Portal frame welding robot path planning method and system based on improved RRT algorithm

Abstract

The invention discloses a portal frame welding robot path planning method and system based on an improved RRT algorithm, and relates to the technical field of robot path planning. The method comprises the steps that welding operation range data of a portal frame double-mechanical-arm welding robot and relative position data of the welding robot and a to-be-welded plate component are received; welding seam information data of the welding plate component is received. A welding plate component is divided into a plurality of operation areas by considering the operation range of the robot and the welding seam distribution of the component; secondly, a constraint degree concept is introduced by considering welding deformation, and welding sequence planning is conducted on multiple pairs of welding seams in each area; and finally, based on results of operation area division and welding sequence planning, an improved RRT algorithm is adopted to plan a welding robot operation end space collision-free trajectory, the improved RRT algorithm fuses improved measures of RRT * and RRT-connect algorithms, an adaptive sampling space and a sampling point preferential mechanism are added, the path length is effectively shortened, and the path planning time is effectively shortened.

Description

Technical Field

[0001] The present invention relates to the technical field of robot path planning, and in particular to a gantry welding robot path planning method and system based on an improved RRT algorithm. Background Art

[0002] The construction process of large bridges requires a large number of prefabricated steel components. How to quickly and accurately weld the components directly determines the construction progress and quality. When welding with welding robots in the automated production of steel components, the traditional manual teaching programming method is inefficient. The lack of support for automatic path planning methods has hindered the development of autonomous intelligent operation of equipment.

[0003] At present, when welding robots are used for automated welding in steel component prefabrication factories, the equipment is mostly controlled by manual teaching programming. This control method is simple and easy to operate, but when faced with welding tasks of different components, frequent programming will result in high time consumption and deployment costs, and the degree of automation needs to be improved. At the same time, when dealing with welding tasks of large-size components, a single welding robot device is difficult to handle, and it is necessary to cooperate with the gantry system to move the spatial position to achieve a large range of operations. The gantry robot welding system brings more degrees of freedom to the welding robot to improve the flexibility of the welding operation, but it also adds additional tasks to the operation path planning, namely the allocation of the welding area and the planning of the welding robot arm operation stop point. For this reason, we propose a gantry welding robot path planning method and system based on the improved RRT algorithm. Summary of the invention

[0004] The purpose of the present invention is to provide a gantry welding robot path planning method and system based on an improved RRT algorithm, which can fill the gap in the current construction robot path planning technology and methods and solve the large-size plate unit welding path planning problem of the gantry welding robot.

[0005] According to the first aspect of the present invention, in order to achieve the above-mentioned purpose, the present invention provides the following technical solution: a gantry welding robot path planning method based on an improved RRT algorithm, the specific steps comprising:

[0006] S1. Receive the welding operation range data of the gantry dual-arm welding robot and the relative position data of the welding robot and the plate component to be welded;

[0007] S2. Receive the weld information data of the welded plate component, and formulate multiple welding robot arm operation stop points according to the weld information data to form a corresponding operation area to cover all welds;

[0008] S3. Eliminate redundant operation stops to form multiple operation areas;

[0009] S4. Performing operation traversal sequence planning for multiple operation areas;

[0010] S5. Plan the welding sequence and welding direction of the welds in each area in accordance with the order of traversal of the work area;

[0011] S6. Determine the starting and ending positions of the end of the welding gun of the welding robot arm at each operation stop point;

[0012] S7. According to the welding sequence planning results of the welds in each working area, determine the starting and ending points of each spatial collision-free movement of the end of the welding gun of the welding robot arm;

[0013] S8. Determine the adaptive sampling space according to the spatial position of the current operation area;

[0014] S9. Sampling multiple spatial points in the current adaptive sampling space, and selecting the optimal spatial point as the final sampling point;

[0015] S10. Generate two random trees from the starting point and the end point of the current trajectory to be planned, the random tree at the starting point extends to the sampling point to generate a new node 1, and then the random tree from the end point extends to the node to generate another new node 2;

[0016] S11. Determine whether node 1 and node 2 can be directly connected without collision. If not, exchange the values ​​of the random tree of the starting point and the random tree of the ending point and return to S9. If so, a collision-free trajectory is formed between the starting point and the ending point.

[0017] S12. Repeat steps S9-S11 to form a collision-free trajectory for all spaces in the current operating area;

[0018] S13. Repeat steps S8-S12 to form a spatial collision-free trajectory in the entire working area.

[0019] Furthermore, the principle for setting the operation stop point in S2 is:

[0020] The length of the weld pair is smaller than the operating radius of the welding robot arm, and the plane position of the operating stop point is arranged at the end of all weld pairs.

[0021] Furthermore, the method for deleting redundant operation stops in S3 is as follows:

[0022] (1) First, the proposed work stop points are arranged in a horizontal and vertical alignment manner, and then deleted from the vertical and horizontal directions. When deleting vertically, the first row position is determined, and all welds within the working range of the first row of work stop points are found. If these welds are within the working range of the second row of work stop points, the first row of work stop points are deleted, otherwise they are retained. Similarly, each row of work stop points is determined in turn to determine whether to delete them;

[0023] (2) When deleting horizontally, first determine the position of the first row, find all welds within the working range of the first row of work stops, and if these welds are within the working range of the second row of work stops, delete the first row of work stops; otherwise, keep them. Similarly, determine whether to delete each row of work stops in turn.

[0024] Furthermore, the operation traversal sequence planning is performed for multiple operation areas, as follows:

[0025] (1) First, the distance between each operation stop point and the center point of the weld plate component is calculated, and the operation point closest to the center of the weld plate component is set as the first operation point with the highest operation priority;

[0026] (2) After the welding operation is completed in the first operation area, one or more operation stops closest to the first operation area are selected as the next round of traversal targets, and the welding operation is performed at the corresponding operation stops in turn. The subsequent operation rounds are performed in the same way.

[0027] (3) When there are multiple work points, the work point closest to the last traversed work point in the previous round of work is selected as the first traversal object of this round of work until all work stop points are traversed.

[0028] Furthermore, the method for planning the welding sequence of the welds in the working area in S5 is as follows:

[0029] (1) The initial constraint values ​​of all weld end points are set to 0. At the beginning of welding, the weld end point temporarily located at the center of the working area is used as the starting point, and its initial constraint value is set to 1;

[0030] (2) Each time welding is started, the endpoint with the highest constraint degree is selected. After each pair of welds is completed, the constraint degree at both ends is increased by 1. When there are multiple endpoints with the highest constraint degree, the endpoint closest to the current welding end point is selected as the starting point for the next pair of welds.

[0031] Furthermore, the sampling of multiple spatial points in the current adaptive sampling space is specifically expressed as follows:

[0032] X rand ∈X adapt ∈X free

[0033]

[0034] Where, X rand is the sampling point; X s , Y s , X g , Y g , X r , Y r , Z r Represents the starting node x start , target node x goal , and sampling point X rand Coordinate values ​​in the same three-dimensional coordinate system; Lim free，x , Lim free，y , Lim free，z Indicates barrier-free space X free The boundary of the adaptive space; e represents the expansion value of the adaptive space relative to the coordinates of the start and end points.

[0035] Furthermore, the optimal sampling point in S9 is obtained by calculating the offset distance Od of each sampling point, as follows:

[0036]

[0037] Where X s , Y s , X g , Y g , X r , Y r , Z r Represents the starting node x start , target node x goal , and sampling point X rand Coordinate values ​​in the same three-dimensional coordinate system;

[0038] The spatial point with the smallest offset distance Od is selected as the sampling point.

[0039] Furthermore, a spatial collision-free trajectory is formed in the simulation software, which is MATLABR2022b.

[0040] According to a second aspect of the present invention, the present invention provides a bridge steel box plate welding path planning system based on an improved RRT algorithm, which is used to implement the above-mentioned gantry welding robot path planning method based on the improved RRT algorithm, comprising:

[0041] The first receiving module is used to receive the welding operation range data of the gantry dual-arm welding robot and the relative position data of the welding robot and the plate component to be welded;

[0042] The second receiving module is used to receive the weld information data of the welded plate component, and to formulate a plurality of welding robot arm operation stop points according to the weld information data to form a corresponding operation area to cover all welds;

[0043] The deletion module is used to delete redundant operation stops to form multiple operation areas;

[0044] The first planning module is used to plan the operation traversal sequence for multiple operation areas;

[0045] The second planning module is used to plan the welding sequence and welding direction of the welds in each area in accordance with the traversal order of the operation area;

[0046] The third planning module is used to determine the starting and ending positions of the welding robot arm's welding gun end at each operation stop point;

[0047] The fourth planning module is used to determine the starting and ending positions of each spatial collision-free movement of the welding gun end of the welding robot arm according to the welding sequence planning results of the welds in each working area;

[0048] A sampling module, used to determine the adaptive sampling space according to the spatial position of the current operation area;

[0049] A selection module is used to sample multiple spatial points in the current adaptive sampling space and select the optimal spatial point as the final sampling point;

[0050] A generation module is used to generate two random trees from the starting point and the end point of the current trajectory to be planned. The random tree at the starting point extends to the sampling point to generate a new node 1, and then the random tree from the end point extends to the node to generate another new node 2;

[0051] A judgment module is used to judge whether node 1 and node 2 can be directly connected without collision. If not, the values ​​of the random tree of the starting point and the random tree of the ending point are exchanged and returned to the selection module. If so, a collision-free trajectory between the starting point and the ending point is formed;

[0052] The spatial collision-free trajectory module is used to form spatial collision-free trajectories in the current operating area and all other operating areas.

[0053] According to a third aspect of the present invention, the present invention provides a terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that a computer program capable of running on the processor is stored in the memory, and when the processor loads and executes the computer program, the above-mentioned gantry welding robot path planning method based on the improved RRT algorithm is adopted.

[0054] The present invention has at least the following beneficial effects:

[0055] The present invention aims at large-sized plate unit components. First, the working performance of the welding equipment is considered to divide the working area to realize the gradual welding of the components. The concept of constraint degree is introduced in the weld sequence planning, so that the planning results are more in line with the process requirements in actual operations. In the local space obstacle avoidance path planning, the improved RRT algorithm incorporates the superior mechanisms of the RRT* and RRT-connect algorithms, and adds an adaptive sampling space and sampling point selection mechanism, which effectively limits the sampling points to the vicinity of the path start and end points, improves the efficiency of path planning and reduces the path length, fills the gap in the current construction robot path planning technology and methods, and solves the path planning problem of the gantry welding robot when performing welding operations on large plate unit components of bridge steel boxes.

[0056] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a schematic diagram of the process of the path planning method of the present invention;

[0058] Figure 2 It is a schematic diagram of the flow of the spatial trajectory planning algorithm of the present invention;

[0059] Figure 3 This is a schematic diagram of the results of path planning in a single operating area in an embodiment of the present invention.

[0060] Figure 4 It is a schematic diagram of the result of overall path planning for welding operation of welding plate components in an embodiment of the present invention. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0062] RRT algorithm, full name Rapidly Exploring Random Tree, is a data structure and algorithm for effectively searching high-dimensional non-convex space. It is originally designed to solve the problems of integrity planning, non-integrity planning and motion dynamics in uncertain environments. It is particularly suitable for fields such as path planning. The RRT algorithm constructs a tree in a special incremental way, which can quickly shorten the expected distance between a random state point and the tree. The algorithm process includes initializing the starting point and end point, entering the loop for random sampling, finding the node closest to the random point, and then growing the tree. The nearest node is connected to the random point as the direction of tree growth, setting the step size to generate a new node, and repeating this process until the new node approaches the end point, and finally finding the path from the starting point to the end point.

[0063] The RRT Connect algorithm is an improved Rapidly Expanding Random Tree (RRT) algorithm. Its main feature is to generate random trees at the starting point and the end point for bidirectional expansion. The algorithm includes the following steps:

[0064] Initialization: Select a starting point as the root node of the tree;

[0065] Sampling: randomly sample a point in the state space;

[0066] Find the nearest node: find the node closest to the sampling point in the existing tree;

[0067] Extension: Extend a certain distance from the nearest node toward the sampling point to form a new node. If the new node does not collide with obstacles, it will be added to the tree.

[0068] Connect: Check if the new node is close enough to the target point, if so, a path is considered to have been found;

[0069] Iteration: Repeat the above process until a path is found or the iteration limit is reached.

[0070] Embodiment 1:

[0071] See also Figure 1-Figure 4 The present invention provides a technical solution: a path planning method for a gantry welding robot based on an improved RRT algorithm, and the specific steps include the following:

[0072] S1. Receive the welding operation range data of the gantry dual-arm welding robot and the relative position data of the welding robot and the plate component to be welded;

[0073] S2. receiving weld information data of the weld plate component, wherein the weld information data includes the position distribution and geometric data of the weld, and formulating a plurality of welding robot arm operation stop points according to the weld information data to form a corresponding operation area to cover all welds;

[0074] The principles for setting the operation stop points are as follows:

[0075] Considering that the length of a weld pair is generally smaller than the operating radius of the welding robot, all welds can be included in the operating range by arranging the plane position of the operating stop point at the end of all weld pairs;

[0076] S3. Eliminate redundant operation stops and form multiple operation areas, as follows:

[0077] (S31) First, the proposed work stop points are arranged in a horizontal and vertical alignment manner, and then the deletion operation is performed vertically and horizontally. When deleting vertically, the first row position is determined, and all welds within the working range of the first row of work stop points are found. If these welds are within the working range of the second row of work stop points, the first row of work stop points are deleted, otherwise they are retained. Similarly, each row of work stop points is determined in turn to determine whether to delete them;

[0078] (S32) When deleting horizontally, first determine the first row position, find all welds within the working range of the first row of work stops, if these welds are within the working range of the second row of work stops, delete the first row of work stops, otherwise keep them, and similarly determine whether to delete each row of work stops in turn;

[0079] S4. Plan the operation traversal sequence for multiple operation areas, as follows:

[0080] (S41) firstly calculating the distance between each operation stop point and the center point of the weld plate component, and setting the operation point closest to the center of the weld plate component as the first operation point with the highest operation priority;

[0081] (S42) After the welding operation is completed in the first operation area, one or more operation stops closest to the first operation area are selected as the next round of traversal targets, and the welding operation is performed at the corresponding operation stops in turn. The subsequent operation rounds are performed in the same manner;

[0082] (S43) When there are multiple work points, the work point closest to the last traversed work point in the previous round of work is selected as the first traversal object of the current round of work, until all work stop points are traversed;

[0083] S5. Plan the welding sequence and welding direction of each weld in each area in accordance with the order of traversal of the work area, as follows:

[0084] (S51) setting the initial value of the constraint degree of all weld end points to 0, and setting the weld end point temporarily located at the center of the working area at the beginning of the welding operation as the starting point, and setting its initial constraint degree to 1;

[0085] (S52) Each time welding is performed, the end point with the highest constraint degree is started. After each pair of welds is welded, the constraint degrees at both ends are increased by 1. When there are multiple end points with the highest constraint degrees, the end point closest to the current welding end point is selected as the starting point of the next pair of welds.

[0086] S6. Determine the starting and ending positions of the end of the welding gun of the welding robot arm at each operation stop point;

[0087] S7. According to the welding sequence planning results of the welds in each working area, determine the starting and ending points of each spatial collision-free movement of the end of the welding gun of the welding robot arm;

[0088] S8. Determine the adaptive sampling space according to the spatial position of the current operation area;

[0089] S9. Sampling multiple spatial points in the current adaptive sampling space, and selecting the optimal spatial point as the final sampling point;

[0090] Among them, sampling of multiple spatial points is performed in the current adaptive sampling space, which is specifically expressed as follows:

[0091] X rand ∈X adapt ∈X free

[0092]

[0093] Where, X rand is the sampling point; X s , Y s , X g , Y g , X r , Y r , Z r Represents the starting node x start , target node x goal , and sampling point X rand Coordinate values ​​in the same three-dimensional coordinate system;

[0094] Lim free，x , Lim free，y , Lim free，z Indicates barrier-free space X free The boundary of the adaptive space; e represents the expansion value of the adaptive space relative to the coordinates of the starting and ending points;

[0095] Furthermore, the optimal sampling point is obtained by calculating the offset distance Od of each sampling point, as follows:

[0096]

[0097] Where X s , Y s , X g , Y g , X r , Y r , Z r Represents the starting node x start , target node x goal , and sampling point X rand Coordinate values ​​in the same three-dimensional coordinate system;

[0098] Select the spatial point with the smallest offset distance Od as the sampling point;

[0099] S10. Generate two random trees from the starting point and the end point of the current trajectory to be planned, the random tree at the starting point extends to the sampling point to generate a new node 1, and then the random tree from the end point extends to the node to generate another new node 2;

[0100] S11. Determine whether node 1 and node 2 can be directly connected without collision. If not, exchange the values ​​of the random tree of the starting point and the random tree of the ending point and return to S9. If so, a collision-free trajectory is formed between the starting point and the ending point.

[0101] It should be noted that the spatial collision-free trajectory was formed in the simulation software, which was MATLABR2022b;

[0102] S12. Repeat steps S9-S11 to form a collision-free trajectory for all spaces in the current operating area;

[0103] S13. Repeat steps S8-S12 to form a spatial collision-free trajectory in the entire working area.

[0104] like Figure 2 As shown, the present invention is further described below in conjunction with specific embodiments:

[0105] Step 1: The operating area radius of the gantry dual-manipulator welding equipment is determined by the equipment model and the height of the base position. In this embodiment, the operating radius of the welding robot arm is 1m, and the plate component to be welded is located directly below the welding equipment;

[0106] Step 2: According to the welding plate component information, weld data and weld position distribution information, it can be known that the longest weld length is 0.5m, which is smaller than the radius of the robot's operating range. Therefore, the ends of all weld pairs are used as the proposed operating stops to include all welds in the operating range.

[0107] Step 3: For the outermost operation point, since the weld located at the outermost side of the weld plate component has another endpoint that has been proposed as an operation stop point, it can be eliminated, and the remaining operation points are deleted in turn in the horizontal and vertical directions, and finally the number of operation stop points is reduced to 15;

[0108] Step 4, by calculating the distance between each work stop point and the center point of the welding plate component, the work point closest to the center of the welding plate component is set as the first work point with the highest work priority; after completing the welding work in the first work area, select one or more work stop points closest to it as the next round of traversal targets, and move to the corresponding work stop points in turn to perform the second round of welding work; after the second round of work, continue to calculate the distance between the remaining untraversed work stop points and the first work stop point, select one or more nearest work stop points as the next round of traversal targets, when there are multiple work points, select the one closest to the last traversed work point in the previous round of work as the first traversal object of this round of work; similarly, plan the next round of work in the previous step until all work points are traversed and the traversal order of all work stop points is obtained;

[0109] Step 5, plan the welding sequence for the welds in the working area covered by each working stop point in turn, first temporarily locate the weld endpoint in the center of the working area as the starting point, set its initial constraint value to 1, there are 4 pairs of unoperated welds adjacent to the starting point, the first step of welding can weld these 4 pairs of welds in turn, and update the constraint value of its endpoint when each pair of welds is completed. After completing the welding of the weld adjacent to the first starting point, according to the current constraint values ​​of each endpoint, select the endpoint with the maximum constraint value as the next starting point. When there are multiple endpoints with the maximum constraint value, select the one closest to the end point of the previous step as the next starting point until all welds are welded, and obtain the welding sequence of the welds in each working area;

[0110] Step 6, determining the spatial position of the welding gun end of the welding equipment at each operation stop point where the welding gun end starts working and finally returns;

[0111] Step 7, according to the welding sequence planning results of the weld seams in the working area below each working stop point, determine the starting and ending point coordinates of the subsequent spatial movement trajectory planning of the end of the welding gun;

[0112] Step 8, according to the starting and ending point positions of the end of the welding gun each time the spatial movement planning is performed, the adaptive sampling space is set, and the adaptive space extension value e is set to 250mm;

[0113] Step 9, random tree extension node sampling is performed in the adaptive sampling space, and the number of sampling points N is set to 10;

[0114] Step 10: Generate two random trees from the starting point and the end point of the current trajectory to be planned. The random tree at the starting point extends to the sampling point to generate a new node, and then extends from the random tree at the end point to the node to generate another new node. The search step size is set to 40.

[0115] Step 11, determine whether the two newly generated nodes can be directly connected without collision. If not, exchange the values ​​of the two random trees and return to step 9; if yes, a collision-free trajectory between the start and end points is formed;

[0116] Step 12, repeat steps 9-11 to form all spatial collision-free trajectories in the current operation area, such as Figure 2 As shown;

[0117] Step 13, repeat steps 8-12 to form a spatial collision-free trajectory in the entire operation area, such as Figure 3 As shown;

[0118] In summary, the present invention proposes a method for dividing the working area taking into account the working range of the gantry welding robot to achieve step-by-step welding, and takes into account the needs of actual welding operations to control the welding deformation. The concept of constraint degree is introduced for planning the weld sequence. In addition, the sampling-based RRT algorithm is often used to plan the obstacle avoidance trajectory of the robot arm working end in three-dimensional space. The present invention integrates the RRT* and RRT-connect algorithms to improve the basic RRT algorithm, adds an adaptive sampling space and sampling point selection mechanism, and forms an improved RRT algorithm for planning the spatial movement trajectory of the welding end of the welding robot arm. The added improvement measures improve the efficiency of the path search by limiting the sampling space of each search. At the same time, the improved algorithm performs multiple sampling in each step of the search, and then selects the sampling point closest to the vertical plane passing through the starting point and the target point, effectively shortening the path length.

[0119] Embodiment 2:

[0120] This embodiment provides a bridge steel box plate welding path planning system based on an improved RRT algorithm, which is used to implement the gantry welding robot path planning method based on the improved RRT algorithm described in the first embodiment, including:

[0121] The first receiving module is used to receive the welding operation range data of the gantry dual-arm welding robot and the relative position data of the welding robot and the plate component to be welded;

[0122] The second receiving module is used to receive the weld information data of the welded plate component, and to formulate a plurality of welding robot arm operation stop points according to the weld information data to form a corresponding operation area to cover all welds;

[0123] The deletion module is used to delete redundant operation stops to form multiple operation areas;

[0124] The first planning module is used to plan the operation traversal sequence for multiple operation areas;

[0125] The second planning module is used to plan the welding sequence and welding direction of the welds in each area in accordance with the traversal order of the operation area;

[0126] The third planning module is used to determine the starting and ending positions of the welding robot arm's welding gun end at each operation stop point;

[0127] The fourth planning module is used to determine the starting and ending positions of each spatial collision-free movement of the welding gun end of the welding robot arm according to the welding sequence planning results of the welds in each working area;

[0128] A sampling module, used to determine the adaptive sampling space according to the spatial position of the current operation area;

[0129] A selection module is used to sample multiple spatial points in the current adaptive sampling space and select the optimal spatial point as the final sampling point;

[0130] A generation module is used to generate two random trees from the starting point and the end point of the current trajectory to be planned. The random tree at the starting point extends to the sampling point to generate a new node 1, and then the random tree from the end point extends to the node to generate another new node 2;

[0131] A judgment module is used to judge whether node 1 and node 2 can be directly connected without collision. If not, the values ​​of the random tree of the starting point and the random tree of the ending point are exchanged and returned to the selection module. If so, a collision-free trajectory between the starting point and the ending point is formed;

[0132] The spatial collision-free trajectory module is used to form spatial collision-free trajectories in the current operating area and all other operating areas.

[0133] Specifically, the above-mentioned first receiving module, second receiving module, deletion module, first planning module, second planning module, third planning module, fourth planning module, sampling module, selection module, generation module, judgment module and spatial collision-free trajectory module can be embedded in a computer processing system, and the computer calls the above-mentioned modules to complete the task of planning the welding path according to the above-mentioned gantry welding robot path planning method based on the improved RRT algorithm; the above-mentioned first receiving module, second receiving module, deletion module, first planning module, second planning module, third planning module, fourth planning module, sampling module, selection module, generation module, judgment module and spatial collision-free trajectory module can perform operations according to the specific steps given in the gantry welding robot path planning method based on the improved RRT algorithm.

[0134] It should be noted that it should be understood that the division of the various modules of the above system is only the division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated, and these modules can all be implemented in the form of software calling through processing elements; they can also be all implemented in the form of hardware; some modules can also be implemented in the form of software calling through processing elements, and some modules can be implemented in the form of hardware. For example, the sampling module can be a separately established processing element, or it can be integrated in a chip of the above device. In addition, it can also be stored in the memory of the above device in the form of program code, and called and executed by a processing element of the above device. The implementation of other modules is similar. In addition, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element described here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each module can be completed by the hardware integrated logic circuit in the processor element or the instructions in the form of software.

[0135] For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits (ASIC), or one or more digital singnal processors (DSP), or one or more field programmable gate arrays (FPGA). For another example, when a module is implemented in the form of a processing element scheduling program code, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processors that can call program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0136] Embodiment three:

[0137] The present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the memory stores a computer program capable of running on the processor, and when the processor loads and executes the computer program, the above-mentioned gantry welding robot path planning method based on the improved RRT algorithm is adopted.

[0138] It should be noted that the terminal device can be a computer device such as a desktop computer, a laptop computer or a cloud server, and the terminal device includes but is not limited to a processor and a memory. For example, the terminal device can also include input and output devices, network access devices and buses.

[0139] Furthermore, the processor may adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. may also be adopted. The general-purpose processor may adopt a microprocessor or any conventional processor, etc., and the present application does not impose any restrictions on this.

[0140] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0141] For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. When an element is referred to as being "assembled on", "installed on", "fixed on" or "set on" another element, it can be directly on the other element or there can also be a centered element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be a centered element at the same time. The terms "vertical", "horizontal", "up", "down", "left", "right" and similar expressions used herein are only for illustrative purposes and are not intended to be the only implementation method.

[0142] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0143] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

Claims

1. A gantry welding robot path planning method based on an improved RRT algorithm is characterized in that: The specific steps include: S1. Receive the welding operation range data of the gantry dual-arm welding robot and the relative position data of the welding robot and the plate component to be welded; S2. Receive the weld information data of the welded plate component, and formulate multiple welding robot arm operation stop points according to the weld information data to form a corresponding operation area to cover all welds; S3. Eliminate redundant operation stops to form multiple operation areas; S4. Performing operation traversal sequence planning for multiple operation areas; S5. Plan the welding sequence and welding direction of the welds in each area in accordance with the order of traversal of the work area; S6. Determine the starting and ending positions of the end of the welding gun of the welding robot arm at each operation stop point; S7. According to the welding sequence planning results of the welds in each working area, determine the starting and ending points of each spatial collision-free movement of the end of the welding gun of the welding robot arm; S8. Determine the adaptive sampling space according to the spatial position of the current operation area; S9. Sampling multiple spatial points in the current adaptive sampling space, and selecting the optimal spatial point as the final sampling point; S10. Generate two random trees from the starting point and the end point of the current trajectory to be planned, the random tree at the starting point extends to the sampling point to generate a new node 1, and then the random tree from the end point extends to the node to generate another new node 2; S11. Determine whether node 1 and node 2 can be directly connected without collision. If not, exchange the values ​​of the random tree of the starting point and the random tree of the ending point and return to S9. If so, a collision-free trajectory is formed between the starting point and the ending point. S12. Repeat steps S9-S11 to form a collision-free trajectory for all spaces in the current operating area; S13. Repeat steps S8-S12 to form a spatial collision-free trajectory in the entire working area.

2. The gantry welding robot path planning method based on the improved RRT algorithm according to claim 1 is characterized in that: The principle for setting the operation stop point in S2 is: The length of the weld pair is smaller than the operating radius of the welding robot arm, and the plane position of the operating stop point is arranged at the end of all weld pairs.

3. The gantry welding robot path planning method based on the improved RRT algorithm according to claim 2 is characterized in that: The method for deleting redundant operation stops in S3 is as follows: (1) First, the proposed work stop points are arranged in a horizontal and vertical alignment manner, and then deleted from the vertical and horizontal directions. When deleting vertically, the first row position is determined, and all welds within the working range of the first row of work stop points are found. If these welds are within the working range of the second row of work stop points, the first row of work stop points are deleted, otherwise they are retained. Similarly, each row of work stop points is determined in turn to determine whether to delete them; (2) When deleting horizontally, first determine the position of the first row, find all welds within the working range of the first row of work stops, and if these welds are within the working range of the second row of work stops, delete the first row of work stops; otherwise, keep them. Similarly, determine whether to delete each row of work stops in turn.

4. The gantry welding robot path planning method based on the improved RRT algorithm according to claim 3 is characterized in that: The operation traversal sequence planning is carried out for multiple operation areas, as follows: (1) First, the distance between each operation stop point and the center point of the weld plate component is calculated, and the operation point closest to the center of the weld plate component is set as the first operation point with the highest operation priority; (2) After the welding operation is completed in the first operation area, one or more operation stops closest to the first operation area are selected as the next round of traversal targets, and the welding operation is performed at the corresponding operation stops in turn. The subsequent operation rounds are performed in the same way. (3) When there are multiple work points, the work point closest to the last traversed work point in the previous round of work is selected as the first traversal object of this round of work until all work stop points are traversed.

5. The gantry welding robot path planning method based on the improved RRT algorithm according to claim 4 is characterized in that: The method for planning the welding sequence of the welds in the working area in S5 is as follows: (1) The initial constraint values ​​of all weld end points are set to 0. At the beginning of welding, the weld end point temporarily located at the center of the working area is used as the starting point, and its initial constraint value is set to 1; (2) Each time welding is started, the endpoint with the highest constraint degree is selected. After each pair of welds is completed, the constraint degree at both ends is increased by 1. When there are multiple endpoints with the highest constraint degree, the endpoint closest to the current welding end point is selected as the starting point for the next pair of welds.

6. The gantry welding robot path planning method based on the improved RRT algorithm according to claim 5 is characterized in that: Sampling of multiple spatial points is performed in the current adaptive sampling space, which is specifically expressed as follows: X rand ∈X adapt ∈X free Where, X rand is the sampling point; X s , Y s , X g , Y g , X r , Y r , Z r Represents the starting node x start , target node x goal , and sampling point X rand Coordinate values ​​in the same three-dimensional coordinate system; Lim free,x , Lim free,y , Lim free,z Indicates barrier-free space X free The boundary of the adaptive space; e represents the expansion value of the adaptive space relative to the coordinates of the start and end points.

7. The gantry welding robot path planning method based on the improved RRT algorithm according to claim 6 is characterized in that: The optimal sampling point in S9 is obtained by calculating the offset distance Od of each sampling point, as follows: Where X s , Y s , X g , Y g , X r , Y r , Z r Represents the starting node x start , target node x goal , and sampling point X rand Coordinate values ​​in the same three-dimensional coordinate system; The spatial point with the smallest offset distance Od is selected as the sampling point.

8. The gantry welding robot path planning method based on the improved RRT algorithm according to claim 6 is characterized in that: The spatial collision-free trajectory is formed in a simulation software, which is MATLAB R2022b.

9. A bridge steel box plate welding path planning system based on an improved RRT algorithm, used to implement the gantry welding robot path planning method based on an improved RRT algorithm as described in any one of claims 1 to 8, characterized in that: include: The first receiving module is used to receive the welding operation range data of the gantry dual-arm welding robot and the relative position data of the welding robot and the plate component to be welded; The second receiving module is used to receive the weld information data of the welded plate component, and to formulate a plurality of welding robot arm operation stop points according to the weld information data to form a corresponding operation area to cover all welds; The deletion module is used to delete redundant operation stops to form multiple operation areas; The first planning module is used to plan the operation traversal sequence for multiple operation areas; The second planning module is used to plan the welding sequence and welding direction of the welds in each area in accordance with the traversal order of the operation area; The third planning module is used to determine the starting and ending positions of the welding robot arm's welding gun end at each operation stop point; The fourth planning module is used to determine the starting and ending positions of each spatial collision-free movement of the welding gun end of the welding robot arm according to the welding sequence planning results of the welds in each working area; A sampling module, used to determine the adaptive sampling space according to the spatial position of the current operation area; A selection module is used to sample multiple spatial points in the current adaptive sampling space and select the optimal spatial point as the final sampling point; A generation module is used to generate two random trees from the starting point and the end point of the current trajectory to be planned. The random tree at the starting point extends to the sampling point to generate a new node 1, and then the random tree from the end point extends to the node to generate another new node 2; A judgment module is used to judge whether node 1 and node 2 can be directly connected without collision. If not, the values ​​of the random tree of the starting point and the random tree of the ending point are exchanged and returned to the selection module. If so, a collision-free trajectory between the starting point and the ending point is formed; The spatial collision-free trajectory module is used to form spatial collision-free trajectories in the current operating area and all other operating areas.

10. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: The memory stores a computer program that can be run on the processor. When the processor loads and executes the computer program, the gantry welding robot path planning method based on the improved RRT algorithm described in any one of claims 1 to 8 is adopted.

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