 765, if the robot (100) is not located on the initial path, it can identify whether there is an obstacle ahead.

[0129] In operation 765-Y, 745, 750, the robot (100) rotates 90 degrees clockwise when an obstacle is detected and can identify whether there is an obstacle in front after the rotation. In operation 750-Y, 745, 750, the robot (100) rotates 90 degrees clockwise when an obstacle is detected and can identify whether there is an obstacle in front after the rotation.

[0130] In operation 730-Y, 760-Y, 700, when the robot (100) is positioned on the initial path, it can rotate 180 degrees clockwise or counterclockwise. Depending on the 180-degree rotation, the front of the robot (100) can become the direction in which the robot (100) was moving along the initial path. In operation 775, the robot (100) can move along the path again.

[0131] In this way, the robot (100) can avoid obstacles by using avoidance driving and move to the exit along the shortest path.

[0132] FIG. 8 shows an example of a robot performing avoidance driving according to one embodiment.

[0133] In FIG. 8, the robot (100) can move along a path (801) based on autometry. The path (801) may be a path for the robot (100) to move to an exit.

[0134] Referring to 811 in FIG. 8, the robot (100) can detect an obstacle (831) in front while driving along a path (801). Referring to 812 in FIG. 8, if the obstacle (831) is detected, the robot (100) can rotate 90 degrees counterclockwise and identify whether there is an obstacle in front. If no obstacle is detected, the robot (100) can move a preset distance and then rotate 90 degrees clockwise. Referring to 813 in FIG. 8, if the robot (100) is identified as not being located on the path (801), it can identify whether there is an obstacle in front. If no obstacle is detected, the robot (100) can move a preset distance and then rotate 90 degrees clockwise. Referring to 814 in FIG. 8, if the robot (100) is identified as not being located on the path (801), it can identify whether there is an obstacle in front. If no obstacle is detected, the robot (100) can move a preset distance and then rotate 90 degrees clockwise. Referring to 815 in FIG. 8, if the robot (100) is identified as being located on path (801), it can rotate 180 degrees and move along path (801).

[0135] Referring to 815 in FIG. 8, the robot (100) can detect an obstacle (832) in front while driving along a path (801). Referring to 816 in FIG. 8, when the obstacle (832) is detected, the robot (100) can rotate 90 degrees counterclockwise and identify whether there is an obstacle in front. If no obstacle is detected, the robot (100) can move a preset distance and then rotate 90 degrees clockwise. Referring to 817 in FIG. 8, when the robot (100) is identified as not being located on the path (801), it can identify whether there is an obstacle in front. If no obstacle is detected, the robot (100) can move a preset distance and then rotate 90 degrees clockwise. Referring to 818 in FIG. 8, when the robot (100) is identified as not being located on the path (801), it can identify whether there is an obstacle in front. When an obstacle (833) is detected, the robot (100) can rotate 90 degrees counterclockwise and identify whether there is an obstacle in front. When no obstacle is detected, the robot (100) can move a preset distance and then rotate 90 degrees clockwise. Referring to 819 in FIG. 8, when the robot (100) is identified as not being located on the path (801), it can identify whether there is an obstacle in front. When no obstacle is detected, the robot (100) can move a preset distance and then rotate 90 degrees clockwise. Referring to 821 in FIG. 8, when the robot (100) is identified as being located on the path (801), it can rotate 180 degrees and move along the path (801).

[0136] FIG. 9 is a diagram illustrating the operation of a robot moving toward an exit according to one embodiment. A processor (140) may perform at least one of the operations of FIG. 9. Instructions stored in memory (130) may cause the robot (100) to perform the operations of FIG. 9 when executed individually or collectively by the processor (140). Regarding the operation of the robot (100) illustrated in FIG. 9, details that overlap with previously described content are omitted for brevity.

[0137] In operation 910, the robot (100) can store information in the map data regarding the path for moving from a location in space to an exit and the path for the robot (100) to move along.

[0138] For example, the path may be a path for the robot (100) to start at the above location, pass through at least one landmark, and move to the exit. The information may include the direction and distance of the robot (100) to move along the path.

[0139] In operation 915, the robot (100) can identify whether a disaster situation has occurred in the space.

[0140] In operation 915-Y, 920, the robot (100) can identify whether the camera (113) and lidar sensor (114) are available when it is identified that a disaster situation has occurred in the space.

[0141] For example, the use of the camera (113) and the lidar sensor (114) may be impossible due to smoke from a fire that has occurred in the space. The robot (100) can monitor the status of the camera (113) and the lidar sensor (114) to identify whether the camera (113) and the lidar sensor (114) are in a usable state. For example, the sensor driver of the robot (100) can generate an interrupt signal based on the brightness value of the image acquired through the camera (113), if the image is too bright or too dark. As another example, the sensor driver can generate an interrupt signal if the value measured by the lidar sensor (114) has a fixed value or is outside a specific range. When the processor (140) identifies that an interrupt signal has been generated, it can identify that the camera (113) and the lidar sensor (114) are in a state where they are unusable.

[0142] In operation 920-Y, 930, if the robot (100) is identified as being able to use the camera (113) or the lidar sensor (114), it can move to the exit using the camera (113) or the lidar sensor (114).

[0143] In one embodiment, the robot (100) can obtain a path to move from the current location of the robot (100) past at least one landmark to an exit based on map data and set a path. The robot (100) can move to the exit along the set path while recognizing the surrounding environment using a camera (113) or a LiDAR sensor (114) and avoiding obstacles.

[0144] In operation 920-N 940, if the robot (100) is identified as being unable to use the camera (113) and the lidar sensor (114), it can move to the exit via odometry-based driving.

[0145] In one embodiment, the robot (100) can set a path by obtaining a path to move from the current position of the robot (100) past at least one landmark to an exit based on map data. The robot (100) can move to the exit along the set path using an inertial sensor (111) and an encoder (112). If an obstacle is detected while the robot (100) is driving along the path, the robot (100) can avoid the obstacle by driving around it.

[0146] According to the embodiment, the camera (113) may be in a usable state even if a disaster situation occurs. When the robot (100) identifies that the camera (113) is usable, it can move to the exit using the camera (113). For example, the robot (100) can acquire a point cloud using the camera (113). The robot (100) can compare the acquired point cloud with the point clouds of landmarks stored in the map data to identify landmarks on the path or landmarks around the set path, and move sequentially to the identified landmarks to move to the exit.

[0147] According to an embodiment, while the robot (100) is moving along a path, it may output a notification to indicate that a disaster situation has occurred. For example, the robot (100) may output light through a warning light installed on the robot (100) or output a warning sound through a speaker (172).

[0148] Various embodiments of the present document may be implemented as software comprising one or more instructions stored in a storage medium (e.g., memory (130)) readable by a machine (e.g., robot (100)). For example, a processor (e.g., processor (140)) of the machine (e.g., robot (100)) may call at least one of the one or more instructions stored in the storage medium and execute it. This enables the machine to be operated to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. The storage medium readable by the machine may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' simply means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily.

[0149] According to one embodiment, the method according to the various embodiments disclosed herein may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or an application store (e.g., Play Store). ™It can be distributed online (e.g., downloaded or uploaded) through ) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0150] According to various embodiments, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to integration. According to various embodiments, operations performed by the module, program, or other components may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0151] Although preferred embodiments of the present disclosure have been illustrated and described above, the present disclosure is not limited to the specific embodiments described above. It is understood that various modifications can be made by those skilled in the art without departing from the essence of the present disclosure as claimed in the claims, and such modifications should not be understood individually from the technical spirit or perspective of the present disclosure.

Claims

1. In a robot that navigates space, Driving part; A sensor for measuring the travel distance of the above robot; Memory for storing instructions; and at least one processor including processing circuitry; and When the above instructions are executed individually or collectively by the at least one processor, the robot, If it is identified that a disaster situation has occurred in the above space, based on map data stored in the memory, the robot identifies a path to move from the robot's location to the exit of the above space while passing through a plurality of landmarks installed in the above space, and Based on the above map data, information regarding the direction and distance of the robot for the robot to move along the above path is obtained, and A robot that controls the driving unit so that the robot moves along the path based on the direction obtained above, the distance traveled above, and the direction and distance traveled of the robot detected through the sensor.

2. In Paragraph 1, The above map data is, A robot comprising information regarding the location and shape of a plurality of landmarks in the space, a path for the robot to move to an exit while passing at least one landmark for each location in the space, and the direction and distance of the robot to move along the path.

3. In Paragraph 2, When the above instructions are executed individually or collectively by the at least one processor, the robot, A robot that controls the driving unit so that, based on the direction and distance traveled above, the robot moves to the landmark closest to the robot's position among a plurality of landmarks, and sequentially moves along the landmarks on the path from the landmark the robot moved to.

4. In Paragraph 3, The above sensor includes an inertial measurement unit (IMU) sensor and an encoder, and When the above instructions are executed individually or collectively by the at least one processor, the robot, A robot that moves in the direction obtained based on the inertial sensor and moves by the distance obtained based on the encoder.

5. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the robot, A robot that identifies the path and moves to the exit when it is determined that the use of the lidar sensor and camera of the Sangri robot is impossible in the above disaster situation.

6. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the robot, A robot that moves along the path to the exit while avoiding obstacles if an obstacle is detected while moving along the path.

7. In Paragraph 6, When the above instructions are executed individually or collectively by the at least one processor, the robot, A robot that, when the above obstacle is detected, deviates from the path and returns to the path to avoid the obstacle, and moves along the path to the exit.

8. In a driving method of a robot for moving to an exit in a disaster situation, When it is identified that the above disaster situation has occurred in the space, the operation of identifying a path for the robot to move from the robot's location to the exit of the space by passing through a plurality of landmarks installed in the space based on map data; An operation to obtain information regarding the direction and distance of the robot for the robot to move along the path based on the map data above; and A driving method comprising: a motion in which the robot moves along the path based on the direction obtained, the distance traveled obtained, and the direction and distance traveled of the robot detected through the robot’s sensor.

9. In Paragraph 8, The above map data is, A driving method comprising information on the location and shape of a plurality of landmarks in the space, a path for the robot to move to an exit while passing at least one landmark for each location in the space, and the direction and distance of the robot to move along the path.

10. In Paragraph 9, The above moving motion is, A driving method comprising: moving to the landmark closest to the robot's position among the plurality of landmarks based on the direction and distance traveled above, and sequentially moving along the landmarks on the path from the landmark the robot moved to.

11. In Paragraph 10, The above sensor includes an inertial measurement unit (IMU) sensor and an encoder, and The above moving motion is, A driving method comprising: moving in the direction obtained based on the inertial sensor, and moving by the distance obtained based on the encoder.

12. In Paragraph 8, The above-mentioned identifying operation is, A driving method comprising: an action of identifying the path when it is identified that the use of the lidar sensor and camera of the Sangri robot is impossible in the above disaster situation.

13. In Paragraph 8, The above moving motion is, A driving method comprising: moving to the exit along the path while avoiding the obstacle when an obstacle is detected and identified while moving along the path.

14. In Paragraph 13, The above moving motion is, A driving method comprising: when the obstacle is detected, moving away from the path, returning to the path to avoid the obstacle, and moving along the path to the exit.

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