A TEB-based path planning method, device and equipment

Abstract

Embodiments of the present application disclose a TEB-based path planning method, device and equipment, wherein the method comprises the following steps: determining a planning starting point of a local planning path; selecting a plurality of splicing points; generating a first part of the local planning path according to the planning starting point and the plurality of splicing points; intercepting a segment of a global planning line after a corresponding point of the last splicing point as a reference planning line; generating a second part of the local planning path according to a preset trajectory constraint function and the reference planning line; and splicing the first part and the second part of the local planning path to form the local planning path. Through the present application, the problem of left and right swinging of a robot when encountering an obstacle can be solved, and the smoothness and stability of path planning are improved.

Description

Technical Field

[0001] This invention relates to the field of robotics, and in particular to a path planning method, apparatus, and device based on TEB. Background Technology

[0002] Robotic vacuum cleaners have emerged with the development of artificial intelligence. Their emergence has greatly liberated people from tedious cleaning work. Sweeping is time-saving, labor-saving, and more efficient. The entire process does not require human control, reducing the burden on people. People can use the saved time to do more meaningful things.

[0003] Local path planning algorithms are a crucial component of robotic vacuum cleaner technology, significantly impacting the robot's operational efficiency and obstacle avoidance capabilities. TEB (Timed Elastic Compute Service) is one such algorithm.

[0004] The Time-Based Elastic Band (TEB) is an evolution of the classic Elastic Band algorithm. While the classic Elastic Band only considers shortest path and obstacle avoidance, the existing TEB adds dynamic constraints related to motion time, such as robot velocity, acceleration, and kinematic constraints. Within a weighted multi-objective convex optimization framework, a time-based quadratic optimization problem is established. This objective function depends only on consecutively adjacent intermediate states. A sparse matrix of relevant constraints is established, and the problem is solved using the G2O (General Graphic Optimization) sparse system solver framework.

[0005] Current robotic vacuum cleaners use local path planning algorithms that can cause their trajectories to sway frequently when encountering obstacles, potentially leading to the robot falling over. Summary of the Invention

[0006] The present invention aims to provide a path planning method, apparatus and device based on TEB to solve the problem that robots often sway left and right when encountering obstacles in the prior art.

[0007] To address the aforementioned technical problems, the embodiments of the present invention provide the following technical solutions:

[0008] According to one aspect of the present invention, a TEB-based path planning method is provided, the method comprising:

[0009] Determine the starting point of the local planning path;

[0010] Based on the planning starting point, select several splicing points from the global planning path or the previous local planning path;

[0011] generating a first part of the local planning path according to the planning start point and the plurality of stitching points;

[0012] finding a corresponding point of the last stitching point on the global planning path, and cutting a segment of the global planning line after the corresponding point as a reference planning line, wherein the corresponding point is a trajectory point found on the global planning path or the local planning path according to a reference point pose and closest to the reference point pose;

[0013] generating a second part of the local planning path according to a preset trajectory constraint function and the reference planning line;

[0014] stitching the first part and the second part of the local planning path to form the local planning path.

[0015] Optionally, the determining of the planning start point of the local planning path comprises:

[0016] taking the current robot pose or a corresponding point of the current robot pose on the last local planning path as the planning start point of the local planning path.

[0017] Optionally, the taking of the current robot pose or the corresponding point of the current robot pose on the last local planning path as the planning start point of the local planning path comprises:

[0018] determining whether the robot is running for the first time;

[0019] if yes, taking the current robot pose as the planning start point of the local planning path;

[0020] if no, comparing the current robot pose with a corresponding point of the current robot pose on the last local planning path, if the difference is less than a threshold, taking the corresponding point of the current robot pose on the last local planning path as the planning start point of the local planning path; otherwise, taking the current robot pose as the planning start point of the local planning path.

[0021] Optionally, the method further comprises:

[0022] selecting a plurality of sample points adjacent to the reference point from the global planning path or the local planning path;

[0023] obtaining a fitted curve equation group of the plurality of sample points by using a polynomial fitting method;

[0024] calculating a point closest to the robot pose of the reference point in time or distance as the corresponding point of the reference point according to the curve equation group.

[0025] Optionally, the preset trajectory constraint function comprises a trajectory similarity constraint function, and the trajectory similarity constraint function is configured to make the generated trajectory similar to a heading direction of a reference planning line.

[0026] Optionally, the selecting the plurality of stitching points from the global planning path or the last local planning path according to the planning start point comprises:

[0027] When the robot is in a first run, the plurality of stitching points are selected from the global planning path according to the planning start point;

[0028] When the robot is in a non-first run, the plurality of stitching points are selected from the last local planning path according to the planning start point.

[0029] Optionally, the selecting the plurality of stitching points from the global planning path or the last local planning path according to the planning start point further comprises:

[0030] When the robot is in a first run, a sample point closest to a corresponding point of the planning start point is found on the global planning path, the sample point is taken as a first stitching point, and a plurality of sample points after the sample point are selected as remaining stitching points from the global planning path according to a preset number of stitching points;

[0031] When the robot is in a non-first run, a sample point closest to a corresponding point of the planning start point is found on the last local planning path, the sample point is taken as a first stitching point, and a plurality of sample points after the sample point are selected as remaining stitching points from the last local planning path according to a preset number of stitching points.

[0032] According to another aspect of the present application, there is provided a device for path planning based on TEB, comprising:

[0033] a start point determination module configured to determine a planning start point of a current local planning path;

[0034] a stitching point selection module configured to select a plurality of stitching points from a global planning path or a last local planning path according to the planning start point;

[0035] a first planning line generation module configured to generate a first part of the current local planning path according to the planning start point and the plurality of stitching points;

[0036] a reference planning line intercepting module configured to find a corresponding point of a last stitching point on the global planning path, and intercept a segment of the global planning line after the corresponding point as a reference planning line, wherein the corresponding point is a trajectory point found on the global planning path or the local planning path according to a reference point pose and closest to the reference point pose.

[0037] a second planning line generation module configured to generate a second part of the current local planning path according to a preset trajectory constraint function and the reference planning line;

[0038] a trajectory splicing module configured to splice the first part and the second part of the current local planning path to form the current local planning path.

[0039] According to still another aspect of the present application, there is provided an electronic device comprising a memory, a processor and a computer program stored in the memory and executable by the processor, wherein the processor implements the steps of the TEB-based path planning method according to any one of the preceding aspects when executing the computer program.

[0040] According to still another aspect of the present application, there is provided a computer readable storage medium storing a computer program, wherein the processor implements the steps of the TEB-based path planning method according to any one of the preceding aspects when executing the computer program.

[0041] The present application has the following advantages: different from the prior art, in the present application, a planning starting point is first determined, then a splicing point is selected based on the last local planning path to form a first part of the current local planning path; then a reference planning line is cut from the global planning path based on the last splicing point, a second part of the current local planning path is generated according to a preset trajectory constraint function (new trajectory similarity constraint) and the reference planning line, and finally the first part and the second part of the current local planning path are spliced to form a final local planning path. The local planning path generated by the present application not only takes into account the last local planning path and the global planning path, but also improves the smoothness of path planning; and the new trajectory similarity constraint generates a heading change of a part of points through the current robot pose, so that the robot does not frequently swing left and right when facing obstacles, thereby improving the stability of path planning. BRIEF DESCRIPTION OF DRAWINGS

[0042] One or more embodiments are illustrated by way of example in the figures that are part of this disclosure and which are illustrative, but not restrictive, of the present embodiments, wherein elements having the same reference number designates like elements throughout the various figures, and the figures are not necessarily to scale. The figures illustrate various embodiments of the present application and, together with the description, serve to explain the principles of the present application.

[0043] Figure 1 is a flowchart of an optional TEB-based path planning method provided by the first embodiment of the present application;

[0044] Figure 2 is a schematic diagram of a robot position and a corresponding point position provided by the first embodiment of the present application;

[0045] Figure 3is a schematic diagram of a local planning path provided by the embodiment one of the present application;

[0046] Figure 4 is a work flow diagram of a mobile robot realized by the method provided by the embodiment one of the present application;

[0047] Figure 5 is a structural schematic diagram of an optional TEB-based path planning device provided by the embodiment two of the present application.

[0048] Figure 6 is a structural schematic diagram of an optional electronic device provided by the embodiment three of the present application. DETAILED DESCRIPTION

[0049] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0050] In addition, the technical features involved in each of the embodiments of the present application described below can be combined with each other as long as there is no conflict.

[0051] Embodiment one

[0052] According to the embodiments of the present application, a TEB-based path planning method is provided, which is an improvement on the existing TEB-based local path planning method and can cope with the problem that a sweeping robot is prone to swing left and right in a complex indoor and outdoor environment. It should be noted that the steps shown in the flowchart can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that here.

[0053] Please refer to Figure 1 , Figure 1 is a flowchart of an optional TEB-based path planning method provided by the embodiment one of the present application, the method is a local path planning method and can be applied to various mobile robots, including sweeping robots, medical robots, etc. The method comprises:

[0054] Step S101, determining the planning starting point of the local planning path this time.

[0055] In one embodiment, the current robot pose or its corresponding point on the previous local planning path is used as the starting point for the current local planning path. Specifically, it is determined whether this is the robot's first run; if so, the current robot pose is used as the starting point for the current local planning path; if not, the current robot pose is compared with its corresponding point on the previous local planning path. If the difference is less than a threshold, the corresponding point on the previous local planning path is used as the starting point for the current local planning path; otherwise, the current robot pose is used as the starting point for the current local planning path. Figure 3 As shown, the current robot pose is used as the starting point for local path planning.

[0056] A corresponding point refers to the trajectory point on the global or local planning path that is closest to the pose of the reference point. Corresponding points can be calculated using methods such as polynomial fitting (e.g., linear interpolation or 5th-order polynomial fitting considering smoothness) or Bézier curves. Specifically, first, several sample points adjacent to the reference point are selected from the global or local planning path; then, a set of curve equations fitted to these sample points is obtained using a polynomial fitting method; finally, the point closest to the robot pose of the reference point in time or distance is calculated based on the set of curve equations and taken as the corresponding point of the reference point.

[0057] like Figure 2 As shown, the reference point is the current robot pose, points AB are two sampling points adjacent to the current robot pose on the previous local planning path, and point O is the corresponding point found after fitting a quadratic polynomial. Specifically, the following quadratic curve equation system is first constructed:

[0058] fx = a0 + a1*t + a2*t 2

[0059] fy = b0 + b1*t + b2*t 2

[0060] Substitute the pose information of sampling points A and B on the previous local planning path, A(x1,y1,θ1) and B(x2,y2,θ2), into the above curve equation system and solve for the parameters a0,a1,a2,b0,b1 and b2 of the above curve equation system to obtain the fitted curve equation system.

[0061] x1 = a0 + a1*t0 + a2*t0 2

[0062] x2 = a0 + a1*t1 + a2*t1 2

[0063] y1 = b0 + b1*t0 + b2*t02

[0064] x2 = b0 + b1*t1 + b2*t1 2

[0065] tanθ1=(b1+ b2*t0*2) / (a1*t0+ a2*t0 2 )

[0066] tanθ2=(b1+ b2*t1*2) / (a1*t0+ a2*t1 2 )

[0067] Furthermore, based on the fitted curve equations, the point closest to the current robot pose in time or distance is calculated, and this point is taken as the corresponding point of the current robot pose. The coordinates and heading information of this corresponding point can be obtained from the aforementioned curve equations.

[0068] Step S102: Select several splicing points from the global planning path or the previous local planning path based on the planning starting point.

[0069] Specifically, when the robot is running for the first time, several splicing points are selected from the global planning path based on the planning start point; when the robot is not running for the first time, several splicing points are selected from the previous local planning path based on the planning start point.

[0070] The following describes the selection process of splicing points in detail, taking the robot's non-first run as an example. When the robot is running for the first time, the sample point closest to the planning start point is first found on the previous local planning path. This sample point is then selected as the first splicing point. Then, according to the preset number of splicing points, several sample points after the sample point on the previous local planning path are selected as the remaining splicing points.

[0071] like Figure 3 As shown, assuming the preset number of stitching points is 3, and the planning starting point is the current robot pose, the method in step S101 can be used to find the corresponding point O on the previous local planning path. The two sampling points adjacent to point O are A and B. Assuming point B is closer to point O, the first stitching point is point B. Then, two sampling points C and D after point B on the previous local planning path are selected as the remaining stitching points. In summary, all stitching points selected using the above method are B, C, and D.

[0072] Step S103: Generate the first part of the local planning path based on the planning starting point and the plurality of splicing points.

[0073] Specifically, the pose information of the planning starting point and several splicing points is obtained, and the pose information of the planning starting point and several splicing points is used as the first part of the local planning path.

[0074] Step S104: Find the corresponding point of the last splicing point on the global planning path, and extract a segment of the global planning line after the corresponding point as a reference planning line.

[0075] The corresponding point of the last splicing point refers to the trajectory point on the global planning path that is closest to the pose of the last splicing point, which can be obtained by calculating the corresponding point in step S101.

[0076] Figure 3 In the process, if the last splicing point is point D, then point D is used as the starting point for splicing the first and second parts of the local planning path. The corresponding point of point D on the global planning path is found as point w. A segment of the global planning line after point w is extracted as a reference planning line, for example, FGH is extracted as the reference planning line. The length of the extracted segment can be determined based on the preset local path planning length. Specifically, it can be obtained by subtracting the length of the first part of the current local planning path from the preset local planning path length.

[0077] Step S105: Generate the second part of the local planning path based on the preset trajectory constraint function and the reference planning line.

[0078] In this embodiment of the invention, to ensure that the robot does not frequently sway its trajectory left and right when facing obstacles, a trajectory similarity constraint is added to the existing motion constraints, time constraints, and key point constraints. The trajectory similarity constraint function is represented by the heading changes (essentially curvature changes) of a subset of points generated so that the generated trajectory is similar to the heading of the reference planning line. Optionally, the sum of the squared errors between the heading of the point that moved the corresponding distance and the previous heading is taken; for example, similarity detection is performed using n points after the splicing point.

[0079] similal_cost = .

[0080] like Figure 3 In the process, the second part {F', G', H'} of the local planning path is generated based on the preset trajectory constraint function and the reference planning line FGH.

[0081] Step S106: Combine the first and second parts of the local planning path to form the current local planning path.

[0082] like Figure 3As shown, the first part of the local planning path this time is composed of the planning starting point {current robot pose} and the splicing points {B, C, D}, and the second part of the local planning path this time {F', G', H'} is obtained by splicing the two parts, and the local planning path this time is formed, specifically: {current robot pose, B, C, D, F', G', H'}.

[0083] As shown in Figure 4 , Figure 4 As shown in the working flowchart of the mobile robot realized by the method provided by the embodiment one of the present application, the part shown in the dashed box in the figure is the process link newly added or modified by the present application on the basis of the prior art, and specifically:

[0084] Step 1: initialize the robot.

[0085] Step 2: construct or obtain a global path planning to obtain a global path point set.

[0086] Step 3: confirm a planning starting point and select splicing points according to a preset number of splicing points based on the global path point set, and the planning starting point and the splicing points constitute the first part of the local planning path.

[0087] Step 4: input the determined planning starting point and splicing point information into a hypergraph, and map a preset trajectory constraint function to the hypergraph, optimize the hypergraph, and generate the second part of the local planning path. Specifically, the preset trajectory constraint function includes vertex constraint, obstacle constraint, key point constraint, speed constraint, acceleration constraint, time optimization constraint, shortest path constraint, kinematics constraint and trajectory similarity constraint. Among them, the trajectory similarity constraint is a newly added constraint in the present application, which can be expressed by the change of the heading direction (in essence, the change of the curvature) of the current generated part of points, and can ensure that the robot will not frequently swing left and right when facing obstacles.

[0088] Step 5: splice the first part and the second part of the local planning path to form a new local planning path.

[0089] Step 6: generate a control instruction based on the new local planning path to control the robot to move.

[0090] Step 7: the robot interacts with the environment.

[0091] Step 8: determine whether the robot has reached the target position, if yes, end; if not, re-initialize the robot and return to step 3.

[0092] The path planning method based on TEB provided in this invention first determines the starting point of the planning, then selects splicing points based on the previous local planning path to form the first part of the current local planning path; then, based on the last splicing point, a reference planning line is extracted from the global planning path, and the second part of the current local planning path is generated according to the preset trajectory constraint function (with added trajectory similarity constraints) and the reference planning line; finally, the first and second parts of the current local planning path are spliced ​​together to form the final local planning path. The local planning path generated by this invention not only takes into account both the previous local planning path and the global planning path, improving the smoothness of path planning, but also, the newly added trajectory similarity constraints generate heading changes at some points through the current robot pose, ensuring that the robot does not frequently sway left and right when facing obstacles, thus improving the stability of path planning.

[0093] Example 2

[0094] According to embodiments of the present invention, a path planning device based on TEB is provided, such as... Figure 5 The diagram shows a schematic of an optional TEB-based path planning device provided in Embodiment 2 of the present invention. The TEB-based path planning device 500 includes a starting point determination module 502, a splicing point selection module 504, a first planning line generation module 506, a reference planning line extraction module 508, a second planning line generation module 510, and a trajectory splicing module 512.

[0095] The starting point determination module 502 is used to determine the starting point of the local planning path for this operation.

[0096] The splicing point selection module 504 is used to select several splicing points from the global planning path or the previous local planning path based on the planning starting point;

[0097] The first planning line generation module 506 is used to generate the first part of the local planning path based on the planning starting point and the plurality of splicing points;

[0098] The reference planning line interception module 508 is used to find the corresponding point of the last splicing point on the global planning path and intercept a segment of the global planning line after the corresponding point as the reference planning line. The corresponding point is the trajectory point that is closest to the pose of the reference point on the global planning path or local planning path according to the pose of the reference point.

[0099] The second planning line generation module 510 is used to generate the second part of the local planning path for this time according to the preset trajectory constraint function and the reference planning line;

[0100] The trajectory splicing module 512 is configured to combine the first part and the second part of the local planning path to form the local planning path.

[0101] The device can perform the embodiment one Figures 1 to 4 The TEB-based path planning method has the corresponding function modules and beneficial effects, and the technical details not described in detail in the embodiment can be referred to the embodiment one Figures 1 to 4 The TEB-based path planning method is provided.

[0102] Embodiment three

[0103] According to the embodiment of the application, an electronic device is provided, such as Figure 6 As shown in the figure, the electronic device provided in the embodiment three can include a processor 601, a communication interface 602, a memory 603 and a communication bus 604, wherein the processor 601, the communication interface 602 and the memory 603 can communicate with each other through the communication bus 604. The processor 601 can call the logical instructions in the memory 603 to execute the TEB-based path planning method, which includes determining a planning starting point of a local planning path; selecting a plurality of splicing points from a global planning path or a last local planning path according to the planning starting point; generating a first part of the local planning path according to the planning starting point and the plurality of splicing points; selecting a last splicing point in the plurality of splicing points as a splicing starting point, finding a corresponding point of the splicing starting point on the global planning path, and cutting a segment of the global planning line after the corresponding point of the splicing starting point as a reference planning line; generating a second part of the local planning path according to a preset trajectory constraint function and the reference planning line; and splicing the first part and the second part of the local planning path to form the local planning path.

[0104] In addition, the logical instructions in the memory 603 can be implemented in the form of a software function unit and sold or used as an independent product, and can be stored in several computer readable storage media. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a plurality of instructions to make a computer device (which can be a personal computer, a server or a network device, etc.) execute the embodiment one Figures 1 to 4All or part of the steps of the method. And the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and various storage program codes can be stored in the medium.

[0105] The product can execute the TEB-based path planning method in any of embodiments one Figures 1 to 4 Any of the TEB-based path planning methods has the corresponding functional modules and beneficial effects of the method, and the technical details not described in detail in the embodiment can refer to the TEB-based path planning method provided in embodiment one Figures 1 to 4 The TEB-based path planning method is provided.

[0106] Embodiment four

[0107] According to the embodiment of the application, a computer readable storage medium is provided, which is of the type described in embodiment three, and the computer readable storage medium stores a computer program, when the computer program is executed by a processor, the processor executes the steps of the TEB-based path planning method described in embodiment one.

[0108] The product can execute the TEB-based path planning method in any of embodiments one, and has the corresponding functional modules and beneficial effects of the method, and the technical details not described in detail in the embodiment can refer to the TEB-based path planning method provided in embodiment one.

[0109] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by means of software plus a general hardware platform, and of course can also be implemented by hardware. Based on such understanding, the above technical solutions essentially or say the part that contributes to the related art can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including a number of instructions to execute the method described in each embodiment or some part of the embodiment by a computer device (which can be a personal computer, server, or network device, etc.).

[0110] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, but not limited to them; under the idea of the present application, the technical features of the above examples or different examples can also be combined, the steps can be implemented in any order, and there are many other changes of different aspects of the present application as described above, which are not provided in details for simplicity; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacement to part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A path planning method based on a time-elastic band (TEB), characterized in that, The method includes: Determine the starting point of the local planning path; When the robot is running for the first time, several splicing points are selected from the global planning path based on the planning starting point. When the robot is not running for the first time, several splicing points are selected from the previous local planning path based on the planning starting point. The first part of the local planning path is generated based on the planning starting point and the several splicing points; Find the corresponding point of the last splicing point on the global planning path, and extract a segment of the global planning line after the corresponding point as the reference planning line. The corresponding point refers to the trajectory point on the global planning path or the local planning path that is closest to the pose of the reference point. The second part of the local planning path is generated based on the preset trajectory constraint function and the reference planning line. The preset trajectory constraint function includes a trajectory similarity constraint function, which is used to make the generated trajectory similar to the heading of the reference planning line. The first and second parts of the local planning path are combined to form the local planning path. The starting point for determining the local planning path includes: Determine if this is the robot's first run; If so, the current robot pose will be used as the starting point for this local path planning. If not, compare the current robot pose with its corresponding point on the previous local planning path. If the difference is less than the threshold, use the corresponding point of the current robot pose on the previous local planning path as the planning starting point of the current local planning path; otherwise, use the current robot pose as the planning starting point of the current local planning path. The step of selecting several splicing points from the global planning path or the previous local planning path based on the planning starting point includes: When the robot is running for the first time, it finds the sample point closest to the corresponding point of the planning start point on the global planning path, uses the sample point as the first splicing point, and selects several sample points after the sample point on the global planning path as the remaining splicing points according to the preset number of splicing points. When the robot is not running for the first time, it finds the sample point closest to the planning start point on the previous local planning path, uses the sample point as the first splicing point, and selects several sample points after the sample point on the previous local planning path as the remaining splicing points according to the preset number of splicing points.

2. The method according to claim 1, characterized in that, The method further includes: Select several sample points adjacent to the reference point from the global planning path or the local planning path; The system of curve equations fitted to the sample points is obtained by using a polynomial fitting method. The point that is closest to the robot pose of the reference point in time or distance is calculated based on the curve equations and used as the corresponding point of the reference point.

3. A path planning device based on TEB, characterized in that, include: The starting point determination module is used to determine the starting point of the local planning path. The splicing point selection module is used to select several splicing points from the global planning path based on the planning start point when the robot is running for the first time, and to select several splicing points from the previous local planning path based on the planning start point when the robot is not running for the first time. The first planning line generation module is used to generate the first part of the local planning path based on the planning starting point and the several splicing points; The reference planning line interception module is used to find the corresponding point of the last splicing point on the global planning path and intercept a segment of the global planning line after the corresponding point as the reference planning line. The corresponding point is the trajectory point that is closest to the pose of the reference point on the global planning path or local planning path, based on the pose of the reference point. The second planning line generation module is used to generate the second part of the local planning path based on the preset trajectory constraint function and the reference planning line. The preset trajectory constraint function includes a trajectory similarity constraint function, which is used to make the generated trajectory similar to the heading of the reference planning line. The trajectory stitching module is used to merge the first and second parts of the local planning path to form the current local planning path. The starting point for determining the local planning path includes: Determine if this is the robot's first run; If so, the current robot pose will be used as the starting point for this local path planning. If not, compare the current robot pose with its corresponding point on the previous local planning path. If the difference is less than the threshold, use the corresponding point of the current robot pose on the previous local planning path as the planning starting point of the current local planning path; otherwise, use the current robot pose as the planning starting point of the current local planning path. The step of selecting several splicing points from the global planning path or the previous local planning path based on the planning starting point includes: When the robot is running for the first time, it finds the sample point closest to the corresponding point of the planning start point on the global planning path, uses the sample point as the first splicing point, and selects several sample points after the sample point on the global planning path as the remaining splicing points according to the preset number of splicing points. When the robot is not running for the first time, it finds the sample point closest to the planning start point on the previous local planning path, uses the sample point as the first splicing point, and selects several sample points after the sample point on the previous local planning path as the remaining splicing points according to the preset number of splicing points.

4. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and running thereon, characterized in that, When the processor executes the program, it implements the steps of the path planning method based on the time elastic band (TEB) as described in claim 1 or 2.

5. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the path planning method based on a time-elastic band (TEB) as described in claim 1 or 2.

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