Rescue positioning method and device for humanoid robot

Abstract

The embodiment of the invention provides a rescue positioning method and device for a humanoid robot, and belongs to the technical field of humanoid robots. The method comprises the following steps: performing map construction processing according to environment scanning information and a robot moving speed to generate a first grid map; determining at least three first specified positions in the first grid map according to the initial position information of the robot; the robot is controlled to move to each first designated position in sequence; determining a first distance estimation value according to the first rescue request information corresponding to each first specified position, and generating a first measurement circle according to the first specified position and the first distance estimation value; determining first rescue position information of the to-be-rescued object; real-time position information of the robot is obtained, and a first rescue path is generated according to the real-time position information of the robot, the first rescue position information and the first grid map. The method is used for achieving the effects of reducing the inaccurate rescue path caused by the positioning error and improving the rescue efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of humanoid robots, in particular to the technical field of humanoid robot control, and specifically to a rescue positioning method and device for a humanoid robot. Background Art

[0002] In today's society, various disasters and emergencies occur from time to time, and efficient and accurate rescue operations are crucial to protecting the safety of life and property. As a highly maneuverable and flexible intelligent device, humanoid robots have increasingly prominent application potential in the field of rescue.

[0003] However, the positioning and navigation of humanoid robots in rescue operations still face many challenges. Traditional positioning methods are often not accurate and reliable enough, and it is difficult to quickly and accurately determine the position of the humanoid robot and the position of the rescue target in a complex rescue environment. Therefore, when generating a rescue path, the rescue positioning method in the prior art has the problem of inaccurate positioning of the environment, resulting in deviations in the rescue path, that is, the accuracy of the rescue path is not high, which affects the rescue efficiency. Summary of the invention

[0004] The embodiments of the present application provide a rescue positioning method and device for a humanoid robot, so as to reduce the rescue path deviation caused by positioning error and improve the rescue efficiency.

[0005] In a first aspect, an embodiment of the present application provides a rescue positioning method of a humanoid robot, comprising:

[0006] Obtain environmental scanning information of the target area and the robot's moving speed;

[0007] Performing map construction processing according to the environment scanning information and the robot moving speed to generate a first grid map;

[0008] Acquire initial position information of the robot, and determine at least three first designated positions in the first grid map according to the initial position information of the robot;

[0009] Controlling the robot to move to each first designated position in sequence to receive first rescue request information corresponding to each first designated position, wherein the first rescue request information is a signal sent by the object to be rescued at the first designated position indicating that rescue is required;

[0010] Determine a first distance estimation value according to the first rescue request information corresponding to each first designated position, and generate a first measurement circle according to the first designated position and the first distance estimation value;

[0011] Determining first rescue position information of the object to be rescued according to all first measurement circles;

[0012] The real-time position information of the robot is obtained, and a first rescue path is generated according to the real-time position information of the robot, the first rescue position information and the first grid map.

[0013] In a possible implementation, the map construction processing is performed according to the environmental scanning information and the robot movement speed to generate a first grid map, including: performing object distance calculation processing according to the environmental scanning information to obtain distance data between the robot and each object in the target area; generating environmental point cloud data according to the distance data and the environmental scanning information, the environmental point cloud data including each scanning point data in the target area; determining a scene coefficient according to the robot movement speed, and determining rescue space data according to the environmental point cloud data; determining a target grid size according to the robot movement speed, the scene coefficient and the rescue space data, wherein the scene coefficient is positively correlated with the target grid size; discretizing the rescue space data according to the target grid size to obtain a plurality of grid units; mapping each scanning point data in the environmental point cloud data to a corresponding grid unit to generate a first grid map.

[0014] In a possible implementation manner, the rescue space data includes the rescue space area;

[0015] Accordingly, the step of determining the target grid size according to the robot moving speed, the scene coefficient and the rescue space data uses the calculation formula:

[0016]

[0017] Among them, k represents the scene coefficient, represents the target grid size, represents the rescue space area, Indicates the robot moving speed.

[0018] In a possible implementation, the rescue space data includes a rescue space volume;

[0019] Accordingly, the step of determining the target grid size according to the robot moving speed, the scene coefficient and the rescue space data uses the calculation formula:

[0020]

[0021] In the formula, k represents the scene coefficient, represents the target grid size, represents the rescue space volume, Indicates the robot moving speed.

[0022] In a possible implementation manner, the first rescue request information includes a signal strength value corresponding to each first designated location, a preset path loss index, and a preset reference signal strength value;

[0023] Accordingly, determining a first distance estimation value according to the first rescue request information corresponding to each first designated location includes:

[0024] Determine a first distance estimation value through distance estimation processing according to the signal strength value corresponding to each first designated position, the preset path loss index and the preset reference signal strength value;

[0025] The calculation formula used in the distance estimation process is:

[0026] RSSI(dBm)=A-10nlog 10 (z)

[0027] In the formula, Indicates the signal strength value corresponding to each first specified position, Indicates the preset reference signal strength value, represents a preset path loss index, and z represents a first distance estimation value.

[0028] In a possible implementation, determining the first rescue position information of the object to be rescued based on all the first measuring circles includes: determining first measuring circle intersection data based on all the first measuring circles, the first measuring circle intersection data including at least one intersection position information; when it is detected that there is one and only one intersection position information in the first measuring circle intersection data, determining the intersection position information as the first rescue position information of the object to be rescued; or when it is detected that there are two or more intersection position information in the first measuring circle intersection data, performing least squares fitting processing on the intersection data to obtain target intersection position information, and determining the target intersection position information as the first rescue position information of the object to be rescued.

[0029] In a possible implementation, generating a first rescue path according to the real-time position information of the robot, the first rescue position information and the first grid map includes: determining starting node information according to the real-time position information of the robot and the first grid map; determining target node information according to the first rescue position information and the first grid map; extracting layout structure information, channel width information and area access restriction information of the rescue space from the first grid map; determining multiple intermediate node information according to the layout structure information, channel width information and area access restriction information of the rescue space; performing path planning processing according to the starting node information, intermediate node information and target node information through a preset path planning algorithm to generate a rescue path.

[0030] In a possible implementation manner, the preset path planning algorithm is the Dijkstra algorithm or the A algorithm.

[0031] In a possible implementation, after generating the first rescue path according to the real-time position information of the robot, the first rescue position information and the first grid map, the method further includes: performing a rescue operation based on the first rescue path, and acquiring the current position information of the robot and the environment change scanning information in real time during the execution of the rescue operation; when it is detected that the environment change scanning information is different from the environment scanning information, performing map construction processing according to the environment change scanning information and the movement speed of the robot to generate a second grid map; determining at least three second designated positions in the second grid map according to the current position information of the robot; controlling the robot to move to each second designated position in turn to receive second rescue request information corresponding to each second designated position; determining a second distance estimation value according to the second rescue request information corresponding to each second designated position, and generating a second measuring circle according to the second designated position and the second distance estimation value; determining the second rescue position information of the object to be rescued according to all the second measuring circles; acquiring the real-time position information of the robot, and generating a second rescue path according to the real-time position information of the robot, the second rescue position information and the second grid map, and performing a rescue operation based on the second rescue path until the rescue is completed.

[0032] In a second aspect, an embodiment of the present application provides a rescue positioning device for a humanoid robot, comprising:

[0033] An acquisition module is used to obtain the environmental scanning information of the target area and the moving speed of the robot;

[0034] A map construction module, used for performing map construction processing according to the environment scanning information and the robot movement speed to generate a first grid map;

[0035] a position determination module, which obtains initial position information of the robot and determines at least three first designated positions in the first grid map according to the initial position information of the robot;

[0036] The position determination module is further used to control the robot to move to each first designated position in sequence to receive first rescue request information corresponding to each first designated position, wherein the first rescue request information is a signal sent by the object to be rescued at the first designated position indicating that rescue is required;

[0037] The position determination module is further used to determine a first distance estimation value according to the first rescue request information corresponding to each first designated position, and generate a first measurement circle according to the first designated position and the first distance estimation value;

[0038] The position determination module is further used to determine the first rescue position information of the object to be rescued according to all the first measurement circles;

[0039] The rescue positioning module is used to obtain the real-time position information of the robot and generate a first rescue path according to the real-time position information of the robot, the first rescue position information and the first grid map.

[0040] The embodiment of the present application provides a method and device for rescuing and positioning a humanoid robot. The method and device first generate a first grid map by performing a map construction process based on environmental scanning information and the robot's moving speed. Then, a plurality of first designated positions are determined in sequence, and corresponding first rescue request information is received at each first designated position. Then, based on each first designated position and its corresponding first rescue request information, a plurality of first measurement circles are determined, and the first rescue position information of the object to be rescued is determined based on all the first measurement circles. Finally, the real-time position information of the robot is obtained, and a first rescue path is generated based on the real-time position information of the robot, the first rescue position information and the first grid map. In this way, the first rescue position information of the object to be rescued is more accurate, and the generated first rescue path is more accurate, which reduces rescue errors caused by positioning errors and improves the accuracy and success rate of rescue. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] Figure 1 A schematic diagram of an application scenario of the rescue positioning method of a humanoid robot provided in this application;

[0043] Figure 2 A schematic diagram of the process flow of the rescue positioning method of the humanoid robot provided in this application;

[0044] Figure 3 A schematic diagram of the structure of the rescue positioning device of the humanoid robot provided in this application;

[0045] Figure 4 A schematic diagram of the electronic device provided for the application.

[0046] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0047] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0048] The inventors found that in the prior art, when a humanoid robot rescues an object to be rescued in a rescue area, due to the complexity and dynamics of the rescue environment, the traditional positioning methods such as radar positioning or direct positioning using a depth camera are often not accurate and reliable enough, and it is difficult to quickly and accurately determine the position of the humanoid robot and the position of the rescue target in a complex rescue environment. In addition, when generating a rescue path, the complexity and dynamics of the environment cannot be fully considered, resulting in the rescue path not being optimized enough, and the obtained rescue path is easily affected by obstacles or there is still a shorter rescue path. This affects the rescue efficiency and other issues.

[0049] In response to the above technical problems, the inventors proposed the following invention concept: use sensors to scan the environmental information of the rescue space to obtain scanning information, build a grid map based on the scanning information, and then after obtaining the rescue request signal, receive the signal strength value corresponding to the rescue request signal through multiple pre-set designated positions in the map grid. Then calculate the distance estimate, and then use each designated position as the center of the circle and the corresponding distance estimate as the radius to generate a measuring circle. The intersection of each measuring circle can be determined as the rescue position of the object to be rescued. Then use the path planning algorithm and the grid map to generate a rescue path, the rescue position is more accurately located, and the final rescue path is also shorter, thereby improving the rescue efficiency.

[0050] In this embodiment, the humanoid robot refers to a robot that has a human appearance, can imitate some human movements and behaviors, and can perform specific tasks. The grid map refers to a map that divides the rescue space into grid units. The current position refers to the current position of the humanoid robot in the grid map. The rescue request refers to a signal sent by the person to be rescued that requires rescue, including rescue-related information. The rescue location refers to the location of the specific place where the rescue request is sent in the grid map. The rescue path refers to the route planned from the current position of the humanoid robot to the rescue location.

[0051] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0052] Figure 1 A schematic diagram of an application scenario of the rescue positioning method of a humanoid robot provided in this application, such as Figure 1 As shown, the specific application scenarios of the present application include: a humanoid robot 101 and an object to be rescued 102, wherein a server and an environmental scanning device for collecting environmental scanning information in the rescue area, such as a radar sensor or a depth camera, are installed on the humanoid robot 101. The server can sequentially execute the relevant steps of the rescue positioning method of the humanoid robot according to the environmental scanning information, and finally obtain a rescue path. The object to be rescued 102 can be any object, waiting for the rescue positioning of the humanoid robot 101. Figure 1 Obstacle 1, Obstacle 2 and Obstacle 3 in the figure are obstacles located between the humanoid robot 101 and the object to be rescued 102.

[0053] It should be noted that Figure 1 The application scenario of the rescue positioning method of the humanoid robot shown only represents one application scenario of rescue positioning. The rescue positioning method of the humanoid robot proposed in this embodiment can also be applied to other application scenarios, which is not limited in this embodiment.

[0054] Figure 2 The flowchart of the rescue positioning method of the humanoid robot provided in this application is shown in FIG. The execution subject of the rescue positioning method of the humanoid robot may be Figure 1 The server in the humanoid robot 101 shown may also be other computer-related devices, chips, controllers or processors that can perform rescue positioning and data processing functions, and this embodiment does not limit this.

[0055] like Figure 2 As shown, the rescue positioning method of the humanoid robot:

[0056] S201: Obtain environmental scanning information of the target area and the robot moving speed.

[0057] In this embodiment, the target area may be the area where the robot and the object to be rescued are located.

[0058] In this embodiment, the environmental scanning information may be data obtained by scanning and photographing the rescue area by an environmental scanning device, wherein the environmental scanning device may be at least one of a laser radar, a camera, and an ultrasonic sensor. For example, a laser radar can calculate the distance to surrounding objects by emitting a laser beam and measuring the time of reflected light. It can quickly obtain a large amount of accurate distance data, form a point cloud map, and display the three-dimensional contour information of the surrounding environment. The camera uses the principle of optical imaging to capture images of the rescue space, and the shape, color and other visual features of the object can be extracted through image processing algorithms. Ultrasonic sensors measure distances based on the reflection time of sound waves by emitting and receiving ultrasonic waves, and are often used to detect obstacles at close range.

[0059] In this embodiment, the moving speed of the robot can be directly obtained by calling control data.

[0060] S202: Performing map construction processing according to the environment scanning information and the robot movement speed to generate a first grid map.

[0061] In this embodiment, the map construction process may be performed using grid map generation software. After the environment scanning information and the robot moving speed are input into the grid map generation software, the first grid map may be generated.

[0062] Specifically, in an optional embodiment of the present application, step S202 includes:

[0063] S202a: Perform object distance calculation processing based on the environment scanning information to obtain distance data between the robot and each object in the target area.

[0064] In this embodiment, the object distance calculation process can be a process of distance calculation using the sending and receiving time of the environment scanning information. For example, the ultrasonic sensor calculates the distance value between the robot and each object as distance data by transmitting and receiving the reflection time and the speed of the ultrasonic wave.

[0065] S202b: Generate environmental point cloud data according to the distance data and the environmental scanning information, where the environmental point cloud data includes data of each scanning point in the target area.

[0066] In this embodiment, the environmental point cloud data may be a set of vectors in a three-dimensional coordinate system. The scanned data is recorded in the form of points, each of which contains three-dimensional coordinates and may carry other information about the attributes of the point, such as color.

[0067] Take the laser radar as an example. It is usually installed at a specific position of the robot and can rotate 360 ​​degrees to scan the surrounding environment. When scanning the rescue space, the laser radar continuously emits laser beams, and the lasers are reflected back when they encounter the surface of the object. The sensor records the emission and reception time of each laser beam and calculates the distance between the object and the robot based on the speed of light and the time difference. As the laser radar rotates, a large amount of distance data is collected to form the environmental point cloud data around the robot, that is, the environmental scanning information of the target area.

[0068] S202c: Determine the scene coefficient according to the robot's moving speed, and determine the rescue space data according to the environmental point cloud data.

[0069] In this embodiment, if the robot moves faster, the grid size of the grid map is required to be larger, so that the robot can cross multiple grids for path planning in a short time, reduce computing power, and improve rescue positioning efficiency. If the robot moves slower, the grid size of the grid map is required to be smaller to improve map accuracy. For example, in a small indoor rescue scene, the space area is small and the robot speed is relatively slow, the scene coefficient is 0.5, and a smaller grid size is calculated; while in a large outdoor open space, the space area is large and the robot speed is fast, the scene coefficient is 1, and a larger grid size is obtained.

[0070] In this embodiment, the rescue space data may be the space area or space volume of the rescue space.

[0071] S202d: Determine the target grid size according to the robot moving speed, the scene coefficient and the rescue space data, wherein the scene coefficient is positively correlated with the target grid size.

[0072] In this embodiment, the target grid size can be determined by inputting the robot movement speed, scene coefficient and rescue space data into a preset grid size calculation formula and then calculating it.

[0073] Specifically, in an optional embodiment of the present application, the rescue space data includes the rescue space area; accordingly, the calculation formula used in step S202d is:

[0074]

[0075] Among them, k represents the scene coefficient, represents the target grid size, represents the rescue space area, Indicates the robot moving speed.

[0076] In another optional embodiment of the present application, the rescue space data includes the rescue space volume; accordingly, the calculation formula used in step S202d is:

[0077]

[0078] In the formula, k represents the scene coefficient, represents the target grid size, represents the rescue space volume, Indicates the robot moving speed.

[0079] In this embodiment, d is a dimensionless value. When the calculation formula in step S202d is used to calculate the target grid size, the dimensions of the rescue space volume V, the rescue space area S, and the robot moving speed v are ignored, and only the corresponding values ​​are taken.

[0080] S202e: Discretize the rescue space data according to the target grid size to obtain a plurality of grid units.

[0081] In this embodiment, the discretization process refers to dividing the entire rescue space into grid units of the same size based on the determined target grid size.

[0082] S202f: Map each scanning point data in the environmental point cloud data to a corresponding grid unit to generate a first grid map.

[0083] In this embodiment, when each scan point data in the environmental point cloud data is mapped to the corresponding grid unit, if there are multiple measurement points in a grid unit, the attributes of the grid unit can be determined according to the distribution of the points, such as whether it is an obstacle, whether it is passable, etc. For example: the three-dimensional coordinates of point A, point B and point C in the environmental point cloud data are all scan points, and all correspond to the i-th grid unit in the first grid map, then the scan information corresponding to point A, point B and point C needs to be mapped to the i-th grid unit.

[0084] S203: Acquire initial position information of the robot, and determine at least three first designated positions in the first grid map according to the initial position information of the robot.

[0085] In this embodiment, the initial position information may be the position information of the robot when executing step S203, which is collected by the self-contained positioning device. The process of obtaining the coordinates of the first designated position after the robot is controlled to move a fixed distance in other specific directions from the initial position as the starting point in the grid map by a pre-specified robot movement strategy according to the initial position information of the robot. For example: the position reached after moving 3 meters along the 3 o'clock direction is determined as a first designated position, the position after moving 3 meters along the 6 o'clock direction is determined as a first designated position, and then the initial position is determined as a designated position.

[0086] In this embodiment, the first designated positions are at least three, in order to provide more data support for subsequent rescue positioning and improve positioning accuracy. When there is a positioning dispute, it is convenient to obtain a more accurate result by fitting through the least square method.

[0087] S204: Control the robot to move to each first designated position in sequence to receive first rescue request information corresponding to each first designated position, wherein the first rescue request information is a signal received at the first designated position and sent by the object to be rescued to indicate the need for rescue.

[0088] In this embodiment, the first rescue request information may be a signal of needing rescue sent by the object to be rescued and received at the first designated position, and the signal includes rescue-related information. In this embodiment, when moving to each first designated position in sequence, the order of movement may be selected by the robot autonomously, and may be random or may be moved according to a pre-set movement rule. This embodiment does not limit this.

[0089] S205: Determine a first distance estimation value according to the first rescue request information corresponding to each first designated position, and generate a first measurement circle according to the first designated position and the first distance estimation value.

[0090] In this embodiment, the first distance estimation value may be determined by calculating the reception time of the first rescue request information and the signal propagation speed, or may be calculated based on the corresponding relationship between the strength of the first rescue request information and the distance. This embodiment is not limited here.

[0091] In an optional embodiment of the present application, the first rescue request information includes a signal strength value corresponding to each first designated location, a preset path loss index, and a preset reference signal strength value; accordingly, step S205 specifically includes: determining a first distance estimation value through distance estimation processing according to the signal strength value corresponding to each first designated location, the preset path loss index, and the preset reference signal strength value;

[0092] The calculation formula used for distance estimation is:

[0093] RSSI(dBm)=A-10nlog 10 (z)

[0094] In the formula, Indicates the signal strength value corresponding to each first specified position, Indicates the preset reference signal strength value, represents a preset path loss index, and z represents a first distance estimation value.

[0095] In this embodiment, generating a first measuring circle according to the first specified position and the first distance estimation value in step S205 can be a process of drawing a circle in the first grid map with the first specified position as the center and the first distance estimation value corresponding to the first specified position as the radius using pre-stored mapping software.

[0096] In this embodiment, when radio waves propagate in free space, their energy will decay according to a certain rule as the propagation distance increases. Therefore, the distance estimation value can be determined based on the signal strength value. The distance calculation formula in the embodiment of the present application takes into account the impact of environmental factors on signal propagation. Through the analysis and fitting of a large amount of actual measurement data, the relationship between signal strength and distance is finally obtained.

[0097] S206: Determine first rescue position information of the object to be rescued according to all first measurement circles.

[0098] In this embodiment, the arcs of all first measurement circles may have at least one intersection point. In this case, the common intersection point of all first measurement circles may be determined as the first rescue position information of the object to be rescued.

[0099] In an optional embodiment of the present application, step S206 includes the following steps:

[0100] S206a: Determine first measurement circle intersection data according to all first measurement circles, where the first measurement circle intersection data includes at least one intersection position information.

[0101] S206b: When it is detected that there is only one intersection position information in the first measurement circle intersection data, the intersection position information is determined as the first rescue position information of the object to be rescued.

[0102] S206c: Or when it is detected that there are two or more intersection position information in the first measurement circle intersection data, a least squares fitting process is performed based on the intersection data to obtain target intersection position information, and the target intersection position information is determined as the first rescue position information of the object to be rescued.

[0103] In this embodiment, due to the distance measuring equipment, there may be a deviation in the distance estimation value. When the first measurement circle cannot be completely intersected or there are multiple intersections due to the deviation in the distance estimation value, the least squares fitting method can be used at this time, and all intersections are regarded as data points. An optimal position point is fitted by the least squares method, that is, a point is found so that the sum of the squares of its distances to all intersections is the smallest. This point is considered to be the most likely rescue position. It can be seen that the rescue position obtained in this embodiment is more accurate and reliable than that obtained by the existing rescue positioning method, and the subsequent rescue path generation result is also more accurate, so as to improve the rescue efficiency.

[0104] S207: Acquire the real-time position information of the robot, and generate a first rescue path according to the real-time position information of the robot, the first rescue position information and the first grid map.

[0105] In this embodiment, the real-time position information may be the specific position information of the robot when executing step S207. At least one rescue path can be planned in the first grid map based on the real-time position information of the robot and the first rescue position information. Then, the robot can be controlled to perform rescue on the rescue object according to the first rescue path.

[0106] In an optional embodiment of the present application, step S207 includes:

[0107] S207a: Determine the starting node information according to the real-time position information of the robot and the first grid map.

[0108] In this embodiment, the starting node may be a coordinate point corresponding to the real-time position information of the robot in the first grid map, namely the starting node. The coordinate point and the corresponding scanning point information may be determined as the starting node information.

[0109] S207b: Determine target node information according to the first rescue position information and the first grid map.

[0110] In this embodiment, the target node may be a coordinate point corresponding to the first rescue position information in the first grid map, namely, the target node. The coordinate point and the corresponding scanning point information may be determined as the target node information.

[0111] S207c: Extracting the layout structure information, channel width information and regional access restriction information of the rescue space from the grid map.

[0112] S207d: Determine multiple intermediate node information based on the layout structure information, channel width information and area access restriction information of the rescue space.

[0113] In this embodiment, the intermediate node information can be determined according to the layout structure of each area of ​​the rescue space, and the connection point or hub position between different areas can be found, wherein the intermediate node refers to the coordinate point that the robot can pass from the starting node to the target node. For example, in the hospital layout, the intersection of corridors, elevator entrances, etc. are key locations connecting different departments and floors, which can be used as intermediate nodes. In addition, for some areas with special functions or attributes, such as the storage area boundaries in large warehouses, the entrances and exits of refuge places, etc., their boundary points can be used as intermediate nodes in path planning. The intermediate nodes can be determined according to the width information of the channel, such as the positions at certain intervals or the turning points of the channel, etc., to ensure that the rescue path can make full use of the wide channel to improve the traffic efficiency. In addition, for areas with restricted access, such as dangerous chemical storage areas, collapse risk areas, etc., their boundary points can be used as intermediate nodes to mark the range that the path needs to avoid, so that the rescue path bypasses these dangerous or prohibited areas.

[0114] S207e: Perform path planning processing according to the starting node information, the intermediate node information and the target node information through a preset path planning algorithm to generate a first rescue path.

[0115] In an optional embodiment of the present application, the preset path planning algorithm is the Dijkstra algorithm or the A algorithm.

[0116] When the path planning algorithm is the Dijkstra algorithm, the path planning by the Dijkstra algorithm includes a distance update phase, a node selection phase and a path backtracking phase.

[0117] The calculation formula for the distance update phase is:

[0118]

[0119] in, Represents the path from the starting node to one of the intermediate nodes The current shortest distance estimate of Indicates that from one of the intermediate nodes To another intermediate node The edge weights of Represents the distance from the starting node to another intermediate node in the grid map The current shortest distance estimate of It is determined based on the layout structure information, channel width information and regional access restriction information of the rescue space.

[0120] The calculation formula for the node selection phase is:

[0121]

[0122] in, represents the set of unvisited intermediate nodes, represents the next unvisited intermediate node to be selected in each iteration, is the set of unvisited intermediate nodes Any intermediate node in Represents an intermediate node from the starting node to the grid map The current shortest distance estimate for .

[0123] The path backtracking stage refers to the process of backtracking from the target node to the intermediate node to generate the final first rescue path. This embodiment will not be described in detail here.

[0124] In this embodiment, when the Dijkstra algorithm is used to calculate the planned path, the distance update phase is the critical first step. Its core purpose is to continuously update the estimated value of the shortest distance from the starting node, that is, the starting node corresponding to the robot's position, to each other intermediate node in the first grid map. The first grid map is a network composed of many nodes, such as channel intersections, key locations, etc., and the edges connecting these nodes. In the early stage of the calculation, it is only known that the distance from the starting node to itself is 0, and the distance to other intermediate nodes is temporarily set to a larger value. As the algorithm progresses, when it is found that there is a new, shorter path to reach a certain intermediate node, the shortest distance estimate can be further updated according to the formula.

[0125] When Dijkstra algorithm is used for path planning, assume represents the current shortest distance estimate from the robot's starting position to another intermediate node in the first grid map, Indicates that from one of the intermediate nodes To another intermediate node The weight of the edge can be determined according to the actual situation. For example, if the channel length is considered as the main factor, It's the channel The actual length of the channel; if the width of the channel is also considered, a coefficient can be comprehensively evaluated to represent the weight. arrive When the path may be better, update The formula is:

[0126] ;

[0127] in, Represents the distance from the starting node to one of the intermediate nodes in the first grid map The current shortest distance estimate of Indicates that from one of the intermediate nodes To another intermediate node The edge weights of Represents the distance from the start node to one of the intermediate nodes in the first grid map The current shortest distance estimate of the current record. The meaning of this formula is to compare the current record from the starting node to another intermediate node The shortest distance and through one of the intermediate nodes Then to another intermediate node The distance (i.e. ), if the latter is smaller, update to a smaller value.

[0128] When the target node is finally determined to be reachable through the previous distance update and node selection phases, the path backtracking phase begins. The task of this phase is to infer the specific planned path from the starting node to the target node based on the previously recorded connection relationship and the shortest distance between the nodes, that is, to determine which intermediate nodes the robot must pass through in order to reach the rescue location as quickly as possible. Indicates the intermediate node The predecessor intermediate node (used to record the path). Then, we construct the node from the starting node by backtracking. To the target node Path. That is, from the target node Start by continuously adding the predecessor nodes of the current node to the path Until backtracking to the starting node , thus obtaining the complete shortest rescue path from the starting node to the target node.

[0129] In addition, when dealing with more complex rescue scenarios, such as considering both the path length and the flow of people in the channel to determine the weight , assuming that the channel The length is , the flow of people is , the weight formula can be defined as ,in and It is a coefficient determined based on actual conditions and is used to balance the impact of length and passenger flow on path selection.

[0130] In this embodiment, the path planning algorithm selected is the Dijkstra algorithm or the A The reference basis of the algorithm can be to set a judgment condition, for example: when the number of grids in the first grid map is greater than 100, select A By setting the judgment conditions, the robot can more quickly select the most appropriate path planning algorithm in different rescue scenarios, reduce the deviation of the rescue path caused by the wrong algorithm selection, and obtain a more accurate rescue path.

[0131] In this embodiment, when the path planning algorithm is A An example of the path planning process during the algorithm is as follows:

[0132] Suppose we want to obtain the first rescue path from point a to point e in the first grid map. At this time, we expand the nodes according to the calculation method of f(n)=g(n)+h(n) (actual cost + heuristic estimated cost), where f(n) represents the estimated total cost from the starting point a to the intermediate node n, g(n) represents the actual cost from the starting point a to the intermediate node n, and h(n) represents the heuristic estimated cost from the intermediate node n to the target node e.

[0133] Step e1: Start point a (f=0+5.656≈5.656) is added to the open list.

[0134] Step e2: Expand a: neighbor node b (f=5+4.472≈9.472) and neighbor node c (f=3+4.472≈7.472) are added to the open list.

[0135] Step e3: Select the node c with the minimum f value (f≈7.472).

[0136] Repeat steps e2 and e3 until a path with the minimum total cost is found, such as a→c→d→e.

[0137] From the above content, we can know that A The algorithm can ensure improved search efficiency under better conditions, and is especially suitable for path planning in large-scale or complex environments.

[0138] Based on the above embodiment, in an optional embodiment of the present application, after step S207, the following steps are further included:

[0139] A: Perform a rescue operation based on the first rescue path, and obtain the robot's current position information and environmental change scanning information in real time during the rescue operation;

[0140] B: When it is detected that the environment change scanning information is different from the environment scanning information, a map construction process is performed according to the environment change scanning information and the robot moving speed to generate a second grid map;

[0141] C: determining at least three second designated positions in the second grid map according to the current position information of the robot;

[0142] D: controlling the robot to move to each second designated position in sequence to receive second rescue request information corresponding to each second designated position;

[0143] E: determining a second distance estimation value according to the second rescue request information corresponding to each second designated position, and generating a second measurement circle according to the second designated position and the second distance estimation value;

[0144] F: Determine the second rescue position information of the object to be rescued according to all the second measurement circles;

[0145] G: Obtain the real-time position information of the robot, and generate a second rescue path according to the real-time position information of the robot, the second rescue position information and the second grid map, and perform rescue operations based on the second rescue path until the rescue is completed.

[0146] In this embodiment, performing a rescue operation based on the first rescue path may be a process in which the robot's server controls the robot's mobile parts to move to the location of the object to be rescued within the target area along the rescue path to implement the rescue. However, in this process, there may be changes in environmental information. Therefore, during the rescue process, the robot's sensor needs to scan the environment in real time and compare it with the previous environmental scanning information. If the comparison result shows that the environment has changed, such as the movement of obstacles, or the appearance of new obstacles on the rescue path. Then, it is necessary to update the rescue path such as steps B to G. The specific implementation principles of steps B to G are similar to those of steps S202 to S207, so this embodiment will not be repeated here.

[0147] In summary, the rescue positioning method of a humanoid robot provided in the embodiment of the present application first generates a first grid map by performing a map construction process based on environmental scanning information and the robot's moving speed. Then, a plurality of first designated positions are determined in sequence, and the corresponding first rescue request information is received at each first designated position. Then, based on each first designated position and its corresponding first rescue request information, a plurality of first measurement circles are determined, and the first rescue position information of the object to be rescued is determined based on all the first measurement circles. Finally, the real-time position information of the robot is obtained, and the first rescue path is generated based on the real-time position information of the robot, the first rescue position information and the first grid map. In this way, the first rescue position information of the rescue object obtained is more accurate, and the generated first rescue path is more accurate. Combined with the robot's moving speed, the robot can reach the actual position of the object to be rescued more quickly to implement rescue, thereby improving the rescue efficiency.

[0148] At the same time, by updating the second grid map in real time when performing rescue operations based on the first rescue path, more accurate second rescue location information and second rescue path can be obtained to cope with more complex and changeable rescue environments and improve the rescue success rate and rescue efficiency in complex rescue scenarios.

[0149] Figure 3 A schematic structural diagram of the rescue positioning device of the humanoid robot provided in this application.

[0150] like Figure 3 As shown, the rescue positioning device of the humanoid robot provided in this embodiment includes: an acquisition module 31 , a map construction module 32 , a position determination module 33 and a rescue positioning module 34 .

[0151] The acquisition module 31 is used to acquire the environment scanning information of the target area and the moving speed of the robot.

[0152] A map construction module 32, configured to perform map construction processing according to the environment scanning information and the robot moving speed, and generate a first grid map;

[0153] A position determination module 33 is configured to obtain initial position information of the robot and determine at least three first designated positions in the grid map according to the initial position information of the robot;

[0154] The position determination module 33 is further used to control the robot to move to each first designated position in sequence to receive first rescue request information corresponding to each first designated position, wherein the first rescue request information is a signal sent by the object to be rescued and indicating the need for rescue and received at the first designated position;

[0155] The position determination module 33 is further used to determine a first distance estimation value according to the first rescue request information corresponding to each first designated position, and to generate a first measurement circle according to the first designated position and the first distance estimation value;

[0156] The position determination module 33 is further used to determine the first rescue position information of the object to be rescued according to all the first measurement circles;

[0157] The rescue positioning module 34 is used to obtain the real-time position information of the robot, and generate a first rescue path according to the real-time position information of the robot, the first rescue position information and the first grid map.

[0158] In one possible implementation, the map construction module 32 is specifically used to: calculate the distance of objects based on the environmental scanning information to obtain the distance data between the robot and each object in the target area; generate environmental point cloud data based on the distance data and the environmental scanning information, and the environmental point cloud data includes each scanning point data in the target area; determine the scene coefficient based on the robot movement speed, and determine the rescue space data based on the environmental point cloud data; determine the target grid size based on the robot movement speed, the scene coefficient and the rescue space data, wherein the scene coefficient is positively correlated with the target grid size; discretize the rescue space data according to the target grid size to obtain multiple grid units; map each scanning point data in the environmental point cloud data to the corresponding grid unit to generate a first grid map.

[0159] In a possible implementation, the rescue space data includes the rescue space area; accordingly, the map building module 32 is used to determine the target grid size according to the robot moving speed, the scene coefficient and the rescue space data. The calculation formula used is:

[0160]

[0161] Among them, k represents the scene coefficient, represents the target grid size, represents the rescue space area, Indicates the robot moving speed.

[0162] In a possible implementation, the rescue space data includes the rescue space volume; accordingly, the map building module 32 is specifically used to: determine the target grid size according to the robot moving speed, the scene coefficient and the rescue space data using the calculation formula:

[0163]

[0164] In the formula, k represents the scene coefficient, represents the target grid size, represents the rescue space volume, Indicates the robot moving speed.

[0165] In a possible implementation, the first rescue request information includes a signal strength value corresponding to each first designated location, a preset path loss index, and a preset reference signal strength value. Accordingly, the location determination module 33 is specifically configured to determine a first distance estimation value according to the first rescue request information corresponding to each first designated location, including:

[0166] Determine a first distance estimation value through distance estimation processing according to the signal strength value corresponding to each first designated position, the preset path loss index and the preset reference signal strength value;

[0167] The calculation formula used for distance estimation is:

[0168] RSSI(dBm)=A-10nlog 10 (z)

[0169] In the formula, Indicates the signal strength value corresponding to each first specified position, Indicates the preset reference signal strength value, represents a preset path loss index, and z represents a first distance estimation value.

[0170] The rescue positioning device for a robot provided in this embodiment can execute the method provided in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be described in detail here.

[0171] In one possible implementation, the position determination module 33 is specifically used to: determine the first measurement circle intersection data based on all the first measurement circles, the first measurement circle intersection data including at least one intersection position information; when it is detected that there is only one intersection position information in the first measurement circle intersection data, the intersection position information is determined as the first rescue position information of the object to be rescued; or when it is detected that there are two or more intersection position information in the first measurement circle intersection data, perform least squares fitting processing on the intersection data to obtain target intersection position information, and determine the target intersection position information as the first rescue position information of the object to be rescued.

[0172] In one possible implementation, the rescue positioning module 34 is specifically used to: determine the starting node information based on the real-time position information of the robot and the first grid map; determine the target node information based on the first rescue position information and the first grid map; extract the layout structure information, channel width information and area access restriction information of the rescue space from the first grid map; determine multiple intermediate node information based on the layout structure information, channel width information and area access restriction information of the rescue space; perform path planning processing through a preset path planning algorithm based on the starting node information, intermediate node information and target node information to produce a rescue path.

[0173] In one possible implementation, the rescue positioning module 34 is used to generate a rescue path based on the robot's real-time position information, the rescue position information and the grid map. The rescue positioning module 34 is also used to perform a rescue operation based on the first rescue path, and obtain the robot's current position information and environmental change scanning information in real time during the rescue operation; the map construction module 32 is also used to: when it is detected that the environmental change scanning information is different from the environmental scanning information, perform map construction processing according to the environmental change scanning information and the robot's moving speed to generate a second grid map; the rescue positioning module 34 is also used to: determine at least three second designated positions in the second grid map according to the robot's current position information; control the robot to move to each second designated position in turn to receive the second rescue request information corresponding to each second designated position; determine a second distance estimate according to the second rescue request information corresponding to each second designated position, and generate a second measuring circle according to the second designated position and the second distance estimate; determine the second rescue position information of the object to be rescued according to all the second measuring circles. The rescue positioning module 34 is also used to: obtain the real-time position information of the robot, and generate a second rescue path according to the real-time position information of the robot, the second rescue position information and the second grid map, and perform rescue operations based on the second rescue path until the rescue is completed.

[0174] The posture estimation device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be repeated here.

[0175] Figure 4 This is a schematic diagram of the structure of the electronic device provided in this application. Figure 4 As shown, the electronic device provided in this embodiment includes: at least one processor 401 and a memory 402. Optionally, the device further includes a communication component 403. The processor 401, the memory 402 and the communication component 403 are connected via a bus 404.

[0176] In a specific implementation process, at least one processor 401 executes the computer-executable instructions stored in the memory 402, so that at least one processor 401 executes the above method.

[0177] The specific implementation process of the processor 401 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0178] An embodiment of the present application also provides a humanoid robot, including a robot body, an environment scanning device disposed on the robot body, and an electronic device as described in the above embodiment disposed in the robot body.

[0179] In this embodiment, both being arranged on the robot body and being arranged inside the robot body can be realized by means of hardware connection structures such as bolt connection, threaded connection, etc.

[0180] An embodiment of the present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0181] An embodiment of the present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0182] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0183] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0184] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0185] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0186] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0187] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0188] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0189] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0190] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0191] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0192] If the function 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 technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0193] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0194] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A rescue positioning method for a humanoid robot, characterized in that: include: Obtain environmental scanning information of the target area and the robot's moving speed; Performing map construction processing according to the environment scanning information and the robot moving speed to generate a first grid map; Acquire initial position information of the robot, and determine at least three first designated positions in the first grid map according to the initial position information of the robot; Controlling the robot to move to each first designated position in sequence to receive first rescue request information corresponding to each first designated position, wherein the first rescue request information is a signal sent by the object to be rescued at the first designated position indicating that rescue is required; Determine a first distance estimation value according to the first rescue request information corresponding to each first designated position, and generate a first measurement circle according to the first designated position and the first distance estimation value; Determining first rescue position information of the object to be rescued according to all first measurement circles; The real-time position information of the robot is obtained, and a first rescue path is generated according to the real-time position information of the robot, the first rescue position information and the first grid map.

2. The method according to claim 1, characterized in that The step of performing map construction processing according to the environment scanning information and the robot moving speed to generate a first grid map includes: Perform object distance calculation processing based on the environment scanning information to obtain distance data between the robot and each object in the target area; Generate environmental point cloud data according to the distance data and the environmental scanning information, wherein the environmental point cloud data includes data of each scanning point in the target area; Determine a scene coefficient according to the movement speed of the robot, and determine rescue space data according to the environmental point cloud data; Determining a target grid size according to the robot moving speed, a scene coefficient and the rescue space data, wherein the scene coefficient is positively correlated with the target grid size; Discretize the rescue space data according to the target grid size to obtain a plurality of grid units; Each scanning point data in the environmental point cloud data is mapped to a corresponding grid unit to generate a first grid map.

3. The method according to claim 2, characterized in that The rescue space data includes the rescue space area; Accordingly, the step of determining the target grid size according to the robot moving speed, the scene coefficient and the rescue space data uses the calculation formula: ， Among them, k represents the scene coefficient, represents the target grid size, represents the rescue space area, Indicates the robot moving speed.

4. The method according to claim 2, characterized in that: The rescue space data includes the rescue space volume; Accordingly, the step of determining the target grid size according to the robot moving speed, the scene coefficient and the rescue space data uses the calculation formula: ， In the formula, k represents the scene coefficient, represents the target grid size, represents the rescue space volume, Indicates the robot moving speed.

5. The method according to claim 1, characterized in that: The first rescue request information includes a signal strength value corresponding to each first designated location, a preset path loss index, and a preset reference signal strength value; Accordingly, determining a first distance estimation value according to the first rescue request information corresponding to each first designated location includes: Determine a first distance estimation value through distance estimation processing according to the signal strength value corresponding to each first designated position, the preset path loss index and the preset reference signal strength value; The calculation formula used in the distance estimation process is: RSSI(dBm)=A-10nlog 10 (from) In the formula, Indicates the signal strength value corresponding to each first specified position, Indicates the preset reference signal strength value, represents a preset path loss index, and z represents a first distance estimation value.

6. The method according to claim 1, characterized in that The step of determining the first rescue position information of the object to be rescued according to all the first measurement circles includes: Determine first measurement circle intersection data according to all first measurement circles, wherein the first measurement circle intersection data includes at least one intersection position information; When it is detected that there is only one intersection position information in the first measurement circle intersection data, the intersection position information is determined as the first rescue position information of the object to be rescued; Or when it is detected that there are two or more intersection position information in the first measurement circle intersection data, least squares fitting processing is performed based on the intersection data to obtain target intersection position information, and the target intersection position information is determined as the first rescue position information of the object to be rescued.

7. The method according to claim 1, characterized in that The step of generating a first rescue path according to the real-time position information of the robot, the first rescue position information and the first grid map includes: Determine starting node information according to the real-time position information of the robot and the first grid map; Determining target node information according to the first rescue location information and the first grid map; Extracting the layout structure information, channel width information and regional access restriction information of the rescue space from the first grid map; Determine multiple intermediate node information according to the layout structure information, channel width information and regional access restriction information of the rescue space; A path planning process is performed according to the starting node information, the intermediate node information and the target node information through a preset path planning algorithm to generate a first rescue path.

8. The method according to claim 7, characterized in that The preset path planning algorithm is Dijkstra algorithm or A algorithm.

9. The method according to any one of claims 1 to 8, characterized in that After generating a first rescue path according to the real-time position information of the robot, the first rescue position information and the first grid map, the method further includes: Performing a rescue operation based on the first rescue path, and acquiring the robot's current position information and environmental change scanning information in real time during the rescue operation; When it is detected that the environment change scanning information is different from the environment scanning information, a map construction process is performed according to the environment change scanning information and the movement speed of the robot to generate a second grid map; Determining at least three second designated locations in the second grid map according to the current location information of the robot; Controlling the robot to move to each second designated position in sequence to receive second rescue request information corresponding to each second designated position; Determining a second distance estimation value according to the second rescue request information corresponding to each second designated position, and generating a second measurement circle according to the second designated position and the second distance estimation value; Determining second rescue position information of the object to be rescued according to all second measurement circles; The real-time position information of the robot is obtained, and a second rescue path is generated according to the real-time position information of the robot, the second rescue position information and the second grid map, and a rescue operation is performed based on the second rescue path until the rescue is completed.

10. A rescue positioning device for a humanoid robot, characterized in that: include: An acquisition module is used to obtain the environmental scanning information of the target area and the robot moving speed; A map construction module, used for performing map construction processing according to the environment scanning information and the robot movement speed to generate a first grid map; a position determination module, which obtains initial position information of the robot and determines at least three first designated positions in the first grid map according to the initial position information of the robot; The position determination module is further used to control the robot to move to each first designated position in sequence to receive first rescue request information corresponding to each first designated position, wherein the first rescue request information is a signal sent by the object to be rescued at the first designated position indicating that rescue is required; The position determination module is further used to determine a first distance estimation value according to the first rescue request information corresponding to each first designated position, and generate a first measurement circle according to the first designated position and the first distance estimation value; The position determination module is further used to determine the first rescue position information of the object to be rescued according to all the first measurement circles; The rescue positioning module is used to obtain the real-time position information of the robot and generate a first rescue path according to the real-time position information of the robot, the first rescue position information and the first grid map.

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