Indoor robot autonomous exploration and mapping method, device and robot

Abstract

The present invention provides an indoor robot autonomous exploration and mapping method, S1, obtain a laser radar scanning frame S; S2, traverse the scanning frame S, obtain all candidate ray sets A whose scanning distance exceeds the laser radar range; S3, classify the candidate ray set A to obtain subsets; S4, obtain the number of the subset Ai and use it as a tree node according to the current posture of the robot; control the robot to explore along the tree node until the node N has no leaves; S5, determine whether there are unexplored leaves at the node N-1, if there are unexplored leaf directions, control the robot to go to the posture of the node N-1, and continue to explore; S6, obtain the map established by the robot using SLAM during the exploration process. The present invention automatically classifies the rays according to the range and angle of the rays, and uses a tree structure to explore the direction of the robot's exploration, which has efficient exploration capabilities and improves the full coverage rate.

Description

Technical Field

[0001] The present invention relates to the field of robotics technology, and in particular to an indoor robot autonomous exploration and mapping method, device and robot. Background Art

[0002] In recent years, with the advancement and maturity of autonomous navigation technology, indoor service robots (including indoor sweepers, hotel food delivery robots, building patrol robots, etc.) have been widely promoted and invested. Generally, the maps used by indoor robots need to be built and deployed in advance. Usually, the on-site deployment personnel push the robot or remotely control the robot to model the environment to generate a two-dimensional grid map that can be used for navigation and positioning. This will bring a lot of inconvenience. For a hotel with dozens of floors, the on-site deployment personnel need to control the robot to model dozens of floors, which is a hard job.

[0003] Most existing robots use LiDAR for mapping. LiDAR is a radar system that emits laser beams to detect the position of a target. Its working principle is to emit a detection signal (laser beam) to the target, and then compare the received signal reflected from the target (target echo) with the transmitted signal. After appropriate processing, relevant information about the target can be obtained, such as target distance, direction and other parameters.

[0004] Therefore, having an autonomous exploration and mapping method will help reduce the pressure on deployment personnel and improve the ease of use of robots.

[0005] The background description provided herein is for the purpose of generally presenting the context of the present disclosure. Unless otherwise indicated herein, the materials described in this section are not prior art to the claims of this application and are not admitted to be prior art by inclusion in this section. Summary of the invention

[0006] In view of the above technical problems in the related art, the present invention proposes an indoor robot autonomous exploration and mapping method, which comprises the following steps:

[0007] S1, obtain the laser radar scanning frame S obtained by the robot rotating one circle;

[0008] S2, traverse the scanning frame S, obtain all rays whose scanning distance exceeds the laser radar range, obtain the angles corresponding to the rays, and record the rays as a candidate ray set A;

[0009] S3, classifying the candidate ray set A to obtain subsets A1, A2, ... Ai, wherein all rays in the subset Ai satisfy that the difference between the maximum ray angle and the minimum ray angle is greater than a first preset angle, and the angle between any two rays does not exceed the minimum resolution angle of the laser radar;

[0010] S4, obtaining the number of the subsets Ai and using the current posture of the robot as a node of the tree, wherein each subset in the subset Ai is used as a child node of the tree node, wherein each node represents a direction that the robot can explore; controlling the robot to explore along the tree nodes until the node N has no leaves; wherein the exploration process is to control the robot to move forward a preset distance in the direction of the leaves of the tree and repeat steps S1-S3;

[0011] S5, determining whether there is an unexplored leaf at the node N-1, and if there is an unexplored leaf direction, controlling the robot to go to the position of the node N-1 and continue exploring;

[0012] S6, obtaining the map created by the robot using SLAM during the exploration process;

[0013] Specifically, in step S2, the rays are sorted according to the angles, and are recorded as a candidate ray set A.

[0014] Specifically, the first preset angle is 60 degrees.

[0015] Specifically, the first preset distance is 3m.

[0016] In a second aspect, another embodiment of the present invention discloses an indoor robot autonomous exploration and mapping device, which includes the following units:

[0017] A laser radar scanning frame acquisition unit, used to acquire a laser radar scanning frame S obtained by one rotation of the robot;

[0018] A candidate ray set acquisition unit, used for traversing the scanning frame S, acquiring all rays whose scanning distance exceeds the laser radar range, acquiring angles corresponding to the rays, and recording the rays as a candidate ray set A;

[0019] A subset classification unit, used for classifying the candidate ray set A to obtain subsets A1, A2, ... Ai, wherein all rays of the subset Ai satisfy that the difference between the maximum ray angle and the minimum ray angle is greater than a first preset angle, and the angle between any two rays does not exceed the minimum resolution angle of the laser radar;

[0020] The first exploration unit is used to obtain the number of subsets Ai and use the current posture of the robot as a node of the tree, each subset in the subset Ai as a subnode of the tree node, wherein each node represents a direction that the robot can explore; control the robot to explore along the tree node until the node N has no leaves; wherein the exploration process is to control the robot to move forward a preset distance along the leaf direction of the tree and repeatedly execute the laser radar scanning frame acquisition unit, the candidate ray set acquisition unit, and the subset classification unit;

[0021] The second exploration unit is used to determine whether there is an unexplored leaf at the node N-1. If there is an unexplored leaf direction, the robot is controlled to go to the position of the node N-1 to continue exploring.

[0022] A mapping unit is used to synchronously obtain the map created by the robot using SLAM during the exploration process;

[0023] Specifically, in the candidate ray set acquisition unit, the rays are sorted according to the angle sizes, and the rays are recorded as candidate ray set A.

[0024] Specifically, the first preset angle is 60 degrees.

[0025] Specifically, the first preset distance is 3m.

[0026] In a third aspect, another embodiment of the present invention discloses a non-volatile memory having instructions stored thereon, which, when executed by a processor, are used to implement the above-mentioned indoor robot autonomous exploration and mapping method.

[0027] In a fourth aspect, another embodiment of the present invention discloses a robot, which includes a 2D single-line laser radar, a chassis, and the above-mentioned indoor robot autonomous exploration and mapping device.

[0028] The present invention automatically classifies the rays according to the range and angle of the rays obtained by the robot, that is, determines which areas can be explored, and uses a tree structure to save the directions that the robot needs to explore. Repeating the nodes of the tree structure can complete the exploration of the entire target area. It has efficient exploration capabilities and improves the full coverage rate. Furthermore, the present invention only needs to plan the path according to the direction of the rays. Its exploration path planning is simple and direct, and can also achieve better results, thereby improving the efficiency of autonomous exploration and scanning. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0030] Figure 1 This is a flow chart of an indoor robot autonomous exploration and mapping method provided by an embodiment of the present invention;

[0031] Figure 2 is a schematic diagram of an exploration direction tree structure provided by an embodiment of the present invention;

[0032] Figure 3 This is a schematic diagram of an indoor robot autonomous exploration and mapping device provided by an embodiment of the present invention;

[0033] Figure 4 It is a schematic diagram of an indoor robot autonomous exploration and mapping device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0035] Embodiment 1

[0036] refer to Figure 1 This embodiment discloses an indoor robot autonomous exploration and mapping method, which includes the following steps:

[0037] The robot of this embodiment is equipped with a 2D single-line laser radar with a field of view of 210 degrees. More specifically, the robot of this embodiment also includes a processing unit and a chassis, wherein the processing unit can receive instructions or control the chassis of the robot to walk autonomously according to the data of the 2D single-line laser radar. Those skilled in the art know that the robot of this embodiment also includes a power supply unit for providing power to the robot, and the specific power supply unit can be a lithium-ion battery, etc. In more general cases, this embodiment also includes other components for realizing the functions of the robot, which will not be repeated in this embodiment.

[0038] S1, obtain the laser radar scanning frame S obtained by the robot rotating one circle;

[0039] Specifically, in this embodiment, the robot is first placed in a target area to be mapped, such as a hotel or other area.

[0040] Specifically, the laser radar light source is set as the origin of the coordinate system, X points to the robot's forward direction, Y points to the robot's left direction, and Z points to the robot's upward direction to establish a three-dimensional coordinate system;

[0041] The robot of this embodiment can run a simultaneous localization and mapping SLAM (Simultaneous Localization and Mapping, SLAM) algorithm. The SLAM algorithm is used to solve the problem that the robot starts moving from an unknown position in an unknown environment, locates itself according to the position and map during the movement, and builds an incremental map based on its own positioning to achieve autonomous positioning and navigation of the robot.

[0042] The map of this embodiment uses a two-dimensional grid map; the specific robot's SLAM algorithm will generate a two-dimensional grid map. Those skilled in the art know that the robot can also use other types of maps, which are commonly used maps in the field, and this embodiment will not further introduce other maps.

[0043] Specifically, when the robot is placed in the target area, the robot can be controlled to rotate one circle to obtain a laser radar scanning frame S around the robot. This embodiment uses a 2D single-line laser radar with a field of view of 210 degrees, which cannot cover a range of 360 degrees, and it cannot rotate by itself. In order to obtain a 360-degree laser radar scanning frame around the robot, it is necessary to control the robot to rotate one circle. In another embodiment, a rotating laser radar can also be installed to control the laser radar to rotate one circle to obtain the laser radar scanning frame S. For example, the laser radar is installed on the top of the robot, and the laser radar itself can rotate, so there is no need to control the robot to rotate one circle, but only to control the laser radar to rotate one circle.

[0044] S2, traverse the scanning frame S, obtain all rays whose scanning distance exceeds the laser radar range, obtain the angles corresponding to the rays, and record the rays as a candidate ray set A;

[0045] Specifically, the laser radar has a range, and the rays it emits have an angle. This step obtains rays whose scanning distance exceeds the laser radar range. Rays whose scanning distance exceeds the laser radar range indicate that there are still areas that have not been explored. Further mapping is required for the areas where the rays whose scanning distance exceeds the laser radar range are located.

[0046] S3, classifying the candidate ray set A to obtain subsets A1, A2, ... Ai, wherein all rays in the subset Ai satisfy that the difference between the maximum ray angle and the minimum ray angle is greater than a first preset angle, and the angle between any two rays does not exceed the minimum resolution angle of the laser radar;

[0047] Specifically, before classifying the candidate ray set A, they may be sorted according to the angle sizes to form the ray set A.

[0048] Clustering the ray set A, where the set A1, A2, ... are classified from the set A, and the subset Ai must satisfy that the difference between the maximum and minimum ray angles is greater than 60 degrees, and the angle between any two rays does not exceed the minimum resolution angle of the laser radar; the minimum resolution angle of the laser radar is an inherent parameter of the laser radar. For example, a certain radar of SICK generally emits a ray every 0.33 degrees, and this 0.33 degrees is the minimum resolution angle of this radar of SICK;

[0049] max_angle(Ai)-min_angle(Ai)>60

[0050] The first preset angle in this embodiment is 60 degrees.

[0051] S4, obtaining the number of the subsets Ai and using the current posture of the robot as a node of the tree, wherein each subset in the subset Ai is used as a child node of the tree node, wherein each node represents a direction that the robot can explore; controlling the robot to explore along the tree nodes until the node N has no leaves; wherein the exploration process is to control the robot to move forward a preset distance in the direction of the leaves of the tree and repeat steps S1-S3;

[0052] S5, determining whether there is an unexplored leaf at the node N-1, and if there is an unexplored leaf direction, controlling the robot to go to the position of the node N-1 and continue exploring;

[0053] The number of subsets obtained from step S3 represents a direction that the robot can explore. The average angle in the subset is the robot's forward angle, but it is impossible to explore multiple directions at the same time. Figure 2 , where the nodes are represented by boxes, representing the current pose of the robot; the leaves are represented by circles, representing the direction the robot needs to move in the current pose. This embodiment uses a tree structure to save the exploration direction, where the current pose of the robot is the node of the tree, and the explorable directions are the leaves of the tree.

[0054] Assume that the robot has two forward directions A1 and A2 at the position of node 0. Then the robot will autonomously control and move forward 3 meters in the direction of A1. The current position of the robot is recorded as node 1. Continue to execute steps S1-S3 to explore the direction that the robot needs to continue to explore at the current position. Repeat this process until there are no more leaves at node N.

[0055] Step S4 indicates that the exploration scan of a branch of the tree is completed, then it is determined whether there is an unexplored leaf (that is, direction) at node N-1 (that is, the previous node). If there is an unexplored leaf direction, the autonomous control robot goes to the position of node N-1 and continues to explore.

[0056] S6, obtaining the map created by the robot using SLAM during the exploration process;

[0057] The above steps are repeated until all leaves on all nodes are explored. Of course, during this exploration process, laser SLAM mapping is always ongoing, thus forming a two-dimensional indoor grid map.

[0058] This embodiment automatically classifies the rays according to the range and angle of the rays obtained by the robot, that is, determines which areas can be explored, and uses a tree structure to save the directions that the robot needs to explore. Repeating the nodes of the tree structure can complete the exploration of the entire target area. It has efficient exploration capabilities and improves the full coverage rate. Furthermore, this embodiment only needs to plan the path according to the direction of the rays. Its exploration path planning is simple and direct, and can also achieve good results, thereby improving the efficiency of autonomous exploration and scanning.

[0059] Embodiment 2

[0060] refer to Figure 3 This embodiment discloses an indoor robot autonomous exploration and mapping device, which includes the following units:

[0061] A laser radar scanning frame acquisition unit, used to acquire a laser radar scanning frame S obtained by one rotation of the robot;

[0062] Specifically, in this embodiment, the robot is first placed in a target area to be mapped, such as a hotel or other area.

[0063] Specifically, the laser radar light source is set as the origin of the coordinate system, X points to the robot's forward direction, Y points to the robot's left direction, and Z points to the robot's upward direction to establish a three-dimensional coordinate system;

[0064] The robot of this embodiment can run a simultaneous localization and mapping SLAM (Simultaneous Localization and Mapping, SLAM) algorithm. The SLAM algorithm is used to solve the problem that the robot starts moving from an unknown position in an unknown environment, locates itself according to the position and map during the movement, and builds an incremental map based on its own positioning to achieve autonomous positioning and navigation of the robot.

[0065] The map of this embodiment uses a two-dimensional grid map; the specific robot's SLAM algorithm will generate a two-dimensional grid map. Those skilled in the art know that the robot can also use other types of maps, which are commonly used maps in the field, and this embodiment will not further introduce other maps.

[0066] Specifically, when the robot is placed in the target area, the robot can be controlled to rotate one circle to obtain a laser radar scanning frame S around the robot. This embodiment uses a 2D single-line laser radar with a field of view of 210 degrees, which cannot cover a range of 360 degrees, and it cannot rotate by itself. In order to obtain a 360-degree laser radar scanning frame around the robot, it is necessary to control the robot to rotate one circle. In another embodiment, a rotating laser radar can also be installed to control the laser radar to rotate one circle to obtain the laser radar scanning frame S. For example, the laser radar is installed on the top of the robot, and the laser radar itself can rotate, so there is no need to control the robot to rotate one circle, but only to control the laser radar to rotate one circle.

[0067] A candidate ray set acquisition unit, used for traversing the scanning frame S, acquiring all rays whose scanning distance exceeds the laser radar range, acquiring angles corresponding to the rays, and recording the rays as a candidate ray set A;

[0068] Specifically, the laser radar has a range, and the rays it emits have an angle. This step obtains rays whose scanning distance exceeds the laser radar range. Rays whose scanning distance exceeds the laser radar range indicate that there are still areas that have not been explored. Further mapping is required for the areas where the rays whose scanning distance exceeds the laser radar range are located.

[0069] A subset classification unit, used for classifying the candidate ray set A to obtain subsets A1, A2, ... Ai, wherein all rays of the subset Ai satisfy that the difference between the maximum and minimum ray angles is greater than a first preset angle, and the angle between any two rays does not exceed the minimum resolution angle of the laser radar;

[0070] Specifically, before classifying the candidate ray set A, they may be sorted according to the angle sizes to form the ray set A.

[0071] Clustering the ray set A, where the set A1, A2, ... are classified from the set A, and the subset Ai must satisfy that the difference between the maximum and minimum ray angles is greater than 60 degrees, and the angle between any two rays does not exceed the minimum resolution angle of the laser radar; the minimum resolution angle of the laser radar is an inherent parameter of the laser radar. For example, a certain radar of SICK generally emits a ray every 0.33 degrees, and this 0.33 degrees is the minimum resolution angle of this radar of SICK;

[0072] max_angle(Ai)-min_angle(Ai)>60;

[0073] The first preset angle in this embodiment is 60 degrees.

[0074] The first exploration unit is used to obtain the number of subsets Ai and use the current posture of the robot as a node of the tree, each subset in the subset Ai as a subnode of the tree node, wherein each node represents a direction that the robot can explore; control the robot to explore along the tree node until the node N has no leaves; wherein the exploration process is to control the robot to move forward a preset distance along the leaf direction of the tree and repeatedly execute the laser radar scanning frame acquisition unit, the candidate ray set acquisition unit, and the subset classification unit;

[0075] The second exploration unit is used to determine whether there is an unexplored leaf at the node N-1. If there is an unexplored leaf direction, the robot is controlled to go to the position of the node N-1 to continue exploring.

[0076] The number of subsets obtained from the subset classification unit represents a direction that the robot can explore. The average angle in the subset is the robot's forward angle, but it is impossible to explore multiple directions at the same time. Figure 2 , where the nodes are represented by boxes, representing the current pose of the robot; the leaves are represented by circles, representing the direction the robot needs to move in the current pose. This embodiment uses a tree structure to save the exploration direction, where the current pose of the robot is the node of the tree, and the explorable directions are the leaves of the tree.

[0077] Assume that the robot has two forward directions A1 and A2 at the position of node 0. Then the robot will autonomously control and move forward 3 meters in the direction of A1. The current robot position is recorded as node 1. The laser radar scanning frame acquisition unit, the candidate ray set acquisition unit, and the subset classification unit will continue to execute the direction that the robot needs to continue to explore at the current position. This process is repeated until no more leaves appear at node N.

[0078] The first exploration unit indicates that the exploration scan of a branch of the tree is completed, and then it is determined whether there is an unexplored leaf (that is, direction) at node N-1 (that is, the previous node). If there is an unexplored leaf direction, the autonomous control robot goes to the position of node N-1 and continues to explore;

[0079] A mapping unit is used to synchronously obtain the map created by the robot using SLAM during the exploration process;

[0080] The above steps are repeated until all leaves on all nodes are explored. Of course, during this exploration process, laser SLAM mapping is always ongoing, thus forming a two-dimensional indoor grid map.

[0081] This embodiment automatically classifies the rays according to the range and angle of the rays obtained by the robot, that is, determines which areas can be explored, and uses a tree structure to save the directions that the robot needs to explore. Repeating the nodes of the tree structure can complete the exploration of the entire target area. It has efficient exploration capabilities and improves the full coverage rate. Furthermore, this embodiment only needs to plan the path according to the direction of the rays. Its exploration path planning is simple and direct, and can also achieve good results, thereby improving the efficiency of autonomous exploration and scanning.

[0082] Embodiment 3

[0083] This embodiment discloses a robot, which includes a 2D single-line laser radar, a processing unit, a chassis, and a storage unit. The storage unit stores instructions, and when the instructions are executed, it is used to implement the indoor robot autonomous exploration and mapping method as described in Example 1.

[0084] Specifically, the robot of this embodiment also includes the indoor robot autonomous exploration and mapping device as described in the second embodiment.

[0085] Embodiment 4

[0086] refer to Figure 4 , Figure 4 : is a structural schematic diagram of an indoor robot autonomous exploration and mapping device of this embodiment. The indoor robot autonomous exploration and mapping device 20 of this embodiment includes a processor 21, a memory 22, and a computer program stored in the memory 22 and executable on the processor 21. When the processor 21 executes the computer program, the steps in the above method embodiment are implemented. Alternatively, when the processor 21 executes the computer program, the functions of each module / unit in the above device embodiments are implemented.

[0087] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory 22 and executed by the processor 21 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program in the indoor robot autonomous exploration and mapping device 20. For example, the computer program may be divided into the modules in Embodiment 2. For the specific functions of each module, please refer to the working process of the device described in the above embodiment, which will not be repeated here.

[0088] The indoor robot autonomous exploration and mapping device 20 may include, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will appreciate that the schematic diagram is merely an example of the indoor robot autonomous exploration and mapping device 20 and does not constitute a limitation on the indoor robot autonomous exploration and mapping device 20. The indoor robot autonomous exploration and mapping device 20 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the indoor robot autonomous exploration and mapping device 20 may also include input and output devices, network access devices, buses, and the like.

[0089] The processor 21 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor 21 is the control center of the indoor robot autonomous exploration and mapping device 20, and uses various interfaces and lines to connect various parts of the entire indoor robot autonomous exploration and mapping device 20.

[0090] The memory 22 can be used to store the computer program and / or module. The processor 21 realizes various functions of the indoor robot autonomous exploration and mapping device 20 by running or executing the computer program and / or module stored in the memory 22 and calling the data stored in the memory 22. The memory 22 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory 22 can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0091] Wherein, if the module / unit integrated in the indoor robot autonomous exploration and mapping device 20 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor 21, the steps of the above-mentioned method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media does not include electrical carrier signals and telecommunication signals.

[0092] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0093] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for autonomous exploration and mapping of indoor robots, comprising the following steps: S1, obtain the laser radar scanning frame S obtained by the robot rotating one circle; S2, traverse the scanning frame S, obtain all rays whose scanning distance exceeds the laser radar range, obtain the angles corresponding to the rays, and record the rays as a candidate ray set A; S3, classifying the candidate ray set A to obtain subsets A1, A2, ... Ai, wherein all rays in the subset Ai satisfy that the difference between the maximum ray angle and the minimum ray angle is greater than a first preset angle, and the angle between any two rays does not exceed the minimum resolution angle of the laser radar; S4, obtaining the number of the subsets Ai and using the current posture of the robot as a node of the tree, wherein each subset in the subset Ai is used as a child node of the tree node, wherein each node represents a direction that the robot can explore; controlling the robot to explore along the tree nodes until the node N has no leaves; wherein the exploration process is to control the robot to move forward a preset distance in the direction of the leaves of the tree and repeat steps S1-S3; S5, determining whether there is an unexplored leaf at the node N-1, and if there is an unexplored leaf direction, controlling the robot to go to the position of the node N-1 and continue exploring; S6, obtains the map created by the robot using SLAM during the exploration process.

2. According to the method of claim 1, in step S2, the rays are sorted according to the angle size and recorded as candidate ray set A. The method according to claim 2 , wherein the first preset angle is 60 degrees. The method according to claim 3 , wherein the preset distance is 3 m.

5. An indoor robot autonomous exploration and mapping device, comprising the following units: A laser radar scanning frame acquisition unit, used to acquire a laser radar scanning frame S obtained by one rotation of the robot; A candidate ray set acquisition unit, used for traversing the scanning frame S, acquiring all rays whose scanning distance exceeds the laser radar range, acquiring angles corresponding to the rays, and recording the rays as a candidate ray set A; A subset classification unit, used for classifying the candidate ray set A to obtain subsets A1, A2, ... Ai, wherein all rays of the subset Ai satisfy that the difference between the maximum ray angle and the minimum ray angle is greater than a first preset angle, and the angle between any two rays does not exceed the minimum resolution angle of the laser radar; The first exploration unit is used to obtain the number of subsets Ai and use the current posture of the robot as a node of the tree, each subset in the subset Ai as a subnode of the tree node, wherein each node represents a direction that the robot can explore; control the robot to explore along the tree node until the node N has no leaves; wherein the exploration process is to control the robot to move forward a preset distance along the leaf direction of the tree and repeatedly execute the laser radar scanning frame acquisition unit, the candidate ray set acquisition unit, and the subset classification unit; The second exploration unit is used to determine whether there is an unexplored leaf at the node N-1. If there is an unexplored leaf direction, the robot is controlled to go to the position of the node N-1 to continue exploring. The mapping unit is used to synchronously obtain the map built by the robot using SLAM during the exploration process.

6. The device according to claim 5, wherein in the candidate ray set acquisition unit, the rays are sorted according to the angle size and recorded as candidate ray set A. The device according to claim 6 , wherein the first preset angle is 60 degrees. The device according to claim 7 , wherein the preset distance is 3 m.

9. A non-volatile memory having instructions stored thereon, which, when executed by a processor, are used to implement the indoor robot autonomous exploration and mapping method as described in any one of claims 1 to 4.

10. A robot comprising a 2D single-line laser radar, a chassis, and an indoor robot autonomous exploration and mapping device as described in any one of claims 5 to 8.

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