Local path planning method, device and equipment of reactor pool decontamination robot

Abstract

The invention is suitable for the technical field of robots, and provides a local path planning method, device and equipment for a reactor pool decontamination robot, and the method comprises the steps: determining a first motion path according to the environmental data of the bottom of a reactor pool; in the process of starting to navigate the reactor pool decontamination robot according to the first motion path, performing real-time local path planning on the first motion path to obtain a local path planning result; the local path planning at least comprises performing multiple smooth constraints on the first motion path, the multiple smooth constraints are used for limiting the distance of each path point in the first motion path and the turning radius of the first motion path, and adjusting the first motion path by using a local path planning result to obtain a second motion path. According to the invention, the accuracy of path planning of the reactor pool decontamination robot can be improved.

Description

Technical Field

[0001] The present application belongs to the field of robotics technology, and in particular, relates to a local path planning method, device, electronic device and computer-readable storage medium for a reactor pool decontamination robot. Background Art

[0002] During the operation of nuclear power plants, various dirt will be generated at the bottom of the reactor pool, such as suspended solids and radioactive substances deposited at the bottom of the reactor pool due to the circulation of cooling water. These dirt will generate radiation, affecting the operating efficiency and service life of nuclear power equipment and the health of workers.

[0003] At present, in order to improve the safety and efficiency of reactor pool bottom decontamination, the reactor pool decontamination robot can be used for cleaning. For example, the navigation algorithm is used to plan the motion path of the reactor pool decontamination robot to complete the pool bottom decontamination. However, since the bottom of the reactor pool includes complex and special terrain structures and pipeline obstacles, the navigation algorithm does not consider the optimization of path smoothness, resulting in inaccurate path planning. Summary of the invention

[0004] The embodiments of the present application provide a local path planning method, system, device and electronic equipment for a reactor pool decontamination robot, which can improve the accuracy of the path planning of the reactor pool decontamination robot.

[0005] In a first aspect, an embodiment of the present application provides a local path planning method for a reactor pool decontamination robot, comprising:

[0006] Determine a first motion path according to environmental data at the bottom of the reactor pool; wherein the first motion path is a path from a preset starting point to a preset end point, and the first motion path includes a plurality of path points;

[0007] In the process of navigating the reactor pool decontamination robot from the preset starting point along the first motion path, real-time local path planning is performed on the first motion path to obtain a local path planning result; the local path planning at least includes performing multiple smooth constraints on the first motion path, and the multiple smooth constraints are used to limit the distance between each path point in the first motion path and the turning radius of the first motion path;

[0008] The first motion path is adjusted using the local path planning result to obtain a second motion path, and the reactor pool decontamination robot is navigated according to the second motion path until the reactor pool decontamination robot reaches the preset end point.

[0009] In a second aspect, an embodiment of the present application provides a local path planning device for a reactor pool decontamination robot, comprising:

[0010] A first motion path determination module, used to determine a first motion path according to environmental data of the bottom of the reactor pool; wherein the first motion path is a path from a preset starting point to a preset end point, and the first motion path includes a plurality of path points;

[0011] A local path planning module, used for performing real-time local path planning on the first motion path during the process of the reactor pool decontamination robot navigating from the preset starting point along the first motion path to obtain a local path planning result; the local path planning at least includes performing multiple smooth constraints on the first motion path, and the multiple smooth constraints are used to limit the distance between each path point in the first motion path and the turning radius of the first motion path;

[0012] The second motion path determination module is used to adjust the first motion path using the local path planning result to obtain a second motion path, and navigate the reactor pool decontamination robot according to the second motion path until the reactor pool decontamination robot reaches the preset end point.

[0013] In a third aspect, an embodiment of the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the local path planning method for the reactor pool decontamination robot described in the first aspect are implemented.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the local path planning method for the reactor pool decontamination robot described in the first aspect above are implemented.

[0015] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on an electronic device, the electronic device executes the local path planning method for the reactor pool decontamination robot as described in any one of the first aspects above.

[0016] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0017] In the embodiment of the present application, the accuracy of the reactor pool decontamination robot path planning can be improved by adjusting the first motion path according to the local path planning result. Specifically, after determining the first motion path according to the environmental map at the bottom of the reactor pool, the first motion path is subjected to real-time local path planning to obtain the local path planning result. Since the local path planning at least includes multiple smooth constraints on the first motion path, and the multiple smooth constraints are used to limit the distance between each path point in the first motion path and the turning radius of the first motion path, it means that in the process of the reactor pool decontamination robot navigating from a preset starting point to a preset end point, the distance between each path point in the first motion path and the turning radius of the first motion path can be adjusted in real time through the local path planning result, thereby improving the smoothness of the first motion path and obtaining a second motion path with stronger path smoothness. Therefore, the accuracy of the path planning of the nuclear power plant reactor pool decontamination robot can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 It is a flow chart of a local path planning method of a reactor pool decontamination robot provided in one embodiment of the present application;

[0020] Figure 2 It is a flowchart of the navigation process of the reactor pool decontamination robot provided in one embodiment of the present application;

[0021] Figure 3 It is a structural schematic diagram of a local path planning device of a reactor pool decontamination robot provided in an embodiment of the present application;

[0022] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0024] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0025] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0026] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0027] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0028] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0029] The bottom of the reactor pool of a nuclear power plant is a special experimental scene and needs to be cleaned frequently to ensure the safe operation of the nuclear power plant. In order to reduce the radiation dose of dirt on the bottom of the pool to personnel and improve the decontamination efficiency, the cleaning work of the bottom of the reactor pool is mainly completed by remotely controlling the reactor pool decontamination robot instead of manual work.

[0030] At present, the path planning of the reactor pool decontamination robot is mainly carried out through navigation algorithms (such as Dijkstra algorithm or A* algorithm, etc.), so that the reactor pool decontamination robot can move from the starting point to the target point (such as the end point). However, in the reactor pool bottom environment, the following problems will arise when using the above navigation algorithm for path planning: 1. The bottom of the reactor pool includes complex and special terrain structures and pipeline obstacles, which require the decontamination robot to maintain precise and stable movement, but the traditional navigation algorithm lacks constraints on jitter and sharp turns when considering obstacle avoidance problems, resulting in poor path smoothness, which may cause the reactor pool decontamination robot to collide and cause accidents in the reactor pool environment. 2. Temporary dynamic obstacles (such as staff, moving test equipment, etc.) may appear at the bottom of the reactor pool. When performing obstacle avoidance planning in a dynamic environment, the traditional navigation algorithm cannot be adjusted in a timely and accurate manner. For example, the Dijkstra algorithm is a graph-based shortest path search. Although it can find the optimal path, it needs to recalculate the entire path in a dynamic environment, which is usually not efficient enough. The A* algorithm is a heuristic search algorithm. Although it can deal with temporary obstacles, it is difficult to make timely obstacle avoidance plans for moving targets.

[0031] Therefore, the above method will lead to inaccurate path planning of the reactor pool decontamination robot, thereby affecting the safety and efficiency of the cleaning work at the bottom of the reactor pool.

[0032] In order to improve the accuracy of path planning of a reactor pool decontamination robot, the present application provides a local path planning method for a reactor pool decontamination robot. In the method, a first motion path is first determined according to an environmental map of the bottom of the reactor pool. In the process of navigating the reactor pool decontamination robot from a preset starting point along the first motion path, real-time local path planning is performed on the above-mentioned first motion path to obtain a local path planning result, wherein the above-mentioned local path planning at least includes multiple smooth constraints on the first motion path, and the above-mentioned multiple smooth constraints are used to limit the distance between each path point in the first motion path and the turning radius of the first motion path. The above-mentioned local path planning result is used to adjust the first motion path to obtain a second motion path, and the reactor pool decontamination robot is navigated according to the above-mentioned second motion path until the reactor pool decontamination robot reaches the end point.

[0033] Figure 1 A flow chart of a local path planning method for a nuclear power plant reactor pool decontamination robot provided in an embodiment of the present application is shown. The above method can be applied to a robot control system, as described in detail as follows:

[0034] S11. Determine a first motion path according to environmental data at the bottom of the reactor pool; wherein the first motion path is a path from a preset starting point to a preset end point, and the first motion path includes a plurality of path points.

[0035] The environmental data may be pre-collected map data, including terrain information, obstacle information, path information, etc. at the bottom of the reactor pool. In addition, the environmental data may also include data collected by sensors installed at the bottom of the reactor pool, such as image data collected by a camera, laser data collected by a laser sensor, etc. The preset starting point and the preset end point may be target points determined by the user.

[0036] Specifically, an environmental map reflecting the environment at the bottom of the reactor pool can be constructed based on the above-mentioned environmental data, and then a preset starting point and a preset end point in the environmental map can be determined according to the target point input by the user, and then the preset global planning algorithm is used to obtain the above-mentioned first motion path, and the reactor pool decontamination robot can be navigated according to the above-mentioned first motion path.

[0037] In an optional embodiment of the present application, the above-mentioned environment map can be one of a grid map, a point cloud map, a feature map, etc.; the above-mentioned preset global planning algorithm can be a Dijkstra algorithm or an A* algorithm, etc.

[0038] S12. During the process of the reactor pool decontamination robot navigating from the preset starting point along the first motion path, real-time local path planning is performed on the first motion path to obtain a local path planning result; the local path planning at least includes multiple smooth constraints on the first motion path, and the multiple smooth constraints are used to limit the distance between each path point in the first motion path and the turning radius of the first motion path.

[0039] The multiple smoothness constraints may include multiple constraint conditions, and the multiple constraint conditions include distance constraints on each path point in the first motion path and turning radius constraints on the first motion path.

[0040] Specifically, in the process of the reactor pool decontamination robot moving from a preset starting point according to the above-mentioned first motion path, an objective function can be constructed according to the environmental data of a certain range around the reactor pool decontamination robot and the above-mentioned multiple constraints, and then the distance of each path point in the local motion path of the reactor pool decontamination robot currently moving and the turning radius composed of each path point are adjusted (for example, increased or decreased), and the value of the above-mentioned objective function is recalculated according to the distance and turning radius of the adjusted path points. When the value of the objective function does not meet the preset requirements, the distance and turning radius of each path point are readjusted, and iterated multiple times until the value of the above-mentioned objective function meets the preset requirements or the number of iterations meets the preset iteration threshold, and the local path planning result is obtained. Among them, the above-mentioned local path planning result may include the adjusted path points, the local motion path composed of the adjusted path points, the path point position information, the number of iterations, etc.

[0041] It should be noted that the above-mentioned local path planning may also include other constraints on the reactor pool decontamination robot, so as to construct different objective functions in combination with the above-mentioned multiple smooth constraints, and continuously optimize and adjust the path points in the first motion path. Optionally, other constraints may include one or more of constraints on obstacles, constraints on the movement time of the reactor pool decontamination robot, constraints on the movement speed of the reactor pool decontamination robot, etc.

[0042] In the embodiment of the present application, by performing real-time local path planning on the first motion path as described above, the smoothness of the path can be optimized and the accuracy of the path planning can be improved by limiting the distance between each path point in the first motion path and the turning radius of the first motion path.

[0043] S13. Using the local path planning result, adjust the first motion path to obtain a second motion path, and navigate the reactor pool decontamination robot according to the second motion path until the reactor pool decontamination robot reaches the preset end point.

[0044] Specifically, after obtaining the above-mentioned local path planning results, the path points in the above-mentioned first motion path can be updated according to the path points in the local path planning results. Since the path points in the above-mentioned local path planning results pass through at least multiple smoothness constraints, a second motion path with stronger smoothness can be obtained by updating the path points, which makes the reactor pool decontamination robot have a more refined and robust motion path. Navigating the reactor pool decontamination robot according to the above-mentioned second motion path can improve the accuracy of the path planning of the reactor pool decontamination robot when it performs cleaning work at the bottom of the reactor pool, and avoid sharp turns, shaking and the like of the reactor pool decontamination robot during the cleaning process.

[0045] In the embodiment of the present application, the accuracy of the reactor pool decontamination robot path planning can be improved by adjusting the first motion path according to the local path planning result. Specifically, after determining the first motion path according to the environmental map at the bottom of the reactor pool, the first motion path is subjected to real-time local path planning to obtain the local path planning result. Since the local path planning at least includes multiple smooth constraints on the first motion path, and the multiple smooth constraints are used to limit the distance between each path point in the first motion path and the turning radius of the first motion path, it means that in the process of the reactor pool decontamination robot navigating from a preset starting point to a preset end point, the distance between each path point in the first motion path and the turning radius of the first motion path can be adjusted in real time through the local path planning result, thereby improving the smoothness of the first motion path and obtaining a second motion path with stronger path smoothness. Therefore, the accuracy of the path planning of the nuclear power plant reactor pool decontamination robot can be improved.

[0046] In some embodiments, the determining of the first motion path according to the environmental data of the bottom of the reactor pool includes:

[0047] Constructing an environmental grid map according to the environmental data of the bottom of the reactor pool, wherein the environmental grid map includes a plurality of grids representing the environment of the bottom of the reactor pool;

[0048] The motion trajectory from the starting grid to the target grid is determined from the environmental grid map using a preset global planning algorithm to obtain the first motion path; the starting grid is used to indicate the preset starting point, and the target grid is used to indicate the preset end point.

[0049] Specifically, after obtaining the above environmental data, an environmental grid map can be constructed according to a preset composition algorithm. The grids in the environmental grid map can represent obstacles at the bottom of the reactor pool, walkable areas, etc., and then the starting grid and the target grid are determined according to the target point input by the user, and global path planning is performed through a preset global planning algorithm to obtain the above first motion path. Optionally, the preset composition algorithm can be a Simultaneous Localization and Mapping (SLAM) algorithm.

[0050] For example, after obtaining the above environmental data, the SLAM algorithm can be used to construct an environmental grid map, and then the starting grid and target grid in the environmental grid map are determined according to the target point input by the user, and then the global path planning is performed through the A* algorithm to obtain the above first motion path.

[0051] In the embodiment of the present application, the environment at the bottom of the reactor pool can be simplified through the environmental grid map, so that the motion path from the preset starting point to the preset end point can be quickly determined through the above environmental grid map and the preset global planning algorithm.

[0052] In some embodiments, the first motion path is composed of a series of discrete path points. In order to more accurately adjust the first motion path, the local path planning result includes optimized path points. The local path planning result obtained by performing real-time local path planning on the first motion path includes:

[0053] Acquire real-time environmental data, and determine a local motion path from the first motion path according to the real-time environmental data, wherein the local motion path includes a plurality of path points;

[0054] Obstacle avoidance constraints are performed according to the above real-time environmental data to obtain obstacle avoidance constraint results; the above obstacle avoidance constraint results are used to reflect the safety degree of the distance between the above reactor pool decontamination robot and the obstacle;

[0055] Performing motion time constraints according to the above-mentioned multiple path points to obtain motion time constraint results; the above-mentioned motion time constraint results are used to reflect the time length of the above-mentioned reactor pool decontamination robot moving in the above-mentioned local motion path;

[0056] Performing the above-mentioned multiple smoothness constraints on adjacent path points in the above-mentioned local motion path to obtain multiple smoothness constraint results; the above-mentioned multiple smoothness constraint results are used to reflect the smoothness of the above-mentioned local motion path;

[0057] The path points in the local motion path are optimized according to the obstacle avoidance constraint results, the motion time constraint results and the multiple smoothness constraint results to obtain the optimized path points.

[0058] The above-mentioned real-time environmental data can be collected in real time during the movement of the reactor pool decontamination robot according to sensors installed on the reactor pool decontamination robot and / or the bottom of the reactor pool. The above-mentioned sensors installed on the reactor pool decontamination robot and / or the bottom of the reactor pool can include at least one of the following: laser radar (e.g., 16-line laser radar), camera (e.g., pan-tilt camera), inertial measurement unit (IMU), wheel odometer, ultrasonic sensor, etc. The above-mentioned real-time environmental data can include real-time obstacle information, real-time movement information of the reactor pool decontamination robot, etc. The above-mentioned obstacle avoidance constraint is used to limit the distance between the reactor pool decontamination robot and the obstacle; the above-mentioned movement time constraint is used to limit the length of time that the reactor pool decontamination robot moves in the above-mentioned local movement path; the above-mentioned multiple smoothness constraint is used to limit the smoothness of the above-mentioned local movement path.

[0059] Specifically, the local range of the current movement of the reactor pool decontamination robot can be determined according to the real-time environmental data, and then the local movement path corresponding to the local range can be determined from the above-mentioned first movement path; for the local movement path, local path planning is performed according to the multiple path points contained therein and the real-time environmental data, and the above-mentioned local path planning may include obstacle avoidance constraints, movement time constraints and multiple smoothness constraints, wherein, when the above-mentioned obstacle avoidance constraints are used, the distance from each path point in the local movement path to the obstacle detected in real time can be determined according to the real-time environmental data, and then the above-mentioned obstacle safety distance can be determined according to the distance from each path point to the obstacle detected in real time and the preset obstacle safety distance. Obstacle avoidance constraint results; in the case of the above-mentioned motion time constraint, the above-mentioned motion time constraint results can be determined according to the speed of the reactor pool decontamination robot through the path composed of path points; in the case of the above-mentioned multiple smoothness constraints, the multiple smoothness constraint results can be determined according to the distance between adjacent path points in the local motion path, turning changes, etc.; then the above-mentioned obstacle avoidance constraint results, motion time constraint results and multiple smoothness constraint results are used as different objective functions, and the total objective function is obtained by assigning weights, and the minimization of the above-mentioned total objective function is used as the optimization goal, and the path points in the local motion path are continuously iterated and adjusted until the total objective function meets the optimization goal, and the optimized path points are obtained. Optionally, obstacle avoidance constraints can be performed using the following formula:

[0060]

[0061] Among them, J obstacle is the above obstacle avoidance constraint result, M is the number of obstacles, d obstacle,j is the distance from the reactor pool decontamination robot to the jth obstacle, and r is the preset obstacle safety distance.

[0062] Optionally, the motion time constraint can be performed by the following formula:

[0063]

[0064] Among them, J time is the result of the above motion time constraint, N is the number of path points in the local motion path, v i is the speed of the reactor pool decontamination robot at the i-th path point.

[0065] In an optional embodiment of the present application, the above obstacle avoidance constraint results, motion time constraint results and multiple smoothness constraint results are used as different objective functions, and the overall objective function can be:

[0066] J=aJ obstacle +bJ time +cJ p

[0067] Among them, J is the overall objective function, a, b, c are the preset weights, J p It should be noted that the above-mentioned multiple smoothness constraints and the corresponding multiple smoothness constraint results will be specifically described in the following embodiments, and will not be repeated here.

[0068] In the embodiments of the present application, by constructing different objective functions, the local motion path can be optimized from multiple angles, thereby improving the accuracy of local path planning.

[0069] In some embodiments, considering that the smoothness of the path is closely related to the distance change of adjacent path points and the change of the turning radius, the above-mentioned multiple smoothness constraints include distance constraints and turning radius constraints. The above-mentioned multiple smoothness constraints are performed on the adjacent path points in the above-mentioned local motion path to obtain multiple smoothness constraint results, including:

[0070] Performing the distance constraint on adjacent path points in the local motion path at least once to obtain a distance constraint result; the distance constraint result is used to indicate the degree of deviation of adjacent path points in the local motion path;

[0071] Performing the turning radius constraint on adjacent path points in the local motion path to obtain a turning radius constraint result; the turning radius constraint result is used to indicate the smoothness of the turning radius in the local motion path;

[0072] The multiple smoothness constraint results are determined based on the distance constraint results and the turning radius constraint results.

[0073] Among them, the above-mentioned distance constraint is used to limit the distance between adjacent path points in the above-mentioned local motion path. The above-mentioned distance constraint may include different distance smoothing methods, for example, a primary distance smoothing method, a secondary distance smoothing method, etc.; the above-mentioned turning radius constraint is used to limit the turning radius in the above-mentioned local motion path.

[0074] Specifically, in order to improve the smoothness of the path and reduce the jitter in the path, the local motion path can be subject to distance constraints for 2 or more times when the distance constraint is applied, and a different distance smoothing method is used each time to obtain a more accurate distance constraint result, thereby better constraining the degree of deviation of adjacent path points in the local motion path; at the same time, when the turning radius constraint is applied, the turning radius of the local motion path can be estimated based on the adjacent path points in the above local motion path, and then the turning radius constraint result is obtained by constraining the above turning radius.

[0075] In an embodiment of the present application, when performing multiple smoothness constraints, not only the degree of deviation of adjacent path points and the smoothness of the turning radius in the local motion path are considered, but the accuracy of the distance constraint results is further improved through multiple distance constraints, thereby better improving the smoothness of path planning.

[0076] In some embodiments, performing the distance constraint on adjacent path points in the local motion path at least once to obtain a distance constraint result includes:

[0077] Calculating the path deviation of adjacent path points in the local motion path, performing a first distance constraint according to the path deviation, and obtaining a first distance constraint result; the first distance constraint result is used to indicate the degree of distance deviation of adjacent path points in the local motion path;

[0078] Performing a second distance constraint according to the coordinates of the adjacent path points in the local motion path to obtain a second distance constraint result; the second distance constraint result is used to indicate the degree of smooth deviation of the adjacent path points in the local motion path;

[0079] The distance constraint result is determined according to the first distance constraint result and the second distance constraint result.

[0080] Specifically, it is assumed that the above distance constraint result is obtained through two distance constraints, and the above two distance constraints may include a primary distance smoothing method and a secondary distance smoothing method. The path deviation of adjacent path points in the local motion path is calculated by the primary distance smoothing method and a first distance constraint is performed to obtain a first distance constraint result; the coordinates of adjacent path points in the local motion path are subjected to a second distance constraint by the secondary distance smoothing method to obtain a second distance constraint result. When the distance constraint result is used as the objective function, the above first distance constraint result and the above second distance constraint result may be used as sub-objective functions when the distance constraint is used.

[0081] Optionally, the first distance constraint can be performed using the following formula:

[0082]

[0083] Among them, J path is the result of the first distance constraint, x i ,y i is the coordinate of the i-th path point, x i+1 -x i ,y i+1 -y i is the degree of deviation between adjacent path points, and N is the number of path points.

[0084] Optionally, a second distance constraint may be performed using the following formula:

[0085]

[0086] Among them, J smooth is the result of the second distance constraint, x i ,y i is the coordinate of the i-th path point.

[0087] In the embodiment of the present application, the first distance constraint and the second distance constraint can better constrain the degree of deviation of adjacent path points and improve the path smoothness during local path planning.

[0088] In some embodiments, the above-mentioned turning radius constraint is performed on adjacent path points in the above-mentioned local motion path to obtain a turning radius constraint result, including:

[0089] Calculate the path length and angle change of adjacent path points in the local motion path;

[0090] Determine the turning radius of the local motion path according to the path length and angle change;

[0091] The turning radius constraint is performed on the turning radius to obtain the turning radius constraint result.

[0092] Specifically, among the N path points in the local motion path, for every two adjacent path points (x i ,y i ) and (x i+1 ,y i+1 ), first calculate the path length of adjacent path points: And, the angle change Δθ of adjacent path points i =|θ i+1 -θ i |, where θ i is the angle between the tangent directions of adjacent path points, θ i =arctan(y i+1 -y i ,x i+1 -x i ), and then determine the turning radius based on the above path length and angle change: The turning radius above is constrained according to the following formula:

[0093]

[0094] Among them, J turn is the turning radius constraint result, R min is the minimum turning radius.

[0095] In the embodiment of the present application, the above-mentioned turning radius constraint can be used to limit the smoothness of the turning radius, thereby avoiding sharp turns and the like during path planning.

[0096] In an optional embodiment of the present application, referring to the above-mentioned first distance constraint result, the second distance constraint result and the above-mentioned turning radius constraint, the final overall objective function in the local path constraint can be:

[0097] J′=αJ path +βJ obstacle +γJ smooth +δJ time +εJ turn

[0098] Among them, J′ is the final overall objective function, J path is the result of the first distance constraint, J obstacle is the obstacle avoidance constraint result, J smooth is the result of the second distance constraint, J time is the motion time constraint result, J turn is the turning radius constraint result. α, β, γ, δ and ε are the preset weights.

[0099] Optionally, considering that the reactor pool of a nuclear power plant is a special experimental scene, the motion path of the reactor pool decontamination robot needs to be more stable and smooth. Therefore, the value range of the weight corresponding to the first distance constraint result and the obstacle avoidance constraint result can be set to be larger, and the value range of the weight corresponding to the second distance constraint result, the motion time constraint result, and the turning radius constraint result can be set to be smaller, so that when planning the path, it is more inclined to choose a path that takes a relatively long time and has a relatively large turning path, so that the second motion path can be more suitable for the cleaning scene of the reactor pool of a nuclear power plant. For example, the value range of α can be [1, 10], the value range of β can be [1, 10], the value range of γ can be [1, 5], the value range of δ can be [1, 3], and the value range of ε can be [1, 5].

[0100] In some embodiments, the method of adjusting the first motion path using the local path planning result to obtain the second motion path includes:

[0101] Using the optimized path points, adjusting the path points in the first motion path to obtain a new first motion path;

[0102] Determining whether the new first motion path is feasible according to the real-time environmental data and / or the first motion path;

[0103] If feasible, determining the new first motion path as the second motion path;

[0104] If it is not feasible, the above-mentioned real-time environmental data is updated, and the process returns to the above-mentioned step of determining the local motion path from the above-mentioned first motion path according to the above-mentioned real-time environmental data and subsequent steps.

[0105] Specifically, during the navigation process, the overall objective function is minimized through local path planning, and the optimized path points are obtained through continuous iteration. Then, the optimized path points are used to update the corresponding path points in the first motion path to obtain a new first motion path, for example, the path points in the first motion path are replaced with the optimized path points. Then, it is determined whether the new first motion path is feasible through real-time environmental data and / or the first motion path. If it is determined through real-time environmental data that the new first motion path is close to the obstacle, and / or the new first motion path and the previous first motion path deviate too much, then the new first motion path is determined to be infeasible. After updating the obstacle information through real-time environmental data, the step of determining the local motion path from the first motion path according to the real-time environmental data and the subsequent steps are returned; otherwise, the new first motion path is determined to be feasible, and the second motion path is obtained.

[0106] In the embodiment of the present application, by determining whether the new first motion path is feasible through real-time environmental data and / or the first motion path, deviations or errors in local path planning results can be avoided, thereby improving the accuracy of path planning.

[0107] In another optional embodiment of the present application, since there are precision instruments at the bottom of the reactor pool, if they collide with the reactor pool decontamination robot, parts may be broken, resulting in foreign objects falling into the reactor pool, thereby causing serious safety accidents. Therefore, before navigating the reactor pool decontamination robot according to the second motion path, the process further includes:

[0108] Obtain ultrasonic ranging data;

[0109] The obstacle distance of the reactor pool decontamination robot is judged according to the ultrasonic ranging data to obtain an obstacle judgment result.

[0110] Specifically, during the movement of the reactor pool decontamination robot, the ultrasonic ranging data published by the ultrasonic rangefinder can be obtained by subscription, and the distance between the reactor pool decontamination robot and the obstacle at the bottom of the reactor pool can be judged according to the ultrasonic ranging data to determine whether it is lower than the preset collision safety distance, and obtain the obstacle judgment result. If it is not lower than, the above obstacle judgment result can indicate that the reactor pool decontamination robot and the obstacle at the bottom of the reactor pool are at a collision safety distance, and if it is lower than, the above obstacle judgment result can indicate that the reactor pool decontamination robot and the obstacle at the bottom of the reactor pool are not at a collision safety distance. Optionally, the above ultrasonic rangefinder can be installed at the bottom of the reactor pool and / or the reactor pool decontamination robot, which is not limited here. The above preset collision safety distance and the preset obstacle safety distance during the obstacle avoidance constraint may be the same or different.

[0111] For example, the above-mentioned obstacle judgment result can be an execution flag. When the execution flag is TURE, it means that the reactor pool decontamination robot and the obstacles at the bottom of the reactor pool are within the collision safety distance; when the execution flag is not TURE, it means that the reactor pool decontamination robot and the obstacles at the bottom of the reactor pool are not within the collision safety distance.

[0112] Correspondingly, navigating the reactor pool decontamination robot according to the second motion path includes:

[0113] When the obstacle judgment result indicates that the reactor pool decontamination robot and the obstacle at the bottom of the reactor pool are at a collision safety distance, the reactor pool decontamination robot is navigated according to the second motion path.

[0114] Specifically, when the obstacle judgment result is the execution mark TURE, it means that the reactor pool decontamination robot is in a safe position, and the reactor pool decontamination robot can be navigated according to the above second motion path.

[0115] In another optional embodiment of the present application, the above method further includes:

[0116] When the obstacle judgment result indicates that the reactor pool decontamination robot and the obstacle at the bottom of the reactor pool are not at a collision safety distance, the movement of the reactor pool decontamination robot is suspended and an alarm is issued.

[0117] Specifically, when the obstacle judgment result is not the execution mark TURE, it means that the reactor pool decontamination robot is not in a safe position. At this time, the movement of the reactor pool decontamination robot can be suspended, and an alarm can be issued, and the position of the reactor pool decontamination robot can be manually adjusted by the operator. The above alarm can include: one or more of voice reminders, text reminders, etc. Of course, alarm prompts can also be issued through other devices, such as alarms through sound and light alarms, etc., which are not limited here.

[0118] In order to better illustrate the navigation and motion process of the reactor pool decontamination robot, Figure 2 For explanation, refer to Figure 2 As shown in FIG. 1 , it is assumed that the local path planning method of the nuclear power plant reactor pool decontamination robot is applied to the robot operating system (Robot Operating System) A system (ROS) platform is provided. First, a ROS node is started, and the ROS node is communicated with the reactor pool decontamination robot through the node, and the data released by the ultrasonic rangefinder is subscribed. Then, the path planning of the reactor pool decontamination robot is performed, and the path planning includes global path planning and local path planning, wherein the global path planning obtains a first motion path through environmental data, and the local path planning obtains a second motion path by adjusting the path points therein, and then a motion instruction is sent to the reactor pool decontamination robot, and the motion instruction includes the second motion path, motion mode, motion time, etc. At the same time, whether the robot is below the collision safety distance is determined according to the subscribed ultrasonic ranging data, if not, the execution flag is determined to be TURE, if it is below, the movement of the reactor pool decontamination robot is suspended, and an alarm is given. After the operator manually adjusts the position of the reactor pool decontamination robot, the step of determining whether the robot is below the collision safety distance according to the subscribed ultrasonic ranging data and subsequent steps are returned. After receiving the motion instruction, the reactor pool decontamination robot also needs to determine whether the execution flag is TURE, if it is TURE, navigation is performed through the second motion path, otherwise, it is suspended and waited.

[0119] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0120] Corresponding to the local path planning method of the reactor pool decontamination robot described in the above embodiment, Figure 3 A structural schematic diagram of a local path planning device of a reactor pool decontamination robot provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0121] Reference Figure 3 The device may be a local path planning device 31 of a reactor pool decontamination robot, and the local path planning device 31 of the reactor pool decontamination robot may include a first motion path determination module 311, a local path planning module 312 and a second motion path determination module 313.

[0122] Reference Figure 3 , the local path planning device of the reactor pool decontamination robot comprises:

[0123] The first motion path determination module 311 is used to determine the first motion path according to the environmental data of the bottom of the reactor pool; wherein the first motion path is a path from a preset starting point to a preset end point, and the first motion path includes a plurality of path points;

[0124] The local path planning module 312 is used to perform real-time local path planning on the first motion path in the process of navigating the reactor pool decontamination robot from the preset starting point along the first motion path to obtain a local path planning result; the local path planning at least includes performing multiple smooth constraints on the first motion path, and the multiple smooth constraints are used to limit the distance between each path point in the first motion path and the turning radius of the first motion path;

[0125] The second motion path determination module 313 is used to adjust the first motion path using the local path planning result to obtain a second motion path, and navigate the reactor pool decontamination robot according to the second motion path until the reactor pool decontamination robot reaches the preset end point.

[0126] In some embodiments, when the first motion path determining module 311 determines the first motion path according to the environmental data of the bottom of the reactor pool, it includes:

[0127] Constructing an environmental grid map according to the environmental data of the bottom of the reactor pool, wherein the environmental grid map includes a plurality of grids representing the environment of the bottom of the reactor pool;

[0128] The motion trajectory from the starting grid to the target grid is determined from the environmental grid map using a preset global planning algorithm to obtain the first motion path; the starting grid is used to indicate the preset starting point, and the target grid is used to indicate the preset end point.

[0129] In some embodiments, the first motion path is composed of a series of discrete path points. In order to more accurately adjust the first motion path, the local path planning result includes optimized path points. When the local path planning module 312 performs real-time local path planning on the first motion path and obtains the local path planning result, it includes:

[0130] Acquire real-time environmental data, and determine a local motion path from the first motion path according to the real-time environmental data, wherein the local motion path includes a plurality of path points;

[0131] Obstacle avoidance constraints are performed according to the above real-time environmental data to obtain obstacle avoidance constraint results; the above obstacle avoidance constraint results are used to reflect the safety degree of the distance between the above reactor pool decontamination robot and the obstacle;

[0132] Performing motion time constraints according to the above-mentioned multiple path points to obtain motion time constraint results; the above-mentioned motion time constraint results are used to reflect the time length of the above-mentioned reactor pool decontamination robot moving in the above-mentioned local motion path;

[0133] Performing the above-mentioned multiple smoothness constraints on adjacent path points in the above-mentioned local motion path to obtain multiple smoothness constraint results; the above-mentioned multiple smoothness constraint results are used to reflect the smoothness of the above-mentioned local motion path;

[0134] The path points in the local motion path are optimized according to the obstacle avoidance constraint results, the motion time constraint results and the multiple smoothness constraint results to obtain the optimized path points.

[0135] In some embodiments, considering that the smoothness of the path is closely related to the distance change of adjacent path points and the change of the turning radius, the above-mentioned multiple smoothness constraints include distance constraints and turning radius constraints. When the above-mentioned local path planning module 312 performs the above-mentioned multiple smoothness constraints on the adjacent path points in the above-mentioned local motion path and obtains the multiple smoothness constraint results, it includes:

[0136] Performing the distance constraint at least once on adjacent path points in the local motion path to obtain a distance constraint result; the distance constraint result is used to indicate the degree of deviation of adjacent path points in the local motion path;

[0137] Performing the turning radius constraint on adjacent path points in the local motion path to obtain a turning radius constraint result; the turning radius constraint result is used to indicate the smoothness of the turning radius in the local motion path;

[0138] The multiple smoothness constraint results are determined based on the distance constraint results and the turning radius constraint results.

[0139] In some embodiments, when the local path planning module 312 performs the distance constraint on adjacent path points in the local motion path at least once to obtain the distance constraint result, the following steps are performed:

[0140] Calculating the path deviation of adjacent path points in the local motion path, performing a first distance constraint according to the path deviation, and obtaining a first distance constraint result; the first distance constraint result is used to indicate the degree of distance deviation of adjacent path points in the local motion path;

[0141] Performing a second distance constraint according to the coordinates of the adjacent path points in the local motion path to obtain a second distance constraint result; the second distance constraint result is used to indicate the degree of smooth deviation of the adjacent path points in the local motion path;

[0142] The distance constraint result is determined according to the first distance constraint result and the second distance constraint result.

[0143] In some embodiments, when the local path planning module 312 performs the turning radius constraint on adjacent path points in the local motion path to obtain the turning radius constraint result, it includes:

[0144] Calculate the path length and angle change of adjacent path points in the local motion path;

[0145] Determine the turning radius of the local motion path according to the path length and angle change;

[0146] The turning radius constraint is performed on the turning radius to obtain the turning radius constraint result.

[0147] In some embodiments, when the second motion path determination module 313 adjusts the first motion path using the local path planning result to obtain the second motion path, it includes:

[0148] Using the optimized path points, adjusting the path points in the first motion path to obtain a new first motion path;

[0149] Determining whether the new first motion path is feasible according to the real-time environmental data and / or the first motion path;

[0150] If feasible, determining the new first motion path as the second motion path;

[0151] If it is not feasible, the above-mentioned real-time environmental data is updated, and the process returns to the above-mentioned step of determining the local motion path from the above-mentioned first motion path according to the above-mentioned real-time environmental data and subsequent steps.

[0152] In another optional embodiment of the present application, since there are precision instruments at the bottom of the nuclear power plant pool, if they collide with the reactor pool decontamination robot, parts may be broken, resulting in foreign objects falling into the reactor pool, thereby causing serious safety accidents. Therefore, the above-mentioned device also includes an obstacle avoidance module, which is used before navigating the above-mentioned reactor pool decontamination robot according to the above-mentioned second motion path, including:

[0153] Obtain ultrasonic ranging data;

[0154] The obstacle distance of the reactor pool decontamination robot is judged according to the ultrasonic ranging data to obtain an obstacle judgment result.

[0155] Correspondingly, when the second motion path determining module 313 navigates the reactor pool decontamination robot according to the second motion path, the second motion path determining module 313 includes:

[0156] When the obstacle judgment result indicates that the reactor pool decontamination robot and the obstacle at the bottom of the reactor pool are at a collision safety distance, the reactor pool decontamination robot is navigated according to the second motion path.

[0157] In another optional embodiment of the present application, the above-mentioned device also includes an alarm module, which is used to:

[0158] When the obstacle judgment result indicates that the reactor pool decontamination robot and the obstacle at the bottom of the reactor pool are not at a collision safety distance, the movement of the reactor pool decontamination robot is suspended and an alarm is issued.

[0159] It should be noted that the information interaction, execution process, etc. between the devices / units are based on the same concept as the method embodiments of the present application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0160] Figure 4 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Figure 4 As shown, the electronic device 4 of this embodiment includes: at least one processor 40 ( Figure 4The at least one processor 40 includes a memory 41 and a computer program 42 stored in the memory 41 and executable on the at least one processor 40. When the processor 40 executes the computer program 42, the steps in any of the method embodiments are implemented.

[0161] The electronic device 4 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device may include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will appreciate that Figure 4 It is only an example of the electronic device 4 and does not constitute a limitation of the electronic device 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include an input sending device, a network access device, a bus, etc.

[0162] The processor 40 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0163] In some embodiments, the memory 41 may be an internal storage unit of the electronic device 4, such as a hard disk or memory of the electronic device 4. The memory 41 may also be an external storage device of the electronic device 4, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 4. Further, the memory 41 may also include both an internal storage unit of the electronic device 4 and an external storage device. The memory 41 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 41 may also be used to temporarily store data that has been sent or is to be sent.

[0164] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the functional units and modules is used as an example. In practical applications, the function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0165] An embodiment of the present application also provides a network device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor implements the steps in any of the method embodiments when executing the computer program.

[0166] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the various method embodiments can be implemented.

[0167] An embodiment of the present application provides a computer program product. When the computer program product runs on an electronic device, the electronic device can implement the steps in the various method embodiments when executing the computer program product.

[0168] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process in the embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the camera / electronic device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0169] In the embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0170] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0171] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods 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 through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0172] 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.

[0173] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A local path planning method for a reactor pool decontamination robot, characterized in that: include: Determine a first motion path according to environmental data at the bottom of the reactor pool; wherein the first motion path is a path from a preset starting point to a preset end point, and the first motion path includes a plurality of path points; In the process of navigating the reactor pool decontamination robot from the preset starting point along the first motion path, real-time local path planning is performed on the first motion path to obtain a local path planning result; the local path planning at least includes performing multiple smooth constraints on the first motion path, and the multiple smooth constraints are used to limit the distance between each path point in the first motion path and the turning radius of the first motion path; The first motion path is adjusted using the local path planning result to obtain a second motion path, and the reactor pool decontamination robot is navigated according to the second motion path until the reactor pool decontamination robot reaches the preset end point.

2. The local path planning method of the reactor pool decontamination robot according to claim 1, characterized in that: The step of determining the first motion path according to the environmental data of the bottom of the reactor pool comprises: Constructing an environmental grid map according to the environmental data of the bottom of the reactor pool, wherein the environmental grid map includes a plurality of grids representing the environment of the bottom of the reactor pool; The motion trajectory from the starting grid to the target grid is determined from the environmental grid map using a preset global planning algorithm to obtain the first motion path; the starting grid is used to indicate the preset starting point, and the target grid is used to indicate the preset end point.

3. The local path planning method of the reactor pool decontamination robot according to claim 2, characterized in that: The local path planning result includes the optimized path points, and the real-time local path planning of the first motion path is performed to obtain the local path planning result, including: Acquire real-time environmental data, and determine a local motion path from the first motion path according to the real-time environmental data, wherein the local motion path includes a plurality of path points; Performing obstacle avoidance constraints according to the real-time environmental data to obtain obstacle avoidance constraint results; the obstacle avoidance constraint results are used to reflect the safety degree of the distance between the reactor pool decontamination robot and the obstacle; Performing motion time constraints according to the multiple path points to obtain motion time constraint results; the motion time constraint results are used to reflect the time length of the reactor pool decontamination robot moving on the local motion path; Performing the multiple smoothness constraints on adjacent path points in the local motion path to obtain multiple smoothness constraint results; the multiple smoothness constraint results are used to reflect the smoothness of the local motion path; The path points in the local motion path are optimized according to the obstacle avoidance constraint result, the motion time constraint result and the multiple smoothness constraint result to obtain the optimized path points.

4. The local path planning method of the reactor pool decontamination robot according to claim 3, characterized in that: The multiple smooth constraints include distance constraints and turning radius constraints. The multiple smooth constraints are applied to adjacent path points in the local motion path to obtain multiple smooth constraint results, including: Performing the distance constraint on adjacent path points in the local motion path at least once to obtain a distance constraint result; the distance constraint result is used to indicate the degree of deviation of adjacent path points in the local motion path; Performing the turning radius constraint on adjacent path points in the local motion path to obtain a turning radius constraint result; the turning radius constraint result is used to indicate the smoothness of the turning radius in the local motion path; The multiple smoothness constraint result is determined according to the distance constraint result and the turning radius constraint result.

5. The local path planning method of the reactor pool decontamination robot according to claim 4, characterized in that: The performing the distance constraint at least once on adjacent path points in the local motion path to obtain a distance constraint result includes: Calculating the path deviation of adjacent path points in the local motion path, performing a first distance constraint according to the path deviation, and obtaining a first distance constraint result; the first distance constraint result is used to indicate the degree of distance deviation of adjacent path points in the local motion path; Performing a second distance constraint according to the coordinates of the adjacent path points in the local motion path to obtain a second distance constraint result; the second distance constraint result is used to indicate the degree of smooth deviation of the adjacent path points in the local motion path; The distance constraint result is determined according to the first distance constraint result and the second distance constraint result.

6. The local path planning method of the reactor pool decontamination robot according to claim 4, characterized in that: The step of performing the turning radius constraint on adjacent path points in the local motion path to obtain a turning radius constraint result includes: Calculating the path length and angle change of adjacent path points in the local motion path; Determining a turning radius of the local motion path according to the path length and angle change; The turning radius constraint is performed on the turning radius to obtain the turning radius constraint result.

7. The local path planning method of a reactor pool decontamination robot according to any one of claims 3 to 6, characterized in that: The step of adjusting the first motion path by using the local path planning result to obtain a second motion path includes: Using the optimized path points to adjust the path points in the first motion path to obtain a new first motion path; Determining whether the new first motion path is feasible according to the real-time environmental data and / or the first motion path; If feasible, determining the new first motion path as the second motion path; If it is not feasible, the real-time environment data is updated, and the process returns to the step of determining the local motion path from the first motion path according to the real-time environment data and subsequent steps.

8. The local path planning method of a reactor pool decontamination robot according to any one of claims 1 to 6, characterized in that: Before navigating the reactor pool decontamination robot according to the second motion path, the method further includes: Obtain ultrasonic ranging data; Performing obstacle distance judgment on the reactor pool decontamination robot according to the ultrasonic ranging data to obtain an obstacle judgment result; The navigating the reactor pool decontamination robot according to the second motion path includes: When the obstacle judgment result indicates that the reactor pool decontamination robot and the obstacle at the bottom of the reactor pool are at a collision safety distance, the reactor pool decontamination robot is navigated according to the second motion path.

9. The local path planning method of the reactor pool decontamination robot according to claim 8, characterized in that: Also includes: When the obstacle judgment result indicates that the reactor pool decontamination robot and the obstacle at the bottom of the reactor pool are not at a collision safety distance, the movement of the reactor pool decontamination robot is suspended and an alarm is issued.

10. A local path planning device for a reactor pool decontamination robot, characterized in that: include: A first motion path determination module, used to determine a first motion path according to environmental data of the bottom of the reactor pool; wherein the first motion path is a path from a preset starting point to a preset end point, and the first motion path includes a plurality of path points; A local path planning module, used for performing real-time local path planning on the first motion path during the process of the reactor pool decontamination robot navigating from the preset starting point along the first motion path to obtain a local path planning result; the local path planning at least includes performing multiple smooth constraints on the first motion path, and the multiple smooth constraints are used to limit the distance between each path point in the first motion path and the turning radius of the first motion path; The second motion path determination module is used to adjust the first motion path using the local path planning result to obtain a second motion path, and navigate the reactor pool decontamination robot according to the second motion path until the reactor pool decontamination robot reaches the preset end point.

11. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 9 is implemented.

12. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

13. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 9 when being executed.

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