Tower crane path planning method, device and equipment based on polar coordinate recursive division

Abstract

The invention provides a tower crane path planning method, device and equipment based on polar coordinate recursive division, and relates to the field of path planning. The method comprises the following steps: acquiring related information of a hoisting point, a target point, a tower crane, a hoisted object and an obstacle, and establishing a polar coordinate system by taking the position of the tower crane as a circle center; further obtaining a tower crane hoisting range represented by a circular ring cylinder; then, dynamically and recursively dividing the hoisting range of the tower crane into a plurality of sub-bodies in different modes until a division termination condition is met; then, under the condition that the lifting point and the target point are not in the outer boundary frame of the sub-body, on the premise that the division termination condition is met, the lifting point and the target point are used as vertexes to be segmented to obtain new sub-bodies; calculating to obtain an optimal path by adopting an A * algorithm and combining a cost function, and optimizing to obtain an optimized path; and collision detection between the obstacle on the optimized path and the hoisted object is executed until the detection result is safe, a planned path is obtained, and the tower crane is controlled to operate. The path planned by the method is high in operability and safety.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning, and in particular to a tower crane path planning method, device and equipment based on polar coordinate recursive partitioning. Background Art

[0002] When operating a tower crane, path planning is a critical task. For traditional path planning methods, tower crane operators mainly perform tasks based on their own observations and experience, which is cumbersome and error-prone. Existing tower crane path planning research mainly focuses on optimizing the path length or planning time in advance, and most of them use random algorithms, such as rapid exploration random trees (RRT), probabilistic roadmaps, annealing algorithms, and particle swarm optimization (PSO), etc., which rarely consider the feasibility of the planned route and have the following disadvantages: (1) The lack of constraints on the search direction leads to a complex path. To solve this limitation, some studies have tried to use a sampling algorithm with direction constraints, but this method takes up a lot of computing memory and has low algorithm efficiency. (2) The limited availability and high cost of high-performance computing equipment restrict the application of algorithms in practical environments; (3) Small changes in state may lead to significant changes in algorithm results, so some algorithms have low interpretability and reusability; (4) The planned routes are mostly broken lines with many nodes, which causes the hook to swing frequently, increasing the risk of collision and energy consumption. In addition, the routes are incompatible with the rotation and amplitude variation characteristics of the tower crane, making it difficult for the operator to operate according to the planned path.

[0003] In view of this, the applicant filed this application after studying the existing technology. Summary of the invention

[0004] The present invention aims to provide a tower crane path planning method, device and equipment based on polar coordinate recursive partitioning to solve at least one of the above problems.

[0005] In order to solve the above technical problems, the present invention is implemented through the following technical solutions: A tower crane path planning method based on polar coordinate recursive partitioning, comprising: S1, obtain the relevant information of the lifting point, target point, tower crane, hoisted object and obstacles; and establish a polar coordinate system with the tower crane position as the center of the circle; S2, obtaining the lifting range of the tower crane represented by a circular cylinder according to the center of the circle, the maximum radius of the tower crane and the minimum radius of the tower crane; S3, dynamically and recursively dividing the tower crane lifting range in different ways according to the relevant information of the hoisted object and obstacles, until the division termination condition is reached, and a plurality of sub-bodies are generated; S4, determining whether the lifting point and the target point are on the outer boundary box of the sub-body, if not, then taking the lifting point and the target point as vertices to split and generate a fan-shaped cylinder under the condition that the division termination condition is met, and obtaining a new sub-body; S5, according to the lifting point and the target point, the A* algorithm is used in combination with the cost function to calculate the priority of each node in the path, and the node with the smallest replacement value is selected as the optimal path and optimized to obtain the optimized path; S6, according to the optimized path, perform collision detection between obstacles and the suspended object in the sub-body area where the optimized path passes through the outer boundary box of the sub-body; if the detection result does not meet the requirements, select the next suboptimal path for optimization, and perform collision detection again until the result meets the requirements, and use the optimized path as the planned path of the tower crane to control the operation of the tower crane.

[0006] Preferably, when establishing a polar coordinate system, the tower crane position is taken as the center of the circle, and the line connecting the center of the circle perpendicular to the ground and the plane projection position of the center of the circle and the position of the hoisted object is taken as the polar axis direction.

[0007] Preferably, the sub-body is a sub-circular cylinder or a sector-shaped cylinder obtained by dividing a circular cylinder, and different division methods include angle division, radius division and height division; The radius division method is as follows: taking the center of the current cylinder to be divided as the center of the circle, the arc length of the current cylinder to be divided is divided according to a preset arc length ratio; wherein the starting point and the end point of the divided sub-volume are respectively the positions of the original radius of the cylinder to be divided at the preset arc length ratio; The angle division method is: dividing the angle of the current cylinder to be divided according to a preset angle ratio; wherein the length of the sub-volume after division is the original radius of the cylinder to be divided, and the starting point and end point of the sub-volume are respectively the positions of the inner arc and outer arc of the cylinder to be divided corresponding to the angle ratio; The height division method is: dividing the height of the current column to be divided according to a preset height ratio.

[0008] The tower crane lifting range is dynamically and recursively divided in different ways, specifically: The division of each step is determined by the dynamic weight factor Determination, that is, dynamically determine the division method and dynamic weight factor according to the density of obstacles The calculation formula is: ; in, is the slope adjustment factor; is the density threshold; is the obstacle density of the current sub-body, ; is the number of obstacles in the sector; V is the sector volume, which is calculated by the following formula: ; when When it is greater than the first threshold, it indicates that the current state is high obstacle density, and the radius division method is selected to divide the path to accurately avoid obstacles, improve spatial resolution, and reduce path length cost. ; when When it is greater than the second threshold and not greater than the first threshold, it indicates that the obstacles in the current state are relatively dispersed and of medium density. The angle division method is selected to quickly scan a large range of space, reduce the blind area of ​​path search, and reduce the time cost. ; when When the height is not greater than the second threshold, it indicates that there are fewer obstacles in the current state, which is low density. The height division method is selected to reduce unnecessary lifting operations, improve lifting efficiency, and reduce energy consumption costs. ; Each sub-body after division is defined as a six-tuple , expressed as: ; in, represents the ith child, , They are the minimum polar angle of the sub-body and the maximum polar angle of the sub-body respectively; , are the maximum radius of the sub-body and the minimum radius of the sub-body respectively; , They are respectively the highest height and the lowest height of the sub-body.

[0009] Preferably, the division termination condition is: ; ; in, , are the maximum radius of the sub-body and the minimum radius of the sub-body respectively; , They are the highest height of the sub-body and the lowest height of the sub-body respectively; is the equivalent collision radius of the suspended object; is the height of the suspended object; δ is the safety margin.

[0010] Preferably, the equivalent collision radius of the suspended object is The calculation method is: ; Among them, L, W, and H are the length, width, and height of the suspended object respectively.

[0011] Preferably, the cost function is calculated by combining the actual cost and the heuristic cost, and S6 is specifically: The priority of each node in the path is sorted according to the calculated cost value; The cost function The expression is: ; ; ; in, for the actual cost; is the heuristic cost; is the path length weight coefficient; is the smoothing weight coefficient; is the energy consumption weight coefficient; is the time weight coefficient; is the path length cost, = + + , the penalty path is too long; is the total length of the path variation, is the total length of the rotary motion, To increase the total length of the movement; As the smoothness cost, the multi-node motion in the path is penalized to suppress the sudden change of angle and radius. The expression is: ; in, is the angle difference between the current node and the target node; is the radius difference between the current node and the target node; is the height difference between the current node and the target node; j represents the current node; is the energy cost, which penalizes frequent vertical adjustments that consume energy. The expression is: ; in, is the vertical segment height difference; is the time cost, the penalty time is too long, the expression is: ; in, is the speed of the amplitude variation motion, is the rotation speed, To increase speed; Indicates the current average radius, ; is the arc length; is the current radius; is the target radius; According to the lifting point and the target point, when traversing each node in the path based on the A* algorithm, two sets are used to represent the nodes to be traversed and the traversed nodes respectively; After calculating the cost value of each node, the priority queue of the node is obtained; Each time the cost function is selected from the priority queue The node with the smallest value, that is, the node with the highest priority, is used as the next node to be traversed, thereby obtaining the optimal path consisting of the nodes with the highest priority.

[0012] Preferably, the steps of optimizing the optimal path are: When the optimal path contains two discontinuous points, and the vertex coordinates of the two points located in different sub-bodies satisfy the same radius r and the same height z, concentric arcs are used to connect the two points to generate a new and better route; When the optimal path contains two discontinuous points, and the vertex coordinates of the two points located in different sub-bodies satisfy the same angle θ and the same height z, the two points are connected by a radius to generate a new and better route; When the optimal path contains two discontinuous points, and the vertex coordinates of the two points located in different sub-bodies satisfy the same radius r and the same angle θ, a height line is used to connect the two points to generate a new and better route; The generated better route is the optimized path.

[0013] Preferably, the specific steps of collision detection between the suspended object and the obstacle are: Obtain the minimum spherical bounding box of the obstacle and the radius of the spherical bounding box based on the relevant information of the obstacle Equivalent collision radius with the suspended object The calculation method is the same as that of , with the center of the sphere being the center of mass of the object; For nodes in the optimized path With Node The straight path formed , the straight line path Constructed as a cylinder, the parameters of the constructed cylinder are: Cylinder radius = ; Where δ is the safety margin; The axis of the cylinder is a line segment ; The height of the cylinder is the length of the cylinder ,Right now ; Calculate the obstacle sphere bounding box on the cylinder axis The projection area interval in the direction [ , ],like , ]∩[0, ]≠ , If it is empty, the distance from the center of the obstacle sphere to the axis of the cylinder is calculated. The shortest distance d; otherwise there is no collision; where, , are the lower and upper limits of the projection area respectively; If d< + ,in, is the radius of the spherical bounding box of the obstacle, a collision occurs; For nodes in the optimized path With Node The arc path is divided into n equal parts to generate n arc segments, where the value of n is determined by the maximum radius of the tower crane. The chord length of each arc segment is used to replace the corresponding arc, and the corresponding cylinder is constructed to perform collision detection on each arc segment. The cylinder construction method and the collision detection method of each arc segment are the same as those of the straight path. If the current optimized path does not meet the safety detection requirements, the next suboptimal path is selected as the optimal path for optimization, and then a safety collision detection is performed until the safety is met.

[0014] The present invention also provides a tower crane path planning device based on polar coordinate recursive partitioning, comprising: An acquisition unit is used to acquire relevant information of the lifting point, target point, tower crane, hoisted object and obstacles; and to establish a polar coordinate system with the tower crane position as the center of the circle; A tower crane lifting range unit, used to obtain the tower crane lifting range represented by a circular cylinder according to the center of the circle, the maximum radius of the tower crane and the minimum radius of the tower crane; A sub-body division unit is used to dynamically and recursively divide the lifting range of the tower crane in different ways according to the relevant information of the hoisted object and obstacles, until the division termination condition is reached, and a plurality of sub-bodies are generated; The new sub-body generation unit is used to determine whether the lifting point and the target point are on the outer boundary box of the sub-body. If not, a fan-shaped cylinder is generated by taking the lifting point and the target point as vertices to obtain a new sub-body under the condition that the division termination condition is met; The path optimization unit is used to calculate the priority of each node in the path according to the lifting point and the target point, using the A* algorithm combined with the cost function, and select the node with the smallest replacement value as the optimal path and optimize it to obtain the optimized path; The path planning unit is used to perform collision detection between obstacles and the suspended objects in the sub-body area when the optimized path passes through the outer boundary box of the sub-body according to the optimized path; if the detection result does not meet the requirements, the next suboptimal path is selected for optimization, and then the collision detection is performed again until the result meets the requirements, and the optimized path is used as the planned path of the tower crane to control the operation of the tower crane.

[0015] The present invention also provides a tower crane path planning device based on polar coordinate recursive partitioning, comprising a processor and a memory, wherein the memory stores a computer program, and the computer program can be executed by the processor to implement a tower crane path planning method based on polar coordinate recursive partitioning as described above.

[0016] The present invention also provides a computer-readable storage medium, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a device where the computer-readable storage medium is located, a tower crane path planning method based on polar coordinate recursive partitioning as described above is implemented.

[0017] In summary, compared with the prior art, the present invention has the following beneficial effects: The present invention recursively divides the three-dimensional space composed of the lifting range of the tower crane into sub-circular cylinders or fan-shaped cylinders in a polar coordinate system, and dynamically adapts different division methods (radius division / angle division / height division) according to the density of obstacles to conform to the kinematic characteristics of the tower crane and facilitate the actual operation of the operator.

[0018] The present invention adopts the A* algorithm and combines it with the cost function to select the optimal path node to achieve target optimization, so that the planned path takes into account both efficiency and operability. In addition, the cost function of the present invention introduces a path length cost item to punish excessively long and redundant hoisting paths; introduces a time cost item to suppress time-consuming movements; introduces an energy cost item to suppress high-energy consumption movements; introduces a path smoothness cost item to suppress angle and radius mutations, and reduce the number of turning points. It considers the factors in the tower crane path planning process from multiple aspects, and improves the efficiency of the planned path.

[0019] When performing collision detection between an obstacle and a suspended object, the present invention only performs deep division and collision detection in a necessary area, avoiding global detection and reducing a large amount of calculation and computer memory usage. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 A schematic diagram of a tower crane path planning method based on polar coordinate recursive partitioning provided in Example 1.

[0022] Figure 2 This is a schematic diagram of different division methods for the lifting range provided in Example 1.

[0023] Figure 3 This is a schematic diagram of path optimization in different situations provided in Example 1.

[0024] Figure 4 A schematic diagram of a tower crane path planning device based on polar coordinate recursive partitioning provided in Example 2.

[0025] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the 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 ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0027] Embodiment 1 Embodiment 1 of the present invention provides a tower crane path planning method based on polar coordinate recursive partitioning, which can be implemented by a tower crane path planning device based on polar coordinate recursive partitioning (hereinafter referred to as the path planning device), and in particular, executed by one or more processors in the path planning device.

[0028] In this embodiment, the path planning device may be an electronic device equipped with a processor, which has a computer program of the tower crane path planning method based on polar coordinate recursive division and the computer program can be executed, such as a computer, a smart phone, a smart tablet, a workstation, etc., which is not limited here.

[0029] In this embodiment, a recursive algorithm is a method that calls itself in a function or algorithm. In programming, recursive algorithms are mainly used to solve tasks that can be decomposed into smaller-scale identical problems.

[0030] The A* algorithm is an efficient path search and graph traversal algorithm, which is widely used in game design, robot path planning, network routing and other fields. It finds the shortest path from the starting point to the end point by combining heuristic evaluation and actual cost.

[0031] like Figure 1 As shown, a tower crane path planning method based on polar coordinate recursive partitioning includes steps S1 to S6.

[0032] S1, obtain the relevant information of the lifting point, target point, tower crane, hoisted objects and obstacles; and establish a polar coordinate system with the tower crane position as the center of the circle.

[0033] During the information collection stage of this embodiment, information such as the lifting point, target point, position of the tower crane, maximum radius and minimum radius of the tower crane are obtained; information such as the position of the hoisted object and the size of the hoisted object are obtained; information such as the position and size of the obstacle are obtained; in order to perform subsequent path planning and collision detection operations.

[0034] Then, a polar coordinate system is established with the tower crane position as the center of the circle, the upward direction perpendicular to the ground as the polar axis, and the line connecting the plane projection position of the tower crane position and the position of the hoisted object as the other polar axis direction.

[0035] S2, according to the center of the circle, the maximum radius of the tower crane and the minimum radius of the tower crane, obtain the lifting range of the tower crane represented by a circular cylinder.

[0036] S3, according to the relevant information of the hoisted object and obstacles, the hoisting range of the tower crane is dynamically and recursively divided in different ways until the division termination condition is reached, and a plurality of sub-bodies are generated by segmentation.

[0037] In this step, the ring cylinder is recursively divided to generate sub-volumes, which are sub-ring cylinders or sector cylinders obtained by dividing the ring cylinder. Different division methods in each step include angle division, radius division and height division.

[0038] The radius division method is as follows: the current cylinder to be divided (such as Figure 2The center of the circle is the black solid line range of the circular cylinder or fan-shaped cylinder shown in (a), and the arc length of the current cylinder to be divided is divided according to the preset arc length ratio (for example, set to half of the original arc length, of course, it can also be set to other ratios according to actual conditions, which is not limited here). Among them, the starting point and end point of the divided sub-volume are the positions of the original radius of the cylinder to be divided at the preset arc length ratio (such as Figure 2 (a) is indicated by the red dividing line.

[0039] The angle division method is: according to the preset angle ratio (such as Figure 2 (b), set to half of the original angle), to divide the angle of the current cylinder to be divided; wherein the length of the divided sub-body is the original radius of the cylinder to be divided, and the starting point and end point of the sub-body are the positions of the inner arc and outer arc of the cylinder to be divided corresponding to the angle ratio.

[0040] The height division method is: according to the preset height ratio (such as Figure 2 (c) shows that the height is set to half of the original height) to divide the height of the current column to be divided.

[0041] The division of each step is determined by the dynamic weight factor Determination, that is, dynamically determine the division method and dynamic weight factor according to the density of obstacles The calculation formula is: ; in, is the slope adjustment factor; is the density threshold; is the obstacle density of the current sub-body, ; is the number of obstacles in the sector; V is the sector volume, which is calculated by the following formula: ; In tower crane operation, obstacles are usually dense in the area near the tower (such as the main structure of the building) or within a specific radius (such as the equipment storage area), which is easy to form a high-density area. Greater than the first threshold (such as ), it means that the current state is high obstacle density. At this time, the radius division method is selected to divide the path to accurately avoid obstacles and improve spatial resolution. By subdividing the radius direction, the path length cost can also be reduced. .

[0042] when Greater than the second threshold and not greater than the first threshold (such as ), it means that the obstacles in the current state are relatively dispersed and of medium density. The angle division method is selected to quickly scan a large range of space and reduce the blind area of ​​path search. The speed of tower crane luffing is usually faster than the rotation speed, so the division of angle direction can reduce the time cost. .

[0043] when Not greater than the second threshold (such as ), it means that there are fewer obstacles in the current state, which is low density. The height division method is selected to divide the obstacles to reduce unnecessary lifting operations and improve the lifting efficiency. The lifting movement of the tower crane consumes a lot of energy. By finely dividing the height, unnecessary lifting operations can be reduced, reducing the energy cost. .

[0044] Each sub-body after division is defined as a six-tuple , expressed as: ; in, represents the ith child, , They are the minimum polar angle of the sub-body and the maximum polar angle of the sub-body respectively; , are the maximum radius of the sub-body and the minimum radius of the sub-body respectively; , They are respectively the highest height and the lowest height of the sub-body.

[0045] The partition termination condition is: ; ; in, , are the maximum radius of the sub-body and the minimum radius of the sub-body respectively; , They are the highest height of the sub-body and the lowest height of the sub-body respectively; is the equivalent collision radius of the suspended object; is the height of the suspended object; δ is the safety margin, such as 1 meter.

[0046] Among them, the equivalent collision radius of the suspended object is The calculation method is: ; Among them, L, W, and H are the length, width, and height of the suspended object respectively.

[0047] According to this method, the original hoisting range of the circular column is recursively divided into sub-bodies. The outer boundary box of each sub-body conforms to the kinematic characteristics of the tower crane, which is convenient for the operator to operate, that is, the possible tower crane operation route.

[0048] S4, judging whether the lifting point and the target point are on the outer boundary box of the sub-body, if not, then under the condition of meeting the termination condition of division, a fan-shaped cylinder is generated by dividing with the lifting point and the target point as the vertices to obtain a new sub-body.

[0049] Before planning the tower crane path, the lifting point and the target point are processed and the lifting point is specified as ), target point ), , Respectively represent the angle values ​​of the lifting point and the target point; , Respectively represent the radius values ​​of the lifting point and the target point; , Respectively represent the height values ​​of the lifting point and the target point. and When it is not on the outer boundary box of the sub-volume and there is no available sector nearby, temporary division is performed to or They are the eight vertices of the sub-volume fan-shaped cylinder, and fan-shaped cylinders similar to the generated sub-volumes are generated in the generated sub-volume fan-shaped cylinder, and the size needs to meet the termination condition of the division.

[0050] S5, according to the lifting point and the target point, the A* algorithm is used in combination with the cost function to calculate the priority of each node in the path, and the node with the smallest replacement value is selected as the optimal path and optimized to obtain the optimized path.

[0051] In this step, the A* algorithm is an algorithm that finds the lowest cost path from multiple nodes on a graph plane. It combines the characteristics of the best-first search and the Dijkstra algorithm to efficiently find the shortest path from the starting point to the end point. The improved A* algorithm is used to find the optimal path, and the cost function To calculate the priority of each node in the path. The cost function combines the actual cost and the heuristic cost calculation, and the priority of each node in the path is sorted according to the calculated cost value.

[0052] The cost function The expression is: ; ; ; in, for the actual cost; is the heuristic cost; n is the number of nodes; is the path length weight coefficient; is the smoothing weight coefficient; is the energy consumption weight coefficient; is the time weight coefficient; is the path length cost, = + + , the penalty path is too long; is the total length of the path variation, is the total length of the rotary motion, To increase the total length of the movement; As the smoothness cost, the multi-node motion in the path is penalized to suppress the sudden change of angle and radius. The expression is: ; in, is the angle difference between the current node and the target node; is the radius difference between the current node and the target node; is the height difference between the current node and the target node; j represents the current node; is the energy cost, which penalizes frequent vertical adjustments that consume energy. The expression is: ; in, is the vertical segment height difference; is the time cost, the penalty time is too long, the expression is: ; in, is the speed of the amplitude variation motion, is the rotation speed, To increase speed; Indicates the current average radius, ; is the arc length; is the current radius; is the target radius; According to the lifting point and the target point, when traversing each node in the path based on the A* algorithm, two sets are used to represent the nodes to be traversed and the traversed nodes respectively; After calculating the cost value of each node, the priority queue of the node is obtained; Each time the cost function is selected from the priority queue The node with the smallest value, that is, the node with the highest priority, is used as the next node to be traversed, thereby obtaining the optimal path consisting of the nodes with the highest priority.

[0053] Then the optimal path is optimized to obtain an optimized path.

[0054] The minimum node path is the optimal path, and the nodes of the path need to be optimized. There are three situations when optimizing: Case 1: If Figure 3 As shown in (a), when the optimal path contains two discontinuous points: nodes With Node , and the vertex coordinates of these two points in different sub-bodies satisfy the same radius r and height z, then concentric arcs are used to connect the two points to generate a new and better route (that is, the green dividing line in the figure).

[0055] Case 2: If Figure 3 As shown in (b), when the optimal path contains two discontinuous points: nodes With Node , and the vertex coordinates of these two points in different sub-bodies satisfy the same angle θ and the same height z, then use the radius to connect the two points to generate a new and better route.

[0056] Case 3: If Figure 3 As shown in (c), when the optimal path contains two discontinuous points: nodes With Node , and the vertex coordinates of these two points in different sub-bodies satisfy the same radius r and the same angle θ, then use the height line to connect the two points to generate a new and better route.

[0057] Traversing every two nodes of the optimal path and optimizing them, the resulting better route is the optimized path.

[0058] S6, according to the optimized path, perform collision detection between obstacles and the suspended object in the sub-body area where the optimized path passes through the outer boundary box of the sub-body; if the detection result does not meet the requirements, select the next suboptimal path for optimization, and perform collision detection again until the result meets the requirements, and use the optimized path as the planned path of the tower crane to control the operation of the tower crane.

[0059] In this step, after the path optimization, a safety check needs to be performed, that is, a collision check between the suspended object and the obstacle needs to be performed. At this time, the collision check only needs to detect whether a collision occurs between the obstacle and the suspended object in the sub-body whose outer boundary box is selected as the path. In this embodiment, the outer boundary box of the sub-body is a possible planned path.

[0060] First, the minimum spherical bounding box of the obstacle is obtained based on the relevant information of the obstacle. The radius of the spherical bounding box is Equivalent collision radius with the suspended object is calculated in the same way, with the center of the sphere being the center of mass of the object.

[0061] For nodes in the optimized path With Node The straight path formed , the straight line path Constructed as a cylinder, the parameters of the constructed cylinder are: Cylinder radius = δ; where δ is the safety margin; The axis of the cylinder is a line segment ; The height of the cylinder is the length of the cylinder ,Right now .

[0062] Calculate the obstacle sphere bounding box on the cylinder axis The projection area interval in the direction [ , ],like , ]∩[0, ]≠ , Indicates empty, that is, the projection area intersects with the cylinder, then the distance from the center of the obstacle sphere to the axis of the cylinder is calculated The shortest distance d; otherwise there is no collision. , are the lower and upper limits of the projection area respectively.

[0063] If d< + ,in, is the radius of the spherical bounding box of the obstacle, a collision occurs.

[0064] For nodes in the optimized path With Node The arc path formed is divided into n equal parts to generate n arc segments, where the value of n is determined by the maximum radius of the tower crane; the chord length of each arc segment is used to replace the corresponding arc, and the corresponding cylinder is constructed to perform collision detection on each arc segment; the cylinder construction method and the collision detection method of each arc segment are the same as those of the straight path.

[0065] If the current optimized path does not meet the safety test requirements, the next suboptimal path is selected as the optimal path for optimization, and then the safety collision test is performed until the safety is met. The optimized path that meets the safety is then used as the planned path of the tower crane to control the tower crane operation.

[0066] In summary, compared with the prior art, the present invention has the following beneficial effects: The present invention recursively divides the three-dimensional space composed of the lifting range of the tower crane into sub-circular cylinders or fan-shaped cylinders in a polar coordinate system, and dynamically adapts different division methods (radius division / angle division / height division) according to the density of obstacles to conform to the kinematic characteristics of the tower crane and facilitate the actual operation of the operator.

[0067] The present invention adopts the A* algorithm and combines it with the cost function to select the optimal path node to achieve target optimization, so that the planned path takes into account both efficiency and operability. In addition, the cost function of the present invention introduces a path length cost item to punish excessively long and redundant hoisting paths; introduces a time cost item to suppress time-consuming movements; introduces an energy cost item to suppress high-energy consumption movements; introduces a path smoothness cost item to suppress angle and radius mutations, and reduce the number of turning points. It considers the factors in the tower crane path planning process from multiple aspects, and improves the efficiency of the planned path.

[0068] When performing collision detection between an obstacle and a suspended object, the present invention only performs deep division and collision detection in a necessary area, avoiding global detection and reducing a large amount of calculation and computer memory usage.

[0069] Embodiment 2 like Figure 4 As shown, the second embodiment of the present invention further provides a tower crane path planning device based on polar coordinate recursive division, comprising: An acquisition unit is used to acquire relevant information of the lifting point, target point, tower crane, hoisted object and obstacles; and to establish a polar coordinate system with the tower crane position as the center of the circle; A tower crane lifting range unit, used to obtain the tower crane lifting range represented by a circular cylinder according to the center of the circle, the maximum radius of the tower crane and the minimum radius of the tower crane; A sub-body division unit is used to dynamically and recursively divide the lifting range of the tower crane in different ways according to the relevant information of the hoisted object and obstacles, until the division termination condition is reached, and a plurality of sub-bodies are generated; The new sub-body generation unit is used to determine whether the lifting point and the target point are on the outer boundary box of the sub-body. If not, a fan-shaped cylinder is generated by taking the lifting point and the target point as vertices to obtain a new sub-body under the condition that the division termination condition is met; The path optimization unit is used to calculate the priority of each node in the path according to the lifting point and the target point, using the A* algorithm combined with the cost function, and select the node with the smallest replacement value as the optimal path and optimize it to obtain the optimized path; The path planning unit is used to perform collision detection between obstacles and the suspended objects in the sub-body area when the optimized path passes through the outer boundary box of the sub-body according to the optimized path; if the detection result does not meet the requirements, the next suboptimal path is selected for optimization, and then the collision detection is performed again until the result meets the requirements, and the optimized path is used as the planned path of the tower crane to control the operation of the tower crane.

[0070] Embodiment 3 The third embodiment of the present invention also provides a tower crane path planning device based on polar coordinate recursive partitioning, which includes a memory and a processor, wherein the memory stores a computer program, and the computer program can be executed by the processor to implement the tower crane path planning method based on polar coordinate recursive partitioning as described above.

[0071] Embodiment 4 The fourth embodiment of the present invention also provides a computer-readable storage medium, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a device where the computer-readable storage medium is located, the tower crane path planning method based on polar coordinate recursive division as described above is implemented.

[0072] In several embodiments provided in the embodiments of the present invention, it should be understood that the disclosed apparatus and method can also be implemented in other ways. The apparatus and method embodiments described above are merely schematic. For example, the flowcharts in the accompanying drawings show the possible architecture, functions and operations of the apparatus, method and computer program product according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0073] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0074] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, electronic device, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code. It should be noted that in this article, the term "include", "include" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements that are not explicitly listed, or also includes elements inherent to such process, method, article or device. Without more constraints, an element defined by the phrase "comprising a..." does not exclude the existence of other identical elements in the process, method, article or apparatus comprising the element.

[0075] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0076] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0077] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0078] The "first\second" mentioned in the embodiments is only to distinguish similar objects, and does not represent a specific order for the objects. It is understandable that the "first\second" can be interchanged with the specific order or sequence where permitted. It should be understood that the objects distinguished by "first\second" can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than those illustrated or described herein.

[0079] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A tower crane path planning method based on polar coordinate recursive partitioning, characterized in that: include: S1, obtain relevant information of the lifting point, target point, tower crane, hoisted object and obstacles; And establish a polar coordinate system with the tower crane position as the center of the circle; S2, obtaining the lifting range of the tower crane represented by a circular cylinder according to the center of the circle, the maximum radius of the tower crane and the minimum radius of the tower crane; S3, dynamically and recursively dividing the tower crane lifting range in different ways according to the relevant information of the hoisted object and obstacles, until the division termination condition is reached, and a plurality of sub-bodies are generated; S4, judging whether the lifting point and the target point are on the outer boundary box of the sub-body, if not, then taking the lifting point and the target point as vertices to split and generate a fan-shaped cylinder under the condition that the division termination condition is met, and obtaining a new sub-body; S5, according to the lifting point and the target point, the A* algorithm is used in combination with the cost function to calculate the priority of each node in the path, and the node with the smallest replacement value is selected as the optimal path and optimized to obtain the optimized path; S6, according to the optimized path, perform collision detection between obstacles and the suspended object in the sub-body area where the optimized path passes through the outer boundary box of the sub-body; if the detection result does not meet the requirements, select the next suboptimal path for optimization, and perform collision detection again until the result meets the requirements, and use the optimized path as the planned path of the tower crane to control the operation of the tower crane.

2. A tower crane path planning method based on polar coordinate recursive partitioning according to claim 1, characterized in that When establishing a polar coordinate system, the tower crane position is taken as the center of the circle, and the line connecting the center of the circle perpendicular to the ground and the plane projection position of the center of the circle and the position of the hoisted object is taken as the polar axis direction.

3. A tower crane path planning method based on polar coordinate recursive partitioning according to claim 1, characterized in that ,The sub-body is a sub-circular cylinder or a sector-shaped cylinder after the circular cylinder is divided, and different ways of division include angle division, radius division and height division; The radius division method is as follows: taking the center of the current cylinder to be divided as the center of the circle, the arc length of the current cylinder to be divided is divided according to a preset arc length ratio; wherein the starting point and the end point of the divided sub-volume are respectively the positions of the original radius of the cylinder to be divided at the preset arc length ratio; The angle division method is: dividing the angle of the current cylinder to be divided according to a preset angle ratio; wherein the length of the sub-volume after division is the original radius of the cylinder to be divided, and the starting point and end point of the sub-volume are respectively the positions of the inner arc and outer arc of the cylinder to be divided corresponding to the angle ratio; The height division method is: dividing the height of the current column to be divided according to a preset height ratio; The tower crane lifting range is dynamically and recursively divided in different ways, specifically: The division of each step is determined by the dynamic weight factor Determination, that is, dynamically determine the division method and dynamic weight factor according to the density of obstacles The calculation formula is: ； in, is the slope adjustment factor; is the density threshold; is the obstacle density of the current sub-body, ; is the number of obstacles in the sector; V is the sector volume, which is calculated by the following formula: ; when When it is greater than the first threshold, it indicates that the current state is high obstacle density, and the radius division method is selected to divide the path to accurately avoid obstacles, improve spatial resolution, and reduce path length cost. ; when When it is greater than the second threshold and not greater than the first threshold, it indicates that the obstacle distribution in the current state is relatively dispersed, with a medium obstacle density. The angle division method is selected to quickly scan a large range of space, reduce the blind area of ​​path search, and reduce the time cost. ; when When it is not greater than the second threshold, it indicates that there are fewer obstacles in the current state, which is a low obstacle density. The height division method is selected to reduce unnecessary lifting operations, improve lifting efficiency, and reduce energy consumption costs. ; Each sub-body after division is defined as a six-tuple , expressed as: ； in, represents the ith child, , They are the minimum polar angle of the sub-body and the maximum polar angle of the sub-body respectively; , are the maximum radius of the sub-body and the minimum radius of the sub-body respectively; , They are respectively the highest height and the lowest height of the sub-body.

4. A tower crane path planning method based on polar coordinate recursive partitioning according to claim 1, characterized in that , the partition termination condition is: ； ； in, , are the maximum radius of the sub-body and the minimum radius of the sub-body respectively; , They are the highest height of the sub-body and the lowest height of the sub-body respectively; is the equivalent collision radius of the suspended object; is the height of the suspended object; δ is the safety margin.

5. A tower crane path planning method based on polar coordinate recursive partitioning according to claim 4, characterized in that , the equivalent collision radius of the suspended object The calculation method is: ； Among them, L, W, and H are the length, width, and height of the suspended object respectively.

6. A tower crane path planning method based on polar coordinate recursive partitioning according to claim 1, characterized in that , the cost function is calculated by combining the actual cost and the heuristic cost, and the S6 is specifically: The priority of each node in the path is sorted according to the calculated cost value; The cost function The expression is: ； ； ； in, for the actual cost; is the heuristic cost; is the path length weight coefficient; is the smoothing weight coefficient; is the energy consumption weight coefficient; is the time weight coefficient; is the path length cost, = + + , the penalty path is too long; is the total length of the path variation, is the total length of the rotary motion, To increase the total length of the movement; As the smoothness cost, the multi-node motion in the path is penalized to suppress the sudden change of angle and radius. The expression is: ； in, is the angle difference between the current node and the target node; is the radius difference between the current node and the target node; is the height difference between the current node and the target node; j represents the current node; is the energy cost, which penalizes frequent vertical adjustments that consume energy. The expression is: ； in, is the vertical segment height difference; is the time cost, the penalty time is too long, the expression is: ； in, is the speed of the amplitude variation motion, is the rotation speed, To increase speed; Indicates the current average radius, ; is the arc length; is the current radius; is the target radius; According to the lifting point and the target point, when traversing each node in the path based on the A* algorithm, two sets are used to represent the nodes to be traversed and the traversed nodes respectively; After calculating the cost value of each node, the priority queue of the node is obtained; Each time the cost function is selected from the priority queue The node with the smallest value, that is, the node with the highest priority, is used as the next node to be traversed, thereby obtaining the optimal path consisting of the nodes with the highest priority.

7. A tower crane path planning method based on polar coordinate recursive partitioning according to claim 1, characterized in that ,The steps of optimizing the optimal path are: When the optimal path contains two discontinuous points, and the vertex coordinates of the two points located in different sub-bodies satisfy the same radius r and the same height z, concentric arcs are used to connect the two points to generate a new and better route; When the optimal path contains two discontinuous points, and the vertex coordinates of the two points located in different sub-bodies satisfy the same angle θ and the same height z, the two points are connected by a radius to generate a new and better route; When the optimal path contains two discontinuous points, and the vertex coordinates of the two points located in different sub-bodies satisfy the same radius r and the same angle θ, a height line is used to connect the two points to generate a new and better route; The generated better route is the optimized path.

8. A tower crane path planning method based on polar coordinate recursive partitioning according to claim 5, characterized in that ,The specific steps of collision detection between the suspended object and the ,obstacle are as follows: Obtain the minimum spherical bounding box of the obstacle and the radius of the spherical bounding box based on the relevant information of the obstacle Equivalent collision radius with the suspended object The calculation method is the same as that of , with the center of the sphere being the center of mass of the object; For nodes in the optimized path With Node The straight path formed , the straight line path Constructed as a cylinder, the parameters of the constructed cylinder are: Cylinder radius = ; Where δ is the safety margin; The axis of the cylinder is a line segment ; The height of the cylinder is the length of the cylinder ,Right now ; Calculate the obstacle sphere bounding box on the cylinder axis The projection area interval in the direction [ , ],like , ]∩[0, ]≠ , If it is empty, the distance from the center of the obstacle sphere to the axis of the cylinder is calculated. The shortest distance d; otherwise there is no collision; where, , are the lower and upper limits of the projection area respectively; If d< + ,in, is the radius of the spherical bounding box of the obstacle, a collision occurs; For nodes in the optimized path With Node The arc path is divided into n equal parts to generate n arc segments, where the value of n is determined by the maximum radius of the tower crane. The chord length of each arc segment is used to replace the corresponding arc, and the corresponding cylinder is constructed to perform collision detection on each arc segment. The cylinder construction method and the collision detection method of each arc segment are the same as those of the straight path. If the current optimized path does not meet the safety detection requirements, the next suboptimal path is selected as the optimal path for optimization, and then a safety collision detection is performed until the safety is met.

9. A tower crane path planning device based on polar coordinate recursive partitioning, characterized in that: include: An acquisition unit is used to acquire relevant information of the lifting point, target point, tower crane, hoisted object and obstacles; And establish a polar coordinate system with the tower crane position as the center of the circle; A tower crane lifting range unit, used to obtain the tower crane lifting range represented by a circular cylinder according to the center of the circle, the maximum radius of the tower crane and the minimum radius of the tower crane; A sub-body division unit is used to dynamically and recursively divide the lifting range of the tower crane in different ways according to the relevant information of the hoisted object and obstacles, until the division termination condition is reached, and a plurality of sub-bodies are generated; The new sub-body generation unit is used to determine whether the lifting point and the target point are on the outer boundary box of the sub-body. If not, a fan-shaped cylinder is generated by taking the lifting point and the target point as vertices to obtain a new sub-body under the condition that the division termination condition is met; The path optimization unit is used to calculate the priority of each node in the path according to the lifting point and the target point, using the A* algorithm combined with the cost function, and select the node with the smallest replacement value as the optimal path and optimize it to obtain the optimized path; The path planning unit is used to perform collision detection between obstacles and the suspended objects in the sub-body area when the optimized path passes through the outer boundary box of the sub-body according to the optimized path; if the detection result does not meet the requirements, the next suboptimal path is selected for optimization, and then the collision detection is performed again until the result meets the requirements, and the optimized path is used as the planned path of the tower crane to control the operation of the tower crane.

10. A tower crane path planning device based on polar coordinate recursive partitioning, characterized in that: It includes a processor and a memory, wherein a computer program is stored in the memory, and the computer program can be executed by the processor to implement a tower crane path planning method based on polar coordinate recursive partitioning as described in any one of claims 1-8.

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