Tower crane trajectory planning method, electronic device and storage medium

Abstract

The present invention relates to the field of path planning technology, and more specifically to a tower crane trajectory planning method, electronic device, and storage medium. The method includes obtaining the position of a target tower crane at a current point and a first motion parameter, wherein the current point is the end point of the target tower crane's last path planning in a grid map, the grid map being a map of the area to be planned, and the first motion parameter includes speed and gear information of a preset mechanism; based on the first motion parameter and the gear shift information of the preset mechanism, path planning is performed in the grid map starting from the current point to determine the current optional path between a preset number of grids; the current optional path is screened based on obstacle information in the grid map to determine the current target path; and path planning is performed based on the end point of the current target path to determine the target path of the target tower crane from the target starting point to the target end point. Each path point obtained by the method includes position information and speed information, so that the target path meets dynamic constraints.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning, and in particular to a tower crane trajectory planning method, electronic equipment and storage medium. Background Art

[0002] A tower crane's movement from its starting point to its endpoint is coordinated by three major mechanisms: luffing, rotation, and lifting. When applying existing trajectory planning algorithms to tower crane trajectory planning, dynamic constraints may not be met. This is because existing trajectory planning algorithms plan paths based on adjacent grids. The resulting output represents the planned path between grids, but the granularity of this planned path is too coarse: it represents a "channel" or "surface" rather than a single, traversable route.

[0003] For example, Figure 1 As shown, taking the A* algorithm as an example, if it is a plane, path planning is performed in eight directions around it. The planning result may be: Grid trajectory 1:

[0004] A->(2,1)->(3,1)->(4,1)->(5,1)->(6,1)->(6,2)->(6,3)->(6,4)->(6,5)->B

[0005] Or, grid track 2:

[0006] A->(1,2)->(1,3)->(1,4)->(1,5)->(1,6)->(2,6)->(3,6)->(4,6)->(5,6)->B

[0007] Or, grid track 3: A->(2,2)->(3,3)->(4,4)->(5,5)->B, or others.

[0008] However, the above grid tracks are all "channels" rather than lines. For example, for grid track 1, there are many ways to walk. Figure 1 As shown, the solid line represents route 1, the dotted line represents route 2, and so on. Furthermore, for a moving object, if its speed is unknown, it is difficult to operate automatically. Therefore, a tower crane based on this grid trajectory cannot achieve automatic operation. Therefore, the path planned by the above method is difficult to meet the requirements of dynamic constraints. Summary of the Invention

[0009] In view of this, an embodiment of the present invention provides a tower crane trajectory planning method, an electronic device, and a storage medium to solve the problem that existing path planning methods are difficult to meet dynamic constraints.

[0010] According to a first aspect, an embodiment of the present invention provides a tower crane trajectory planning method, comprising:

[0011] Obtaining a position of a target tower crane at a current point and a first motion parameter, wherein the current point is the end point of the target tower crane's last path planning in a grid map, the grid map being a map of the area to be planned, and the first motion parameter includes speed and gear information of a preset mechanism;

[0012] Based on the first motion parameter and the gear shift information of the preset mechanism, performing path planning in the grid map starting from the current point to determine a current optional path between a preset number of grids;

[0013] Filtering the current optional path based on the obstacle information in the grid map to determine the current target path;

[0014] Path planning is performed based on the end point of the current target path to determine the target path of the target tower crane from the target starting point to the target end point.

[0015] The tower crane trajectory planning method provided by an embodiment of the present invention utilizes a first motion parameter and the gear shift information of a preset mechanism to perform path planning between a preset number of grids during path planning, and the result of the path planning between the grids of the preset grids is the current optional path, which includes multiple path points. Therefore, multiple path points between the preset grids can be obtained. At the same time, speed information is also combined when performing path planning. Therefore, each path point obtained includes not only position information but also speed information, so that the target path finally determined can meet the dynamic constraints, and for the target tower crane, automatic operation can be achieved based on the target path.

[0016] Optionally, the performing path planning in the grid map starting from the current point based on the first motion parameter and the gear shift information of the preset mechanism to determine a current optional path between a preset number of grids includes:

[0017] Obtaining a gear change combination of the preset mechanism;

[0018] Adjusting the gear information of the preset mechanism based on the gear change combination to determine the current selectable gear information of the preset mechanism;

[0019] Starting from the current point, path planning is performed in the grid map based on the current selectable gear information and the speed to determine a current selectable path between a preset number of grids.

[0020] The tower crane trajectory planning method provided by the embodiment of the present invention has a plurality of gear change modes at the same position point for the preset mechanism. Therefore, the gear change modes of each preset mechanism are combined to obtain a gear change combination. The gear change combination is used to adjust the gear information of the preset mechanism to obtain more comprehensive current optional gear information. Path planning is then performed based on the current optional gear information and speed to ensure the comprehensiveness of the current optional path obtained, thereby ensuring the accuracy of the target path finally obtained.

[0021] Optionally, starting from the current point, performing path planning in the grid map based on the current gear information and the speed to determine a current optional path between a preset number of grids includes:

[0022] Starting from the current point, sampling in the grid based on each of the current selectable gear information and the speed to obtain a current path point;

[0023] When the sampling duration of the sampling is less than the longest sampling duration and the path from the current point to the current path point passes through the preset number of grids, the current path point is determined to be the end point of the current optional path to determine the current optional path point, and the longest sampling duration is the maximum time threshold for sampling in the grid.

[0024] The tower crane trajectory planning method provided by the embodiment of the present invention uses sampling duration as a constraint, and can delete some path points that do not meet the conditions during sampling, thereby reducing the subsequent data processing volume and improving the efficiency of path planning.

[0025] Optionally, screening the current optional paths based on the obstacle information in the grid map to determine the current target path includes:

[0026] Using the obstacle information, determining a path in the current optional path that does not pass through the obstacle as a current passable path;

[0027] Obtaining a distance cost and a gear shift cost of the current traversable path, wherein the distance cost is the distance between an end point of the current traversable path and the target end point, and the gear shift cost is obtained based on the gear shift costs of each of the preset mechanisms;

[0028] Determining a cost of the current traversable path based on the distance cost and the gear shift cost;

[0029] The current traversable path corresponding to the minimum cost of the current traversable path is determined as the current target path.

[0030] The tower crane trajectory planning method provided by an embodiment of the present invention not only considers obstacle information when screening the current optional paths, but also combines distance cost and gear shift cost, and comprehensively considers the cost of the target tower crane during operation, thereby improving the accuracy of the determined current target path.

[0031] Optionally, obtaining the distance cost of the current traversable path includes:

[0032] Obtaining the distance between each grid and the target end point to obtain a grid distance cost;

[0033] When there are at least two endpoints of the current passable paths in the same grid, calculating the offset distance between the endpoint of the current passable path and the center point of the same grid to obtain an offset cost;

[0034] The distance cost of each of the currently traversable paths is determined based on the grid distance cost and the offset cost.

[0035] The tower crane trajectory planning method provided by the embodiment of the present invention further improves the accuracy of the distance cost by calculating the offset cost of each end point when there are at least two end points of the currently traversable paths in the same grid.

[0036] Optionally, obtaining the distance between each grid and the target end point to obtain the grid distance cost includes:

[0037] Obtaining a distance weight coefficient occupied by the height direction, where the distance weight coefficient is smaller than the distance weight coefficients occupied by other directions except the height direction;

[0038] Based on the distance weight coefficient, the distance between each grid and the target end point is calculated to obtain the grid distance cost.

[0039] The tower crane trajectory planning method provided by an embodiment of the present invention combines a distance weight coefficient in distance calculation, aiming to reduce the weight of height so that when encountering an obstacle during path planning, the crane can quickly raise its head and cross the obstacle, rather than blindly planning a path near the obstacle, thereby avoiding the path planning from falling into a local optimum.

[0040] Optionally, obtain the gear change cost of the current traversable path, including:

[0041] Obtaining the shift cost of each of the preset mechanisms and initializing the shift cost coefficient of each of the preset structures;

[0042] Based on the weighting of the shift cost and the corresponding shift cost coefficient, the optional shift cost of the current traversable path is determined to determine the shift cost.

[0043] The tower crane trajectory planning method provided by an embodiment of the present invention adopts an initialization method when calculating the gear shift cost. Subsequent path planning is performed based on the results of each initialization, and finally the obtained paths are screened to determine the gear shift cost.

[0044] Optionally, performing path planning based on the end point of the current target path to determine a target path of the target tower crane from a target starting point to a target end point includes:

[0045] Based on the position of the end point of the current target path and the second motion parameter, determining an optional path for each of the preset mechanisms to move according to preset constraints, wherein the preset constraints include each of the motion parameters changing from a current value to a corresponding maximum value, then moving at a constant speed, and then decelerating to zero;

[0046] When the optional path does not pass through the obstacle, determining that the end point of the current target path can directly reach the target end point, and determining the directly reachable optional path as a direct path;

[0047] The path planned and the direct path are combined to determine the target path.

[0048] The tower crane trajectory planning method provided by an embodiment of the present invention performs a direct reachability judgment after each path planning is completed. If the path is directly reachable, the path planning is completed. The target path can be obtained by directly splicing the direct path with the path planned, avoiding multiple path planning processes and improving the efficiency of trajectory planning.

[0049] According to a second aspect, an embodiment of the present invention provides a tower crane trajectory planning device, comprising:

[0050] an acquisition module, configured to acquire a position of a target tower crane at a current point and a first motion parameter, wherein the current point is the end point of the target tower crane's last path planning in a grid map, the grid map being a map of the area to be planned, and the first motion parameter includes speed and gear information of a preset mechanism;

[0051] a path planning module, configured to perform path planning in the grid map starting from the current point based on the first motion parameter and the gear shift information of the preset mechanism, and determine a current optional path between a preset number of grids;

[0052] A screening module, configured to screen the current optional paths based on the obstacle information in the grid map to determine the current target path;

[0053] The planning module is used to perform path planning based on the end point of the current target path and determine the target path of the target tower crane from the target starting point to the target end point.

[0054] According to the third aspect, an embodiment of the present invention provides an electronic device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the tower crane trajectory planning method described in the first aspect or any one of the embodiments of the first aspect by executing the computer instructions.

[0055] According to the fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute the tower crane trajectory planning method described in the first aspect or any one of the embodiments of the first aspect.

[0056] For the corresponding beneficial effects of the tower crane trajectory planning device, electronic device and computer-readable storage medium provided by the embodiments of the present invention, please refer to the description of the corresponding beneficial effects of the tower crane trajectory planning method above, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0058] Figure 1 A schematic diagram of existing trajectory planning is shown;

[0059] Figure 2 is a flow chart of a tower crane trajectory planning method according to an embodiment of the present invention;

[0060] Figure 3a-3c is a schematic diagram of a grid map according to an embodiment of the present invention;

[0061] Figure 4 is a schematic diagram of a path planning map according to an embodiment of the present invention;

[0062] Figure 5 is a flow chart of a tower crane trajectory planning method according to an embodiment of the present invention;

[0063] Figure 6 is a schematic diagram of calculating the offset cost according to an embodiment of the present invention;

[0064] Figure 7a-7bis a schematic diagram of distance calculation according to an embodiment of the present invention;

[0065] Figure 8 is a flow chart of a tower crane trajectory planning method according to an embodiment of the present invention;

[0066] Figure 9 is a schematic diagram of a direct path according to an embodiment of the present invention;

[0067] Figure 10 is a schematic diagram of a target path according to an embodiment of the present invention;

[0068] Figure 11 is a structural block diagram of a tower crane trajectory planning device according to an embodiment of the present invention;

[0069] Figure 12 It is a schematic diagram of the hardware structure of the electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0070] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0071] The tower crane trajectory planning method provided by an embodiment of the present invention is used to plan the tower crane trajectory from the target starting point to the target end point, and the cost of the target trajectory finally determined is minimized and meets the dynamic constraints. Specifically, starting from the target starting point, the path planning is performed in combination with the speed of the target tower crane and the gear shift information of each preset mechanism to obtain the trajectory points between the preset number of grids to determine the tower crane trajectory between the grids. After each path planning is completed, the end point of the current target path obtained by the current path planning can be used as the starting point of the next path planning, and the path planning is continued until the target end point is reached.

[0072] In some implementations, after each path planning is completed, the next path planning may not be performed immediately. Instead, a determination may be made as to whether the destination of the current target path is directly reachable from the destination. If so, path planning is complete, and the direct path is concatenated with the previously planned path to obtain the target trajectory.

[0073] According to an embodiment of the present invention, an embodiment of a tower crane trajectory planning method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings 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 shown here.

[0074] In this embodiment, a tower crane trajectory planning method is provided, which can be used for electronic devices such as computers, mobile terminals, etc. Figure 2 : is a flow chart of a tower crane trajectory planning method according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0075] S11, obtaining the position of the target tower crane at the current point and the first motion parameter.

[0076] The current point is the end point of the last path planning of the target tower crane in the grid map, the grid map is a map of the area to be planned, and the first motion parameter includes speed and gear information of a preset mechanism.

[0077] For the area to be planned, it can be mapped to a map and represented by a grid, thus obtaining a grid map, wherein the location information of obstacles is marked in the grid map.

[0078] When planning a crane trajectory, the electronic device needs to obtain the center point, target starting point, and target end point of the target crane and map them to a grid map. Therefore, the grid map includes obstacle information, the center point, target starting point, and target end point of the target crane.

[0079] Take the top view of the area to be planned as an example, read the obstacle information and generate the obstacle model. Figure 3a As shown in the figure, the tower crane radius is 50m, the tower crane height is 50m, and a cube of 100*100*50 is formed. Figure 3b As shown, grid division is performed and the resolution is set to 2m on the area volume of 100*100*50; Figure 3c As shown, a raster map is generated with a resolution of 2m.

[0080] As mentioned above, when planning the trajectory of the target tower crane, path planning begins from the target starting point. Each time path planning is performed, a current target trajectory is determined, and the end point of the current target trajectory is used as the starting point for the next path planning. Each current target trajectory includes multiple trajectory points, and the connection between these trajectory points forms the corresponding current target trajectory. For each trajectory point of the current target trajectory, the position information is recorded in the grid map. Therefore, during each path planning, the position information of the end point of the previous path planning trajectory is extracted from the grid map to obtain the position of the starting point of the current path planning, that is, the position of the current point.

[0081] When planning a tower crane trajectory, the speed of each preset mechanism is considered. Therefore, for each trajectory point of the current target trajectory, the speed of each preset mechanism is also included. Based on this, the electronic device can obtain the speed and gear position information of the preset mechanism at the current point. The preset mechanisms include the luffing mechanism, the hoisting mechanism, and the rotating mechanism. The gear position information indicates the gear position of the preset mechanism, for example, 1st gear, 2nd gear, 3rd gear, and so on.

[0082] S12: Based on the first motion parameter and the shift information of the preset mechanism, path planning is performed in the grid map starting from the current point to determine the current optional path between a preset number of grids.

[0083] The gear shift information indicates the change in gear information, for example, increasing one gear or reversing one gear. Based on the first motion parameter and the gear shift information, the electronic device determines the gear information at the current point. This information is then used to perform path planning within the grid map, determining the currently available paths between a preset number of grids. The preset number of grids can span two grids or a single grid. "Spanning a single grid" refers to two adjacent grids.

[0084] During path planning, the electronic device may set a specific value of a preset number as the end condition for this path planning; or, based on the preset number, combined with the maximum path planning time, use it as the end condition for this path planning, etc. Specifically, during path planning, the A* algorithm, a modified A* algorithm, or other path planning algorithms may be used, and there is no limitation on them here, and they are set according to actual needs.

[0085] After completing a path planning, the electronic device may obtain multiple current optional paths, which are determined by the gear shift information of the preset mechanism. Different gear shift information will result in different path points in the grid map.

[0086] S13, screening the current optional paths based on the obstacle information in the grid map to determine the current target path.

[0087] After the electronic device obtains multiple current optional paths in this path planning, it compares the current optional paths with the obstacles to determine whether the current optional paths pass through the obstacles. For example, the electronic device can compare the path point positions in each current optional path with the positions of the obstacles to determine whether the path points fall within the positions of the obstacles. If the path points fall within the positions of the obstacles, it means that the current optional path passes through the obstacles and needs to be discarded. Alternatively, after obtaining the current optional path, the electronic device determines whether the current optional path intersects with the obstacles. If there is an intersection, it means that the current optional path passes through the obstacles and needs to be discarded.

[0088] After the above obstacle screening, the paths that pass through obstacles in the current optional paths are discarded. If only one path remains, it is used as the current target path; if there are multiple paths, the costs of each current optional path can be combined to screen again, and the current optional path with the lowest cost is used as the current target path. The cost of the current optional path includes but is not limited to the distance cost between the end point of the current optional path and the target end point, and the gear shift cost of the preset mechanism, etc. For example, Figure 4 As shown, the current optional path corresponding to the path point with the minimum cost is determined as the current target path.

[0089] S14, performing path planning based on the end point of the current target path to determine the target path of the target tower crane from the target starting point to the target end point.

[0090] After obtaining the current target path, the electronic device can use the end point of the current target path as the starting point for the next path planning, and continue path planning until the target end point is reached, thereby obtaining the target path from the target starting point to the target end point.

[0091] Alternatively, the electronic device takes the end point of the current target path as the starting point and determines whether there is a direct path between the starting point and the target end point. That is, in order to improve efficiency, at the end of each path planning, it will be calculated whether the target end point can be reached directly from the end point of the current target trajectory according to the dynamic constraints. If it can be reached directly, the path planning ends. Specifically, the judgment of whether it can be reached directly is actually broken down into three parts: amplitude change: moving from the current amplitude to the end point amplitude; rotation: moving from the current angle to the end point angle; lifting: moving from the current height to the end point height. Since the running time of these three parts may be inconsistent, the number of points in each part is different. Based on this, according to the most points, the other insufficient parts can be supplemented, and then the three parts are assembled into the final trajectory line to obtain a direct path.

[0092] The tower crane trajectory planning method provided in this embodiment utilizes the first motion parameter and the gear shift information of the preset mechanism to perform path planning between a preset number of grids, and the result of the path planning between the grids of the preset grids is the current optional path, which includes multiple path points. Therefore, multiple path points between the preset grids can be obtained. At the same time, speed information is also combined during path planning. Therefore, each path point obtained includes not only position information but also speed information, so that the target path finally determined can meet the dynamic constraints, and the target tower crane can achieve automatic operation based on the target path.

[0093] In this embodiment, a tower crane trajectory planning method is provided, which can be used for electronic devices such as computers, mobile terminals, etc. Figure 5 : is a flow chart of a tower crane trajectory planning method according to an embodiment of the present invention. Figure 5 As shown, the process includes the following steps:

[0094] S21, obtaining the position of the target tower crane at the current point and the first motion parameter.

[0095] The current point is the end point of the last path planning of the target tower crane in the grid map, the grid map is a map of the area to be planned, and the first motion parameter includes speed and gear information of a preset mechanism.

[0096] For details, please see Figure 2 S11 of the illustrated embodiment will not be described in detail here.

[0097] S22 , based on the first motion parameter and the shift information of the preset mechanism, performing path planning in the grid map starting from the current point, and determining a current optional path between a preset number of grids.

[0098] Specifically, the above S22 includes:

[0099] S221, obtaining a gear change combination of a preset mechanism.

[0100] In order to ensure the smoothness and stability of the trajectory and prevent the inertial swing of the hanging object, each path planning can only be based on the current gear position of the three major mechanisms at the end of the last path planning, and can be changed to +1 gear, unchanged, or -1 gear, but cannot be suddenly changed to +2 gear or +3 gear, etc. At the same time, if the current gear is already the maximum gear, it cannot be changed to +1 gear, that is, the gear must be between 0 gear and the maximum gear. Based on this, the gear change combination (amplitude shifting, rotation shifting, lifting shifting) is set, and there are 27 combinations, namely, (-1, -1, -1), (-1, -1, 0), (-1, -1, 1), (-1, 0, -1), (-1, 0, 0), (-1, 0, 1), (-1, 1, -1), (-1, 1, 0), (-1, 1, 1), (0, -1, -1), (0, -1, -1), (0, -1 ,0),(0,-1,1),(0,0,-1),(0,0,0),(0,0,1),(0,1,-1),(0,1,0),(0,1,1),(1,-1,-1),(1,-1,0),(1,-1,1),(1,0,-1),(1,0,0),(1,0,1),(1,1,-1),(1,1,0),(1,1,1).

[0101] S222: Adjust the gear information of the preset mechanism based on the gear change combination to determine the current selectable gear information of the preset mechanism.

[0102] After obtaining the gear change combination, the gear information is adjusted based on the first motion parameter at the end of the previous path planning, i.e., the gear information in the first motion parameter, to obtain the current selectable gear information of the preset mechanism at the current point. Corresponding to the 27 gear change combinations mentioned above, 27 types of currently selectable gear information can be obtained.

[0103] S223 , starting from the current point, performing path planning in the grid map based on the current selectable gear information and speed, and determining the current selectable path between a preset number of grids.

[0104] Using the current gear information and speed, path planning is performed starting from the current point, generating 27 current optional paths. Each current optional path consists of several path points. In other words, each path planning step results in 27 current optional paths that meet the dynamic constraints.

[0105] In some embodiments, the above S223 includes:

[0106] (1) Starting from the current point, based on the current selectable gear information and speed, the current path point is sampled in the grid.

[0107] (2) When the sampling duration of the sampling is less than the longest sampling duration and the path from the current point to the current path point passes through a preset number of grids, the current path point is determined to be the end point of the current optional path to determine the current optional path point.

[0108] The maximum sampling duration is the maximum time threshold for sampling in the grid.

[0109] The starting point of each path planning is the endpoint of the previous path planning. Each path planning process involves planning in 27 directions, resulting in 27 endpoints. The endpoint conditions must satisfy the following requirements: the path span must be at least two grid cells (for adjacent grids, the path span must be one grid cell), and the path planning time must be an integer multiple of 1 second.

[0110] For example: when rotating, the amplitude is large (far away from the center of the circle), and it takes 1 second to cross two grids. Then the path planning ends. Or, when rotating, the amplitude is small (close to the center of the circle), and it takes 5 seconds to cross two grids, then the path planning ends. At the same time, set the maximum sampling time, for example 20s. If there is no crossing of two grids within 20s, the path planning ends. Among them, the preset number can be across two grids or across one grid. When crossing one grid, the step length is short and the number of steps taken is large; when crossing two grids, the step length is long and the number of steps taken is small.

[0111] Each currently available path includes multiple path points. Specifically, each path planning run lasts an integer number of seconds (n seconds, where n is an integer) and stops when the path from the current point to the current path point passes through two grids. If the sampling time is 100ms, the three mechanisms generate a sequence of path points based on their actual acceleration, current speed, current position, and a sampling frequency of 100ms. Each path point in the sequence includes both position and speed information.

[0112] For example, at the end of a 2s path planning, it crosses 2 grids, and there will be a sequence of 20 consecutive path points (position + velocity). This sequence of 20 points satisfies the dynamic constraints of the tower crane.

[0113] By using the sampling duration as a constraint, some path points that do not meet the conditions can be deleted during sampling, reducing the subsequent data processing volume and improving the efficiency of path planning.

[0114] S23, screening the current optional paths based on the obstacle information in the grid map to determine the current target path.

[0115] Specifically, the above S23 includes:

[0116] S231 : Using the obstacle information, determine the path that does not pass through the obstacle in the current optional path as the current passable path.

[0117] The electronic device uses obstacle information to calculate whether a sampled path point on each currently available path is within an obstacle. If a point falls within an obstacle area, the currently available path is discarded. Ultimately, at the end of each path planning cycle, N currently traversable paths are generated without collision. Accordingly, each of the N currently traversable paths has N endpoints.

[0118] Taking the A* algorithm as an example, each time path planning is completed, for these N end points, their corresponding starting points are set as their respective parent nodes to ensure that the path points can be backtracked when the path planning is completed, and the N end points of the N currently accessible paths are added to the open set.

[0119] S232: Obtain the distance cost and gear change cost of the current traversable path.

[0120] The distance cost is the distance between the end point of the current traversable path and the target end point, and the gear shift cost is obtained based on the gear shift costs of each preset mechanism.

[0121] After the current path planning is complete, we need to determine the starting point for the next path planning. Therefore, we need to re-screen the currently available paths. Specifically, we determine the endpoint with the lowest cost from the endpoints of the currently available paths and use it as the starting point for the next path planning. Continuing with the A* algorithm as an example, we add the point with the lowest cost in the open set to the closed set.

[0122] The electronic device uses the distance cost and gear shift cost of each currently traversable path to screen the currently traversable paths. The distance cost represents the distance between the current traversable path's endpoint and the target endpoint; the gear shift cost for the currently traversable path is the combined gear shift costs of each preset mechanism. The gear shift cost can be a random value or customized based on actual needs. The gear shift cost indicates that fewer gear changes are preferred; fewer gear changes result in a smoother trajectory. This cost determines whether the algorithm ultimately produces a smooth, stable trajectory with a shorter run time and fewer gear changes.

[0123] In some implementations, obtaining the distance cost of the current traversable path includes:

[0124] (1) Obtain the distance between each grid and the target end point to obtain the grid distance cost.

[0125] (2) When there are at least two endpoints of the current passable paths in the same grid, the offset distance between the endpoint of the current passable path and the center point of the same grid is calculated to obtain the offset cost.

[0126] (3) Determine the distance cost of each currently traversable path based on the grid distance cost and the offset cost.

[0127] When acquiring a grid map, the electronic device also includes the distance between each grid cell in the grid map and the target destination as the grid distance cost. When calculating the distance between each grid cell and the target destination, the distance between the grid center point and the target destination is calculated. Distance calculation methods include, but are not limited to, Euclidean distance, Manhattan distance, or diagonal distance.

[0128] If there are at least two currently traversable paths whose endpoints are in the same grid, calculate the offset distance between each endpoint and the grid center point to obtain the offset cost. Figure 6 As shown in , there are two end points in the same grid, namely end point A and end point B. By calculating the offset distance between end point A and center point C, and the offset distance between end point B and center point C, the corresponding offset cost is obtained. Figure 6 As shown, the offset distance of A is small, so the cost of point A is small. In other words, point A is closer to the end point D, the offset is smaller, and therefore the cost is smaller.

[0129] Combine Figure 6 As shown, the distance cost corresponding to each end point in the same grid is calculated as follows:

[0130] It should be noted that, in the following text, C_x represents the x-axis coordinate of point C. Similarly, C_y represents the y-axis coordinate of point C, and the rest are similar.

[0131] xDis1=|C_x–D_x|;

[0132] yDis1=|C_y–D_y|;

[0133] xDis2 = |A_x - D_x|;

[0134] yDis2=|A_y-D_y|;

[0135] xRadio=1 or -1, where xRadio=1 when xDis2>xDis1, otherwise xRadio=-1;

[0136] yRadio=1 or -1, wherein, when yDis2>yDis1, yRadio=1, otherwise yRadio=-1.

[0137] xshift = gridresolution / 2+xRadio*|A_x–C_x|;

[0138] yshift = gridresolution / 2 + yRadio*|A_y–C_y|;

[0139] The offset cost of point A:

[0140]

[0141] The distance cost of point A is:

[0142] CostA = the distance from the grid where point A is located to the target end point + the offset cost of point A shiftCostA.

[0143] When there are at least two endpoints of currently traversable paths in the same grid, the offset cost of each endpoint is obtained by calculation, thereby improving the accuracy of the distance cost.

[0144] In some other embodiments, the above step (1) includes:

[0145] 1.1) Obtaining a distance weight coefficient occupied by the height direction, wherein the distance weight coefficient is smaller than the distance weight coefficients occupied by other directions except the height direction.

[0146] 1.2) Based on the distance weight coefficient, calculate the distance between each grid and the target end point to obtain the grid distance cost.

[0147] Take the A* algorithm for path planning as an example. Since the A* algorithm is a heuristic algorithm, it is inevitable to fall into the local optimal value in the heuristic algorithm. Heuristic is essentially a greedy strategy, which objectively determines that better or optimal solutions that do not conform to the greedy rule will be missed. In combination with the actual business of tower cranes, a large scenario is to adjust from the ground to the roof, or from the roof to the ground. There are scaffoldings around the roof, which are about 6 meters higher than the roof, forming a semi-hollow state. Among them, Figure 7a This is a top view of the scene. Figure 7b This is a side view of the scene. Figure 7a The height of the scaffolding outside 7b is 6 meters, and the building is 30 meters tall. If starting point A is at the ground level (20, 0, 0), and end point B is at the center of the roof (-8, -12, 30), O1's coordinates (x, y, 30) are at the same height as end point B, and O2's coordinates (x1, y1, 38) are 2 meters above the scaffolding to prevent collision. The trajectory from starting point to end point must consist of two stages.

[0148] Phase 1: Climbing phase, A to O1 to O2;

[0149] Phase 2: Descending phase, O2 to B.

[0150] O1's horizontal movement directly to endpoint B offers the lowest cost. However, obstacles prevent this, requiring the user to gradually experiment with moving from O1 to endpoint B and then diverging in all directions. This ultimately creates a densely packed area, leading to a local optimum. Therefore, the first phase, from O1 to O2, is prone to local optima.

[0151] When analyzing the causes of the local optimal problem, we found that: each time the path is planned, the probabilities of the three directions of x-axis, y-axis and z-axis are the same, so a local optimal solution is formed. That is. When planning the path of O1, due to the obstruction of the scaffolding, the path will spread around O1 as the center and B as the target point. At the same time, because the scaffolding is too high, it will take many explorations before it can cross the scaffolding (the time consumption increases exponentially). In this scenario, if an obstacle is encountered, the upward path planning is carried out autonomously with a high probability, and the obstacle can be quickly crossed. After analysis, when encountering an obstacle, the factor affecting the probability of path planning in a certain direction is the distance from each grid to the target grid, which plays a decisive role. Based on this, this embodiment makes improvements by calculating the distance between each grid and the target end point.

[0152] Specifically, when calculating the distance from each grid to the target grid, the weight of altitude is reduced. This way, when planning a path, the cost of path planning in the altitude direction will be less than the cost in the horizontal direction. Therefore, if an obstacle is encountered during path planning, the path will tend to move upwards, and can quickly move over the obstacle. This allows the path planning to quickly "raise its head" and move over the obstacle, rather than blindly planning a path near the obstacle.

[0153] As mentioned above, it is necessary to adjust the distance weight coefficient of the height in the height direction. This distance weight coefficient means reducing the weight of the height. The distance weight coefficient in the height direction is smaller than the distance weight coefficients in the x-axis and y-axis directions. Taking Manhattan distance as an example, the distance weight coefficients in the x-axis and y-axis directions are 1, while the distance weight coefficient in the height direction (i.e., the z-axis direction) is greater than 0 and less than 1:

[0154] Distance = |x1–x2| + |y1–y2| + distance weight coefficient * |z1–z2|, where (x1, y1, z1) are the coordinates of the grid center point, and (x2, y2, z2) are the coordinates of the target endpoint.

[0155] The distance weight coefficient is incorporated into the distance calculation to reduce the weight of altitude. This allows the user to quickly look up and overcome obstacles when encountering them during path planning, rather than blindly planning paths near them, thus preventing path planning from falling into local optimality.

[0156] In some implementations, obtaining the gear shift cost of the current traversable path includes:

[0157] (1) Obtain the shift cost of each preset mechanism and initialize the shift cost coefficient of each preset structure.

[0158] (2) Based on the weighting of the gear shift cost and the corresponding gear shift cost coefficient, the optional gear shift cost of the current passable path is determined to determine the gear shift cost.

[0159] Shift cost = Weight factor 1 * Leverage shift cost + Weight factor 2 * Rotation shift cost + Weight factor 3 * Hoist shift cost + Weight factor 4 * Run time cost. The Leverage shift cost, Rotation shift cost, Hoist shift cost, and Run shift cost can be set to fixed values, and the corresponding coefficients are initialized. Through random initialization, multiple optional shift costs are obtained, which are used to screen the current available paths.

[0160] For example, during planning, different coefficient combinations are calculated simultaneously. The calculation ends with the combination that produces the result first, and the trajectory is returned. Subsequent optimizations will include a trajectory scoring program based on trajectory smoothness, run time, and other factors, automatically selecting high-quality coefficient combinations. This means that different shift cost coefficients may yield different results, ultimately resulting in different trajectories.

[0161] When calculating the gear shift cost, an initialization method is used. Subsequent path planning is based on the results of each initialization, and finally the obtained paths are screened to determine the gear shift cost.

[0162] S233: Determine the cost of the current traversable path based on the distance cost and the gear change cost.

[0163] Taking the A* algorithm as an example, the cost of the current traversable path = distance cost + gear change cost. Alternatively, if other path planning algorithms are used, the cost of the current traversable path can be calculated based on the distance cost and gear change cost according to the calculation method of other path planning algorithms.

[0164] S234: Determine the current traversable path corresponding to the minimum cost of the current traversable path as the current target path.

[0165] After obtaining the costs of each currently passable path, the electronic device compares the costs of each currently passable path, selects the current passable path corresponding to the minimum cost of the current passable path, and determines the current passable path as the current target path.

[0166] S24, performing path planning based on the end point of the current target path to determine a target path of the target tower crane from the target starting point to the target end point.

[0167] For details, please see Figure 2 S14 of the illustrated embodiment will not be described in detail here.

[0168] The tower crane trajectory planning method provided in this embodiment has multiple gear change modes for the preset mechanism at the same position point. Therefore, the gear change modes of each preset mechanism are combined to obtain a gear change combination. The gear change combination is used to adjust the gear information of the preset mechanism to obtain more comprehensive current optional gear information. Path planning is then performed based on the current optional gear information and speed to ensure the comprehensiveness of the current optional path obtained, thereby ensuring the accuracy of the target path obtained in the end. When screening the current optional path, not only obstacle information is considered, but also the distance cost and gear change cost are combined to comprehensively consider the cost of the target tower crane during operation, thereby improving the accuracy of the determined current target path.

[0169] In this embodiment, a tower crane trajectory planning method is provided, which can be used for electronic devices such as computers, mobile terminals, etc. Figure 8 : is a flow chart of a tower crane trajectory planning method according to an embodiment of the present invention. Figure 8 As shown, the process includes the following steps:

[0170] S31, obtaining the position of the target tower crane at the current point and the first motion parameter.

[0171] The current point is the end point of the last path planning of the target tower crane in the grid map, the grid map is a map of the area to be planned, and the first motion parameter includes speed and gear information of a preset mechanism.

[0172] For details, please see Figure 2 S11 of the illustrated embodiment will not be described in detail here.

[0173] S32: Based on the first motion parameter and the shift information of the preset mechanism, path planning is performed in the grid map starting from the current point to determine the current optional path between a preset number of grids.

[0174] For details, please see Figure 5 S22 of the illustrated embodiment will not be described in detail here.

[0175] S33, screening the current optional paths based on the obstacle information in the grid map to determine the current target path.

[0176] For details, please see Figure 5 S23 of the illustrated embodiment will not be described in detail here.

[0177] S34, performing path planning based on the end point of the current target path to determine the target path of the target tower crane from the target starting point to the target end point.

[0178] Specifically, the above S34 includes:

[0179] S341, based on the position of the end point of the current target path and the second motion parameter, determining the path points of each preset mechanism moving according to the preset constraint conditions to determine an optional path.

[0180] The preset constraint conditions include that each of the motion parameters changes from a current value to a corresponding maximum value, then moves at a constant speed, and then decelerates to zero.

[0181] To improve efficiency, each time a path is planned, it is calculated whether it is possible to reach the destination directly from the end point of the current target path to the destination according to the preset constraints. If it is possible, the path planning ends. The algorithm for reaching the destination directly is as follows:

[0182] For example, if the crane position at the current target path's endpoint is (luffing value A1, rotation value B1, lifting value C1), and the crane position at the target endpoint is (luffing value A2, rotation value B2, lifting value C2), then the three major crane mechanisms must move as follows: the luffing mechanism must change by A2-A1; the rotation mechanism must rotate by B2-B1; and the lifting mechanism must lift by C2-C1. By combining the speed information at the current target path's endpoint with the crane's gear position and acceleration information, the pathpoints along the direct path are calculated.

[0183] Specifically, if the coordinates of the current target path's endpoint are (x, y, z), they are converted to cylindrical coordinates (rx, θx, hx), where rx represents the current amplitude, θx represents the current rotation angle, and hx represents the current height. The amplitude, rotation, and lifting speeds of the current coordinates are rv, θv, and hv, respectively, and the cylindrical coordinates of the target endpoint are rG, θG, and hG.

[0184] Given the speed formula vt=v0+at and the distance formula S=v0*t+0.5*a*t^2, the three major mechanism directions are calculated separately.

[0185] For example, assume the tower crane has five gears for luffing: 1st gear has a speed of 0.2 m / s, 2nd gear has a speed of 0.4 m / s, ..., and 5th gear has a speed of 1 m / s. The luffing acceleration is a(1 m / s²). The current luffing position is rx (10 meters), the current luffing speed is rv (1st gear, 0.2 m / s), and the target end position is rG (30 meters). Therefore, the motion is: first accelerate from 1st gear to 5th gear, then maintain a constant speed, and then decelerate to zero, ensuring that it reaches the end point rG (30 meters). The time used is set to 200 ms.

[0186] According to the speed formula and the distance formula, a series of points r(1), r(2), r(3), r(4), ……, r(n) and the movement time rt are calculated, where r(1) = rx(10 m) and r(n) = rG(30 m).

[0187] Correspondingly, the following data can be obtained:

[0188] The luffing mechanism r(1), r(2), r(3), r(4), …, r(n1), movement time r;

[0189] The slewing mechanism θ(1), θ(2), θ(3), θ(4), …, θ(n2), movement time is θt;

[0190] The hoisting mechanism h(1), h(2), h(3), h(4), …, h(n3), movement time is ht.

[0191] The above values of n1, n2, and n3 are different. For those with fewer points, they are supplemented according to those with more points. If n1 < n2 < n3, the above data after supplementation is as follows:

[0192] The luffing mechanism r(1), r(2), r(3), r(4), … r(n1), r(n1), r(n1), …, r(n1), a total of n3 points;

[0193] The slewing mechanism θ(1), θ(2), θ(3), θ(4), …θ(n2), θ(n2), θ(n2), …, θ(n2), a total of n3 points;

[0194] The hoisting mechanism h(1), h(2), h(3), h(4), …, h(n3) a total of n3 points.

[0195] Form paths (r(1), θ(1), h(1)), (r(2), θ(2), h(2)), (r(3), θ(3), h(3)), (r(4), θ(4), h(4)), …, (r(n1), θ(n2), h(n3)) a total of n3 points.

[0196] S342, when the alternative path does not pass through an obstacle, determine that the end point of the current target path is directly reachable to the target end point, and determine the directly reachable alternative path as the direct path.

[0197] For the above n3 points, perform collision detection. If there is no collision, it means that the end point can be "directly reached" from the current point. Then, there is no need to perform path planning hereafter, and the algorithm ends, obtaining a direct path as shown in Figure 9 shown.

[0198] It should be noted that Figure 9 The direct path shown here consists of only rotations, without amplitude variation or lift, and the resulting direct trajectory is not a straight line. That is, in (r(1), θ(1), h(1)), (r(2), θ(2), h(2)), (r(3), θ(3), h(3)), (r(4), θ(4), h(4)), …, (r(n1), θ(n2), h(n3)), r(1) = r(2) = r(3) = … = r(n1), h(1) = h(2) = h(3) = … = h(n3).

[0199] S343: Combine the planned path and the direct path to determine the target path.

[0200] The path of path planning is the current target path obtained by each path planning before the direct judgment. According to the order of path planning, the current target path obtained by each path planning is spliced ​​and then combined with the direct path to obtain the target path between the target starting point and the target end point. For example, Figure 10 A schematic diagram of the final target path is shown.

[0201] In other words, the resulting target path can be composed of two parts: the first stage of continuous path planning and the second stage of direct access to the destination. The second stage means that after the first stage of reckless path planning, the obstacle zone has been cleared and the destination is an open area. Therefore, there is no need for further step-by-step path planning; a direct route is sufficient. It should be noted that the direct route here is not a straight line.

[0202] The tower crane trajectory planning method provided in this embodiment performs a direct reachability judgment after each path planning is completed. If it is directly reachable, the path planning is completed. The target path can be obtained by directly splicing the direct path with the path planned, avoiding the processing of multiple path planning and improving the efficiency of trajectory planning.

[0203] In this embodiment, a tower crane trajectory planning device is also provided. The device is used to implement the above-mentioned embodiments and preferred embodiments. The details that have been described will not be repeated here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0204] This embodiment provides a tower crane trajectory planning device, such as Figure 12 Shown, including:

[0205] An acquisition module 41 is configured to acquire a position of a target crane at a current point and a first motion parameter, wherein the current point is the end point of the target crane's last path planning in a grid map, the grid map being a map of the area to be planned, and the first motion parameter includes speed and gear information of a preset mechanism;

[0206] A path planning module 42 is configured to perform path planning in the grid map starting from the current point based on the first motion parameter and the gear shift information of the preset mechanism, and determine a current optional path between a preset number of grids;

[0207] A screening module 43 is configured to screen the current optional paths based on the obstacle information in the grid map to determine the current target path;

[0208] The planning module 44 is configured to perform path planning based on the end point of the current target path, and determine a target path of the target tower crane from a target starting point to a target end point.

[0209] In some embodiments, the path planning module 42 includes:

[0210] A first acquiring unit, configured to acquire a gear change combination of the preset mechanism;

[0211] an adjusting unit, configured to adjust the gear information of the preset mechanism based on the gear change combination, and determine the current selectable gear information of the preset mechanism;

[0212] A path planning unit is configured to start from the current point, perform path planning in the grid map based on the current selectable gear information and the speed, and determine a current selectable path between a preset number of grids.

[0213] In some embodiments, the path planning unit includes:

[0214] a sampling subunit, configured to, starting from the current point, sample in the grid based on the information of each currently selectable gear and the speed to obtain a current path point;

[0215] The first determination subunit is used to determine that the current path point is the end point of the current optional path when the sampling duration of the sampling is less than the longest sampling duration and the path from the current point to the current path point passes through the preset number of grids, so as to determine the current optional path point, and the longest sampling duration is the longest time threshold for sampling in the grid.

[0216] In some embodiments, the screening module comprises:

[0217] a screening unit, configured to use the obstacle information to determine a path in the current optional path that does not pass through an obstacle as a current passable path;

[0218] a second acquiring unit, configured to acquire a distance cost and a gear shift cost of the current passable path, wherein the distance cost is the distance between an end point of the current passable path and the target end point, and the gear shift cost is obtained based on the gear shift costs of each of the preset mechanisms;

[0219] a first determining unit, configured to determine a cost of the current passable path based on the distance cost and the gear shift cost;

[0220] The second determining unit is configured to determine the current traversable path corresponding to the minimum cost of the current traversable path as the current target path.

[0221] In some embodiments, the second acquiring unit includes:

[0222] A first acquisition subunit is configured to acquire the distance between each grid and the target end point to obtain a grid distance cost;

[0223] a first calculation subunit, configured to calculate, when at least two endpoints of the currently passable paths are in the same grid, an offset distance between the endpoint of the currently passable path and a center point of the same grid, to obtain an offset cost;

[0224] The second determining subunit is configured to determine the distance cost of each of the currently traversable paths based on the grid distance cost and the offset cost.

[0225] In some embodiments, the first acquiring subunit includes:

[0226] A second acquisition subunit is configured to acquire a distance weight coefficient occupied by a height direction, wherein the distance weight coefficient is smaller than the distance weight coefficients occupied by other directions except the height direction;

[0227] The second calculation subunit is configured to calculate the distance between each grid and the target end point based on the distance weight coefficient to obtain the grid distance cost.

[0228] In some embodiments, the second acquiring unit includes:

[0229] a third acquisition subunit, configured to acquire the shift cost of each of the preset mechanisms and initialize the shift cost coefficient of each of the preset mechanisms;

[0230] The third determining subunit is configured to determine the optional gear shift cost of the current passable path based on a weighted combination of the gear shift cost and the corresponding gear shift cost coefficient, so as to determine the gear shift cost.

[0231] In some embodiments, the planning module 44 includes:

[0232] a third determining unit, configured to determine, based on the position of the end point of the current target path and the second motion parameter, a path point for each of the preset mechanisms to move according to preset constraints, wherein the preset constraints include each of the motion parameters changing from a current value to a corresponding maximum value, then moving at a constant speed, and then decelerating to zero;

[0233] a fourth determining unit, configured to, when the optional path does not pass through the obstacle, determine that the end point of the current target path can directly reach the target end point, and determine the directly reachable optional path as a direct path;

[0234] A splicing unit is used to splice the path planned and the direct path to determine the target path.

[0235] The tower crane trajectory planning device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0236] The further functional description of each of the above modules is the same as that of the above corresponding embodiments and will not be repeated here.

[0237] An embodiment of the present invention further provides an electronic device having the above Figure 11 The tower crane trajectory planning device shown.

[0238] See also Figure 12 , Figure 12 is a structural diagram of an electronic device provided by an optional embodiment of the present invention, such as Figure 12 As shown, the electronic device may include: at least one processor 51, such as a CPU (Central Processing Unit), at least one communication interface 53, a memory 54, and at least one communication bus 52. The communication bus 52 is used to realize the connection and communication between these components. The communication interface 53 may include a display screen (Display), a keyboard (Keyboard), and the optional communication interface 53 may also include a standard wired interface and a wireless interface. The memory 54 may be a high-speed RAM memory (Random Access Memory, volatile random access memory) or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 54 may optionally be at least one storage device located away from the aforementioned processor 51. The processor 51 may be combined with Figure 11In the described apparatus, the memory 54 stores an application program, and the processor 51 calls the program code stored in the memory 54 to execute any of the above method steps.

[0239] The communication bus 52 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The communication bus 52 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 12 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0240] Among them, the memory 54 may include volatile memory (English: volatile memory), such as random-access memory (English: random-access memory, abbreviated: RAM); the memory may also include non-volatile memory (English: non-volatile memory), such as flash memory (English: flash memory), hard disk drive (English: hard disk drive, abbreviated: HDD) or solid-state drive (English: solid-state drive, abbreviated: SSD); the memory 54 may also include a combination of the above types of memory.

[0241] The processor 51 may be a central processing unit (CPU), a network processor (NP), or a combination of a CPU and a NP.

[0242] The processor 51 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0243] Optionally, the memory 54 is further configured to store program instructions. The processor 51 may call the program instructions to implement the tower crane trajectory planning method as shown in any embodiment of the present application.

[0244] An embodiment of the present invention further provides a non-transitory computer storage medium storing computer-executable instructions capable of executing the tower crane trajectory planning method of any of the above-mentioned method embodiments. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD); the storage medium may also include a combination of the above-mentioned types of memory.

[0245] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A tower crane trajectory planning method, characterized in that: include: Obtaining the position of the target tower crane at a current point and a first motion parameter, wherein the current point is the end point of the target tower crane's last path planning in a grid map, the grid map being a map of the area to be planned, and the first motion parameter includes speed and gear information of a preset mechanism; Based on the first motion parameter and the gear shift information of the preset mechanism, path planning is performed in the grid map starting from the current point to determine a current optional path between a preset number of grids, wherein the gear shift information represents a change in gear position information; Filtering the current optional path based on the obstacle information in the grid map to determine the current target path; Performing path planning based on the end point of the current target path to determine the target path of the target tower crane from the target starting point to the target end point; The step of performing path planning in the grid map starting from the current point based on the first motion parameter and the gear shift information of the preset mechanism to determine a current optional path between a preset number of grids includes: Acquire a gear change combination of the preset mechanism, wherein the gear change combination includes amplitude shifting, rotation shifting, and lifting shifting; Adjusting the gear information of the preset mechanism based on the gear change combination to determine the current selectable gear information of the preset mechanism; Starting from the current point, path planning is performed in the grid map based on the current selectable gear information and the speed to determine a current selectable path between a preset number of grids.

2. The method according to claim 1, characterized in that Starting from the current point, performing path planning in the grid map based on the current gear information and the speed to determine a current optional path between a preset number of grids includes: Starting from the current point, sampling in the grid based on each of the current selectable gear information and the speed to obtain a current path point; When the sampling duration of the sampling is less than the longest sampling duration and the path from the current point to the current path point passes through the preset number of grids, the current path point is determined to be the end point of the current optional path to determine the current optional path point, and the longest sampling duration is the maximum time threshold for sampling in the grid.

3. The method according to claim 1, characterized in that The screening of the current optional paths based on the obstacle information in the grid map to determine the current target path includes: Using the obstacle information, determining a path in the current optional path that does not pass through the obstacle as a current passable path; Obtaining a distance cost and a gear shift cost of the current traversable path, wherein the distance cost is the distance between an end point of the current traversable path and the target end point, and the gear shift cost is obtained based on the gear shift costs of each of the preset mechanisms; Determining a cost of the current traversable path based on the distance cost and the gear shift cost; The current traversable path corresponding to the minimum cost of the current traversable path is determined as the current target path.

4. The method according to claim 3, characterized in that The obtaining of the distance cost of the current passable path includes: Obtaining the distance between each grid and the target end point to obtain a grid distance cost; When there are at least two endpoints of the current passable paths in the same grid, calculating the offset distance between the endpoint of the current passable path and the center point of the same grid to obtain an offset cost; The distance cost of each of the currently traversable paths is determined based on the grid distance cost and the offset cost.

5. The method according to claim 4, characterized in that The obtaining of the distance between each grid and the target end point to obtain the grid distance cost includes: Obtaining a distance weight coefficient occupied by the height direction, where the distance weight coefficient is smaller than the distance weight coefficients occupied by other directions except the height direction; Based on the distance weight coefficient, the distance between each grid and the target end point is calculated to obtain the grid distance cost.

6. The method according to claim 3, characterized in that Get the gear change cost of the current traversable path, including: Obtaining the shift cost of each of the preset mechanisms and initializing the shift cost coefficient of each of the preset structures; Based on the weighting of the shift cost and the corresponding shift cost coefficient, the optional shift cost of the current traversable path is determined to determine the shift cost.

7. The method according to claim 1, characterized in that The performing path planning based on the end point of the current target path to determine the target path of the target tower crane from the target starting point to the target end point includes: Based on the position of the end point of the current target path and the second motion parameter, determining an optional path for each of the preset mechanisms to move according to preset constraints, wherein the preset constraints include each of the motion parameters changing from a current value to a corresponding maximum value, then moving at a constant speed, and then decelerating to zero; When the optional path does not pass through the obstacle, determining that the end point of the current target path can directly reach the target end point, and determining the directly reachable optional path as a direct path; The path planned and the direct path are combined to determine the target path.

8. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the tower crane trajectory planning method according to any one of claims 1 to 7 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the tower crane trajectory planning method according to any one of claims 1 to 7.

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