Material assembly path planning method and device, medium and computer program product

Abstract

The invention discloses a material assembly path planning method and device, a medium and a computer program product. The method comprises the following steps: acquiring a material initial position, a material assembly position and a static obstacle position of a target material; generating an assembly path of the target material based on the material initial position, the material assembly position and the static obstacle position; and based on the assembly path, a movement control instruction is generated, and the movement control instruction is used for controlling the grabbing device to move the target material from the initial position to the assembly position along the assembly path. By accurately obtaining the initial position and the assembly position of the target material and the position information of the static obstacle, the assembly path of the material from the initial position to the assembly position can be planned, interference conflict with the static obstacle can be avoided, safe, efficient and automatic material carrying is achieved, the production efficiency is improved, and the production cost is reduced. The intelligent and automatic level of material assembly is improved, the labor cost is reduced, and the technical problem that the optimal path of material assembly cannot be obtained is solved.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving, and in particular, to a method, device, medium, and computer program product for material assembly path planning. Background Art

[0002] Traditional robot assembly systems rely on the fixed positions and movement modes of the assembly mechanisms. The assembly tasks are achieved by workpiece positioning and the movement of the assembly tools. The assembly efficiency and quality are affected by factors such as the movement control accuracy of the assembly mechanism, the position accuracy of the assembly tool, and the load capacity of the assembly mechanism. Due to the single movement mode of the assembly mechanism, the assembly path planning and control methods are relatively simple. Usually, path planning algorithms are used to generate the basic path, and the assembly mechanism is controlled to move to the end position of the path. During the assembly process, the movement path of the assembly tool is fixed. By detecting the proximity between the assembly tool and the workpiece, it is judged whether the assembly action is completed. The assembly result depends on the movement accuracy of the assembly mechanism. The movement accuracy of the assembly mechanism is affected by factors such as the structure of the assembly mechanism, the position accuracy of the assembly mechanism, the load capacity of the assembly mechanism, the physical limitations of the assembly tool, abnormal movement or vibration during the assembly process, etc., resulting in deviations in the assembly result and reducing the assembly quality. In the prior art, to solve the problem of optimal path confirmation, especially for path planning in complex environments, common technical means include, but are not limited to, the Artificial Potential Field Method, A* algorithm, Dijkstra algorithm, and Dynamic Programming, etc., but they all have their limitations, either unable to find the global optimal path, or unable to handle high-dimensional space planning problems, with low computational efficiency.

[0003] In view of the above problems, no effective solution has been proposed yet. Summary of the Invention

[0004] Embodiments of the present invention provide a method, device, medium, and computer program product for material assembly path planning to at least solve the technical problem of being unable to obtain the optimal path for material assembly.

[0005] According to one aspect of the embodiments of the present invention, a method for material assembly path planning is provided, including: obtaining the initial position of the target material, the material assembly position, and the static obstacle positions; generating an assembly path for the target material based on the initial position of the material, the material assembly position, and the static obstacle positions; generating a movement control instruction based on the assembly path, where the movement control instruction is used to control the grasping device to move the target material from the initial position to the assembly position along the assembly path.

[0006] Optionally, an assembly path for the target material is generated based on the initial position of the material, the assembly position of the material, and the positions of static obstacles, including: generating a first environment model based on the initial position of the material, the assembly position of the material, and the positions of static obstacles; generating a first path exploration tree based on the first environment model, where the first path exploration tree includes at least a first root node and a first target node, the first root node is used to represent the initial position of the material, and the first target node is used to represent the assembly position of the material; generating an assembly path based on the first path exploration tree using the RRT algorithm, and the assembly path is used to provide a path for the target material to move from the first root node to the first target node.

[0007] Optionally, the method further includes: obtaining the initial position of the target material, the initial station information of the grasping device, and the positions of static obstacles; generating a grasping path for the target material based on the initial station information, the initial position of the target material, and the positions of static obstacles; generating a grasping control instruction based on the grasping path, and the grasping control instruction is at least used to control the grasping device to move along the grasping path.

[0008] Optionally, when generating a grasping path for the target material based on the initial station information, the initial position of the target material, and the positions of static obstacles, the method further includes: generating a second environment model based on the initial station information, the initial position of the target material, and the positions of static obstacles; generating a second path exploration tree based on the second environment model, where the second path exploration tree includes at least a second root node and a second target node, the second root node is used to represent the initial station information of the grasping device, and the target node is used to represent the initial position of the material; generating a grasping path based on the second path exploration tree using the RRT algorithm, and the grasping path is used to provide a path for the grasping device to move from the second root node to the second target node.

[0009] Optionally, the method further includes: obtaining the real-time position information of the dynamic obstacle, and predicting the movement path of the dynamic obstacle based on the real-time position information of the dynamic obstacle; in the case where it is determined that the movement path of the dynamic obstacle overlaps at least partially with the assembly path of the target material, generating a new assembly path for the target material, and the new assembly path is used to avoid the movement path of the dynamic obstacle; controlling the grasping device to move along the new assembly path to the assembly position.

[0010] Optionally, generating a new assembly path for the target material includes: obtaining the real-time position information of the target material; generating a new assembly path for the target material using the RRT algorithm based on the movement path of the dynamic obstacle, the real-time position information of the target material, and the assembly position information.

[0011] Optionally, based on the first path exploration tree, an assembly path is generated using the RRT algorithm, including: obtaining the position of the exploration node based on the first path exploration tree; determining whether the position of the exploration node overlaps with the position of the static obstacle; generating an exploration node when it is determined that the position of the exploration node does not overlap with the position of the static obstacle; or re-obtaining the position of the exploration node when it is determined that the position of the exploration node overlaps with the position of the static obstacle; generating an assembly path based on the first root node, the first target node, and the exploration node.

[0012] According to another aspect of the embodiments of the present invention, there is also provided a device for planning a material assembly path, including: an acquisition module, where the acquisition module is used to acquire the initial position of the target material, the material assembly position, and the position of the static obstacle; a path generation module, where the path generation module is used to generate an assembly path of the target material based on the initial position of the material, the material assembly position, and the position of the static obstacle; a control instruction generation module, where the control instruction generation module is used to generate a movement control instruction based on the assembly path, and the movement control instruction is used to control the gripping device to move the target material from the initial position to the assembly position along the assembly path.

[0013] According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium in which a computer program is stored, where the computer program is configured to execute the above-mentioned material assembly path planning method when running.

[0014] According to another aspect of the present application, there is also provided a computer program product, including computer instructions, where the computer instructions implement the steps of the above-mentioned material assembly path planning method when executed by a processor.

[0015] In the embodiments of the present invention, the initial position of the target material, the material assembly position, and the position of the static obstacle are acquired; an assembly path of the target material is generated based on the initial position of the material, the material assembly position, and the position of the static obstacle; a movement control instruction is generated based on the assembly path, and the movement control instruction is used to control the gripping device to move the target material from the initial position to the assembly position along the assembly path. By accurately acquiring the initial position and assembly position of the target material, as well as the position information of the static obstacle, the assembly path of the material from the initial position to the assembly position can be effectively planned, interference and conflicts with static obstacles can be avoided, safe, efficient, and automated material handling can be achieved, production efficiency can be improved, the level of intelligence and automation of material assembly can be enhanced, labor costs can be reduced, and thus the technical problem of being unable to obtain the optimal path for material assembly is solved. Description of the Drawings

[0016] The accompanying drawings described herein are used to provide a further understanding of the present invention and form a part of this application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0017] Figure 1 is a hardware structure block diagram of a computer terminal for a material assembly path planning method according to an embodiment of the present invention;

[0018] Figure 2 is a flowchart of a material assembly path planning method according to an alternative embodiment of the present invention;

[0019] Figure 3 is a structure block diagram of a material assembly path planning device according to an embodiment of the present invention. Detailed implementation manners

[0020] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0021] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned accompanying drawings are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order different from those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0022] According to an embodiment of the present invention, an embodiment of a material assembly path planning method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from that here.

[0023] This method embodiment can be executed in a computer terminal or a similar computing device including a memory and a processor in a vehicle. Taking running on a computer terminal as an example, such asFigure 1 As shown, the computer terminal may include one or more processors 102 (the processors may include, but are not limited to, processing devices such as a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microprocessor (MCU), a field-programmable gate array (FPGA), a neural network processor (NPU), a tensor processing unit (TPU), an artificial intelligence (AI) type processor, etc.) and a memory 104 for storing data. Optionally, the above computer terminal may further include a transmission device 106 for communication functions, an input / output device 108, and a display 110. Those of ordinary skill in the art can understand that Figure 1 the structure shown is only schematic and does not limit the structure of the above computer terminal. For example, the computer terminal may further include more or fewer components than those described in the above structure, or have a configuration different from that described in the above structure.

[0024] The memory 104 can be used to store computer programs. For example, software programs and modules of application software, such as the computer program corresponding to the material assembly path planning method in the embodiments of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, implements the above-mentioned material assembly path planning method. The memory 104 may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, a flash memory, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories can be connected to the mobile terminal through a network. Examples of the above network include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0025] The transmission device 106 is used to receive or send data via a network. Specific examples of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one instance, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices through a base station and thus communicate with the Internet. In one instance, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0026] The display 110 can be, for example, a touch-screen liquid crystal display (LCD). This liquid crystal display enables the user to interact with the user interface of the mobile terminal. In some embodiments, the above-mentioned mobile terminal has a graphical user interface (GUI), and the user can perform human-computer interaction with the GUI through finger contacts and / or gestures on the touch-sensitive surface. The human-computer interaction function here optionally includes the following interactions: creating web pages, drawing, word processing, creating electronic documents, games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital videos, playing digital music, and / or web browsing, etc. The executable instructions for performing the above human-computer interaction functions are configured / stored in a computer program product or readable storage medium executable by one or more processors.

[0027] In this embodiment, a method for planning a material assembly path running on the above computer terminal is provided. Figure 2 It is a flowchart of a method for planning a material assembly path according to an embodiment of the present invention, as Figure 2 shown. The process includes the following steps:

[0028] Step S20, obtain the initial material position, material assembly position, and static obstacle position of the target material;

[0029] Specifically, the material assembly system has a collection device. Through the collection device, the initial position and assembly position of the target material can be collected, and the collection device can also collect the environmental images of the target material and the assembly station, such as the images and positions of static obstacles.

[0030] It should be noted that in step S20, the initial material position of the target material is the position where the target material is stored inside the production line. In this embodiment, the target material is a heat insulation pad, and the heat insulation pad is stored on the material rack inside the production line; the material assembly position of the target material is the assembly position of the heat insulation pad. In this embodiment, the assembly path planning is to assemble the heat insulation pad to the bottom end of the cab, so the material assembly position is the heat insulation pad assembly position at the bottom end of the cab; the static obstacle position is the positions of various static instruments at the heat insulation pad assembly station, and their positions remain unchanged during the heat insulation pad assembly process.

[0031] In an exemplary embodiment of the present application, the collection device uses a 3D (Three-Dimensional) vision camera or vision sensor to collect the initial material position and material assembly position information of the target material, and transmits the collected image data or position information to the control system for analysis and confirmation of the position of the target material and the position data to be assembled, so as to facilitate subsequent path planning.

[0032] Step S22, generate an assembly path for the target material based on the initial material position, material assembly position, and static obstacle position;

[0033] Specifically, sensors such as lidar and cameras are used to collect environmental information of the working position. After confirming the initial position of the material and the assembly position of the material, the system plans the assembly path based on the collected information through built-in algorithms.

[0034] Step S24: Generate a movement control instruction based on the assembly path. The movement control instruction is used to control the gripping device to move the target material from the initial position to the assembly position along the assembly path.

[0035] Specifically, the material assembly system also has a gripping device. The gripping device can grip the target material and carry the target material for movement. After the material assembly system analyzes and processes the data information, it determines the assembly path and generates a movement control instruction based on the assembly path. The gripping device will carry the target material from the initial position of the material to the assembly position of the material based on the movement control instruction.

[0036] In step S24, by optimizing and validating the optimization control instruction sequence through the movement control instruction, it can ensure the smooth and safe movement of the gripping device, and at the same time meet the assembly accuracy requirements. At the same time, to verify the effectiveness of the control instruction, it can be checked whether the gripping device can accurately complete the gripping and assembly tasks according to the planned path through simulation or pre-execution.

[0037] Through the above steps, obtain the initial position of the target material, the assembly position of the material, and the position of static obstacles; based on the initial position of the material, the assembly position of the material, and the position of static obstacles, generate the assembly path of the target material; based on the assembly path, generate a movement control instruction, and the movement control instruction is used to control the gripping device to move the target material from the initial position to the assembly position along the assembly path. By accurately obtaining the initial position and assembly position of the target material, as well as the position information of static obstacles, it is possible to effectively plan the assembly path of the material from the initial position to the assembly position, avoid interference and conflicts with static obstacles, achieve safe, efficient, and automated material handling, improve production efficiency, enhance the intelligence and automation level of material assembly, reduce labor costs, and thus solve the technical problem of being unable to obtain the optimal path for material assembly.

[0038] Optionally, in step S22, generating the assembly path of the target material based on the initial position of the material, the assembly position of the material, and the position of static obstacles includes the following execution steps:

[0039] Step S221: Generate a first environmental model based on the initial position of the material, the assembly position of the material, and the position of static obstacles;

[0040] Specifically, after the acquisition device acquires the initial position of the material, the assembly position of the material, and the position of the static obstacle, the control system establishes a unified first environmental model (three-dimensional coordinate system) in the environment based on the data information of the acquisition device, and marks the coordinates of each position in the first environmental model.

[0041] In an embodiment of the present application, the environmental model can be reconstructed through point cloud data or depth images to more intuitively and accurately represent the environment, which is suitable for highly complex environments.

[0042] In step S221, by constructing the first environmental model, the initial position, assembly position of the material, and the position information of the static obstacle are integrated to form a visual environmental map, which is convenient for the control system to generate and plan paths based on the three-dimensional environmental model, demonstrating the degree of intelligence of path planning.

[0043] Step S222: Based on the first environmental model, generate a first path exploration tree. The first path exploration tree includes at least a first root node and a first target node. The first root node is used to represent the initial position of the material, and the first target node is used to represent the assembly position of the material.

[0044] In step S222, the system can generate a tree structure to explore the path from the initial position of the material (the first root node) to the assembly position (the first target node).

[0045] Specifically, initialize the tree structure to create an empty tree T, and use the initial position of the material as the root node of the tree (the first root node), denoted as X_start. In the tree structure, the root node does not have a parent node and is the starting point of path exploration; the target node is set to use the assembly position of the material as the target node (the first target node), denoted as X_goal. Generate the first path exploration tree based on the first environmental model, and explore the path between the first root node and the first target node through the first path exploration tree, thereby planning a safe and effective path for the robot from the initial position of the material to the assembly position.

[0046] Step S223: Based on the first path exploration tree, use the RRT algorithm to generate an assembly path, and the assembly path is used to provide a path for the target material to move from the first root node to the first target node.

[0047] In step S223, using the RRT (Rapidly-exploring Random Trees) algorithm, an assembly path for moving the target material to the assembly position is planned. Specifically, determine the parameters for setting the RRT algorithm, including but not limited to the sampling step size δ, the maximum number of iterations N, and the target region radius t; path extension. Based on the first path exploration tree, the RRT algorithm will continue to explore and extend the path until a path from the first root node (the initial position of the material) to the first target node (the assembly position of the material) is found, including the following steps:

[0048] Step 1: Random sampling, randomly generate a point X_rand in the free space;

[0049] Step 2: Nearest node search, find the node X_near in the first path exploration tree that is closest to X_rand;

[0050] Step 3: New node generation and connection: Move a step size δ from X_near in the direction of X_rand to generate a new node X_new. If the path is safe (i.e., the path from X_near to X_new does not intersect with static obstacles), then add X_new to the tree and establish a connection from X_near to X_new in the tree;

[0051] Step 4: Connect to the target node. When X_new enters the preset target region (i.e., the distance from the material assembly position is less than t), try to directly connect X_new to the first target node X_goal to create a complete path.

[0052] It should be noted that in this embodiment, once a path from the first root node to the first target node is found, path reconstruction is performed, that is, starting from the first root node, a series of nodes are found along the edges in the tree to form a complete assembly path. Subsequently, the path is optimized, which may include local optimization to reduce the path length or the number of turns, and global optimization to find a better path.

[0053] Through steps S221 - S223, using the RRT algorithm, not only can static obstacles be avoided, but also the path length can be optimized, the handling time can be reduced, thereby improving the efficiency of the automated production line. In addition, the flexibility of the RRT algorithm enables it to adapt to different environmental models, including but not limited to three-dimensional space, multi-obstacle environments, and even dynamically changing environments, enhancing the robustness and adaptability of the system.

[0054] Optionally, the method further includes:

[0055] Step S201: Obtain the initial position of the target material, the initial station information of the grasping device, and the positions of static obstacles;

[0056] Specifically, before moving the target material to its assembly position, it is also necessary to control the grasping device to move from its initial position at the assembly station to the grasping position to perform the grasping operation on the target material. Therefore, before generating the assembly path, it is also necessary to plan the movement path of the grasping device from the initial station to the initial position of the target material.

[0057] In step S201, the material assembly system uses acquisition devices such as 3D vision cameras, sensors, or lidar to obtain the initial position of the target material, the initial station information of the grasping device, and the positions of static obstacles, and transmits the data of the above positions to the control system to facilitate the control system to process the data and then plan the movement path.

[0058] Step S202: Generate the grasping path of the target material based on the initial station information, the initial position of the target material, and the positions of static obstacles;

[0059] Specifically, sensors such as lidar and cameras are used to collect the environmental information of the working position. After confirming the initial position of the material and the material assembly position, the system plans the assembly path according to the collected information through the built-in algorithm.

[0060] Step S203: Generate a grasping control instruction based on the grasping path, and the grasping control instruction is at least used to control the grasping device to move along the grasping path.

[0061] Specifically, the control instruction planning converts the refined path points into specific control instructions, and the control instructions guide the grasping device to move from the initial station to the grasping position of the target material.

[0062] In step S203, after the material assembly system parses and processes the data information, it determines the grasping path and generates a grasping control instruction based on the assembly path. Moreover, after the grasping device reaches the grasping position, the system will also generate an instruction to grasp the target material. Based on the grasping instruction, after the grasping device identifies the characteristic position of the heat insulation pad, it combines the characteristic information such as the size and material of the heat insulation pad and the characteristic position to grasp the heat insulation pad.

[0063] Through steps S201 - S203, by combining the initial position of the target material and the positions of static obstacles, a grasping path from the initial station of the grasping device to the initial position of the material is generated, and based on the characteristic information of the heat insulation pad obtained by the acquisition device, the heat insulation pad is accurately and stably grasped, ensuring the coherence and efficiency of the action.

[0064] Optionally, in step S202, based on the initial station information, the initial material position of the target material, and the static obstacle positions, a grasping path for the target material is generated. The method further includes:

[0065] Step S2021: Based on the initial station information, the initial material position of the target material, and the static obstacle positions, a second environmental model is generated;

[0066] Specifically, after the acquisition device acquires the initial material position, the initial station information of the grasping device, and the static obstacle positions, the control system establishes a unified second environmental model (three-dimensional coordinate system) in the environment based on the data information of the acquisition device, and marks the coordinates of each position in the second environmental model.

[0067] In step S2021, by constructing the second environmental model, the initial position of the material, the initial station of the grasping device, and the position information of the static obstacles are integrated to form a visual environmental map, which facilitates the control system to generate and plan the path based on the three-dimensional environmental model. The construction of the second environmental model enables the system to more accurately plan the movement path of the grasping device.

[0068] Step S2022: Based on the second environmental model, a second path exploration tree is generated. The second path exploration tree includes at least a second root node and a second target node. The second root node is used to represent the initial station information of the grasping device, and the target node is used to represent the initial material position;

[0069] Specifically, according to the constructed second environmental model, the second root node and the second target node in the second environmental model are determined to plan the grasping path.

[0070] It should be noted that the reference position information used in constructing the second environmental model is different from that of the first environmental model. The second environmental model is mainly established based on the initial station of the grasping device, the initial position of the heat insulation pad, and the static obstacle positions near these two positions collected by the acquisition device, while the first environmental model is mainly established based on the initial position and the assembly position of the heat insulation pad.

[0071] Step S2023: Based on the second path exploration tree, using the RRT algorithm, a grasping path is generated. The grasping path is used to provide a path for the grasping device to move from the second root node to the second target node.

[0072] Specifically, based on the established second path exploration tree, the RRT algorithm is used to expand and update the second path exploration tree, and then a grasping path is generated. Finally, through path reconstruction and optimization, the optimal grasping path is determined.

[0073] Through steps S2021 - S2023, the construction of the second environmental model enables the system to more precisely plan the movement path of the grasping device. By randomly expanding the tree - like structure, starting from the initial station of the grasping device (the second root node), the shortest path to the target material position (the second target node) is explored. This not only avoids static obstacles but also takes into account the physical limitations of the grasping device, such as arm length, rotation angle, etc., to ensure the feasibility of the path. In addition, the iterative nature of the RRT algorithm allows the system to continuously optimize during the path - planning process, improving the flexibility and efficiency of the system.

[0074] Optionally, the method further includes:

[0075] Step S26, obtaining the real - time position information of the dynamic obstacle, and predicting the movement path of the dynamic obstacle based on the real - time position information of the dynamic obstacle;

[0076] Specifically, during the process of planning the assembly path or during the execution based on the movement control instruction, the positions of the grasping device and the dynamic obstacle are monitored in real time to prevent the grasping device from interfering with the dynamic obstacle in the assembly path.

[0077] In step S26, the real - time position information of the dynamic obstacle is the real - time position of the moving obstacle in the first environmental model collected by the acquisition device in real time. Through the system's analysis of the type and position of the dynamic obstacle, as well as data processing and fusion of different original data collected by the acquisition device, based on the historical trajectory and current motion state of the dynamic obstacle, its motion pattern is analyzed. The motion path of the dynamic obstacle can be predicted through the algorithms built into the system (such as motion prediction algorithms or deep - learning methods).

[0078] Step S28, in the case where it is determined that at least part of the motion path of the dynamic obstacle overlaps with the assembly path of the target material, generating a new assembly path for the target material, and the new assembly path is used to avoid the motion path of the dynamic obstacle;

[0079] Specifically, after obtaining the motion path of the dynamic obstacle, an analysis and evaluation are carried out, compared with the current assembly path, and it is judged whether there is a risk of collision. If there is a risk of collision, the control system will re - plan and generate a new assembly path based on the real - time position of the grasping device, the assembly position of the target material, the motion path of the dynamic obstacle, and the position of the static obstacle, to ensure the completion of the assembly task under the condition of production safety.

[0080] In one embodiment of the present application, by confirming that the assembly path overlaps with the path of a dynamic obstacle or there is a potential for collision, the necessity and urgency of avoidance are evaluated. If time permits, an attempt can be made to re-plan the assembly path; if time is tight, a temporary avoidance path can also be generated immediately to prevent the gripper from colliding with the dynamic obstacle. This process reflects the high degree of automation and intelligence of the intelligent system, can adapt to the changing environmental conditions in the workshop, and improve the safety of operations.

[0081] Step S29, control the gripper to move along the new assembly path to the assembly position.

[0082] Specifically, after determining the new assembly path, the control system will send a control instruction to control the gripper to move according to the new assembly path.

[0083] Through steps S26 - S29, by obtaining the position information of the dynamic obstacle in real time and predicting its movement path, the system can intelligently generate an avoidance path to ensure that the assembly path of the target material does not overlap with the movement path of the dynamic obstacle. It can not only avoid collisions but also dynamically adjust the path to adapt to changes on the production line, improving the safety of the system. In addition, the introduction of the dynamic obstacle avoidance mechanism enables the system to handle more complex and changeable environments, and can achieve efficient, safe, and automated operation of equipment in complex environments, which plays an important role in enhancing the adaptability and robustness of the intelligent system.

[0084] In an exemplary embodiment of the present application, during the planning of the grasping path and the execution of the grasping instruction, the position information of the dynamic obstacle can also be obtained in real time to determine whether the grasping path partially overlaps with the movement path of the dynamic obstacle, and a new grasping path can be planned and generated to prevent the gripper from colliding with the dynamic obstacle during the grasping of the heat insulation pad.

[0085] Optionally, in step S28, generating a new assembly path for the target material includes:

[0086] Step S281, obtain the real-time position information of the target material;

[0087] Specifically, the real-time position information of the target material is the real-time position of the target material collected by the collection device, and the collection device transmits the real-time position data of the target material to the control system to confirm the real-time positions of the target object and the gripper.

[0088] Step S282, based on the movement path of the dynamic obstacle, the real-time position information of the target material, and the assembly position information, use the RRT algorithm to generate a new assembly path for the target material.

[0089] Specifically, obtain the real-time position, speed, and predicted movement path of dynamic obstacles; update the precise position information of the target material (such as a heat insulation pad) in real time, reconstruct the real-time environment model, build an exploration tree in the real-time environment model, and use the RRT algorithm to regenerate a new assembly path for the target material.

[0090] In step S282, according to the real-time environment model, determine the real-time position of the target material as the root node, determine the assembly position as the target node, use the RRT algorithm to randomly select a free point that does not collide with any obstacles (including the predicted path of dynamic obstacles), and gradually build a path tree. Once a new assembly path is found and optimized, generate specific robot control instructions, and guide the grasping device to move to the position of the target material along the new path, and then move to the assembly position to complete the assembly task.

[0091] In steps S281 - S282, through the real-time replanning ability of the RRT algorithm, the system can quickly generate a new assembly path under the influence of dynamic obstacles, avoid delays in the material handling process, and improve the flexibility and efficiency of the production line. It can achieve efficient and safe handling of materials in a dynamic environment, which is of great significance for enhancing the real-time response ability and operation efficiency of intelligent systems.

[0092] Optionally, in step S223, the method includes:

[0093] Step S2231, based on the first path exploration tree, obtain the position of the exploration node;

[0094] Specifically, after initially establishing the first path exploration tree and confirming the first root node and the first target node, it is necessary to expand the exploration tree until a path from the first root node to the first target node is generated. The exploration node is a node randomly generated in the first environment model.

[0095] Step S2232, determine whether the position of the exploration node overlaps with the position of the static obstacle;

[0096] Specifically, obtain the position coordinates of the initial exploration node (the newly generated node) being inspected in the configuration space, and use an appropriate collision detection algorithm to determine whether the node position overlaps with the position of the static obstacle.

[0097] Step S2233, in the case where it is determined that the position of the exploration node does not overlap with the position of the static obstacle, generate the exploration node; or, in the case where it is determined that the position of the exploration node overlaps with the position of the static obstacle, re-obtain the position of the exploration node;

[0098] Specifically, if the position of a node overlaps with or is too close to the position of any static obstacle, the node is considered infeasible and cannot be added to the first path exploration tree; conversely, if the position of the node is safe and does not overlap with any static obstacle, it can be added to the first path exploration tree as a possible path point for subsequent path exploration.

[0099] Step S2234: Generate an assembly path based on the first root node, the first target node, and the exploration nodes.

[0100] In step S2234, starting from the first root node, traverse the entire first path exploration tree. For each node in the tree, read its position information. During the traversal, store the position information of each exploration node in a data structure. In addition to obtaining the position information of the nodes, the parent node information of each node also needs to be recorded. When a certain exploration node is close enough to the first target node, start backtracking from this node and find a series of nodes along the parent node links. These nodes form a path from the starting position to the target position. Concatenate the position information of these nodes to obtain the complete assembly path.

[0101] Through steps S2231 - S2234, by determining whether the position of the exploration nodes overlaps with static obstacles, the system can intelligently generate or regenerate exploration nodes to ensure the feasibility of the path. It can not only avoid collisions but also optimize the path, reduce the handling time, and improve the efficiency of the automated production line.

[0102] From the above steps, it can be seen that the material assembly path planning method of this application has the following beneficial effects: Using the RRT algorithm for optimal path planning can effectively handle path planning problems in high-dimensional and complex environments. The RRT algorithm randomly samples in the search space and gradually constructs a tree structure to explore possible paths until a path from the starting point to the target point is found, reducing the ineffective movement of the robot during the assembly process, thereby improving the assembly efficiency; the path planning ability of the RRT algorithm enables the robot to autonomously complete the heat insulation pad assembly task, reducing manual intervention, enhancing the automation degree of the production process, significantly improving the operation efficiency and safety, and enhancing the flexibility and resource optimization ability of the automated production system.

[0103] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0104] In this embodiment, a material assembly path planning device is further provided. This device is used to implement the above embodiments and preferred implementation manners, and those that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0105] Figure 3 is a structural block diagram of a material assembly path planning device according to an embodiment of the present invention. As Figure 3 shown, the device includes: an acquisition module 32, and the acquisition module 32 is used to acquire the initial position of the target material, the material assembly position, and the static obstacle position; a path generation module 34, and the path generation module 34 is used to generate an assembly path of the target material based on the initial position of the material, the material assembly position, and the static obstacle position; a control instruction generation module 36, and the control instruction generation module 36 is used to generate a movement control instruction based on the assembly path, and the movement control instruction is used to control the gripping device to move the target material from the initial position to the assembly position along the assembly path.

[0106] Through the above device, the initial position of the target material, the material assembly position, and the static obstacle position are acquired; based on the initial position of the material, the material assembly position, and the static obstacle position, an assembly path of the target material is generated; based on the assembly path, a movement control instruction is generated, and the movement control instruction is used to control the gripping device to move the target material from the initial position to the assembly position along the assembly path. By accurately acquiring the initial position and assembly position of the target material, as well as the position information of the static obstacle, the assembly path of the material from the initial position to the assembly position can be effectively planned, interference and conflicts with static obstacles can be avoided, safe, efficient, and automated material handling can be realized, production efficiency can be improved, the intelligence and automation level of material assembly can be enhanced, labor costs can be reduced, and thus the technical problem of being unable to obtain the optimal path for material assembly is solved.

[0107] Optionally, the material assembly path planning device provided in this application may further include other modules. For example, the material assembly path planning device may further include a communication module, which is used for data communication between the control system and other devices (such as sensors and positioning systems), ensuring that the path planning information can be transmitted to the execution device in real time and receiving execution feedback. The material assembly path planning device may further include a path optimization module, which is used to optimize the generated preliminary path, reduce the path length, and avoid unnecessary turning and repeated movements.

[0108] It should be noted that the above-mentioned various modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to this: the above-mentioned modules are all located in the same processor; or, the above-mentioned various modules are respectively located in different processors in any combination form.

[0109] An embodiment of the present invention also provides a storage medium, in which a computer program is stored. Wherein, the computer program is set to execute the steps in any one of the above method embodiments when running.

[0110] Optionally, in this embodiment, the above storage medium may be set to store a computer program for executing the following steps:

[0111] Step S1, obtain the initial position of the target material, the material assembly position, and the static obstacle position;

[0112] Step S2, generate an assembly path for the target material based on the initial position of the material, the material assembly position, and the static obstacle position;

[0113] Step S3, generate a movement control instruction based on the assembly path, and the movement control instruction is used to control the grasping device to move the target material from the initial position to the assembly position along the assembly path.

[0114] Optionally, in this embodiment, the above storage medium may include but is not limited to: USB flash drives, read-only memories (ROM for short), random access memories (RAM for short), mobile hard disks, magnetic disks, or optical discs and other various media that can store computer programs.

[0115] An embodiment of the present invention also provides a processor, which is set to run a computer program to execute the steps in any one of the above method embodiments.

[0116] Optionally, in this embodiment, the above processor may be set to execute the following steps through a computer program:

[0117] Step S1, obtain the initial material position, the material assembly position, and the static obstacle position of the target material;

[0118] Step S2, generate an assembly path for the target material based on the initial material position, the material assembly position, and the static obstacle position;

[0119] Step S3, generate a movement control instruction based on the assembly path, where the movement control instruction is used to control the grasping device to move the target material from the initial position to the assembly position along the assembly path.

[0120] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and will not be elaborated herein.

[0121] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0122] In the above embodiments of the present invention, the descriptions of the respective embodiments have their own emphases. For parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0123] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the units or modules can be in an electrical or other form.

[0124] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0125] In addition, the functional units in the various embodiments of the present invention can be integrated in one processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0126] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0127] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A method for planning a material assembly path, characterized in that The method includes the following steps: Obtain the initial position of the target material, the assembly position of the material, and the position of the static obstacle; Generate an assembly path for the target material based on the initial position of the material, the assembly position of the material, and the position of the static obstacle; Generate a movement control instruction based on the assembly path, where the movement control instruction is used to control the gripper to move the target material from the initial position to the assembly position along the assembly path.

2. The method according to claim 1, wherein Generating the assembly path for the target material based on the initial position of the material, the assembly position of the material, and the position of the static obstacle includes: Generate a first environmental model based on the initial position of the material, the assembly position of the material, and the position of the static obstacle; Generate a first path exploration tree based on the first environmental model. The first path exploration tree at least includes a first root node and a first target node. The first root node is used to represent the initial position of the material, and the first target node is used to represent the assembly position of the material; Generate the assembly path based on the first path exploration tree using the RRT algorithm. The assembly path is used to provide a path for the target material to move from the first root node to the first target node.

3. The method according to claim 1, characterized in that The method further includes: Obtain the initial position of the target material, the initial station information of the gripper, and the position of the static obstacle; Generate a grasping path for the target material based on the initial station information, the initial position of the target material, and the position of the static obstacle; Generate a grasping control instruction based on the grasping path. The grasping control instruction is at least used to control the gripper to move along the grasping path.

4. The method according to claim 3, wherein Generating the grasping path for the target material based on the initial station information, the initial position of the target material, and the position of the static obstacle, the method further includes: Generate a second environmental model based on the initial station information, the initial position of the target material, and the position of the static obstacle; Generate a second path exploration tree based on the second environmental model. The second path exploration tree at least includes a second root node and a second target node. The second root node is used to represent the initial station information of the gripper, and the target node is used to represent the initial position of the material; Generate the grasping path based on the second path exploration tree using the RRT algorithm. The grasping path is used to provide a path for the gripper to move from the second root node to the second target node.

5. The method according to claim 2, wherein The method further includes: Obtain the real-time position information of the dynamic obstacle, and predict the movement path of the dynamic obstacle based on the real-time position information of the dynamic obstacle; In the case where it is determined that the movement path of the dynamic obstacle overlaps at least partially with the assembly path of the target material, generate a new assembly path for the target material, where the new assembly path is used to avoid the movement path of the dynamic obstacle; Control the gripper to move to the assembly position along the new assembly path.

6. The method according to claim 5, wherein Generating the new assembly path for the target material includes: Obtain the real-time position information of the target material; Based on the motion path of the dynamic obstacle, the real-time position information and the assembly position information of the target material, use the RRT algorithm to generate a new assembly path for the target material.

7. The method according to claim 2, characterized in that Based on the first path exploration tree, use the RRT algorithm to generate the assembly path, including: Based on the first path exploration tree, obtain the position of the exploration node; Determine whether the position of the exploration node overlaps with the position of the static obstacle; In the case where it is determined that the position of the exploration node does not overlap with the position of the static obstacle, generate an exploration node; or In the case where it is determined that the position of the exploration node overlaps with the position of the static obstacle, re-obtain the position of the exploration node; Based on the first root node, the first target node and the exploration node, generate the assembly path.

8. A material assembly path planning device, characterized in that Including: An acquisition module, the acquisition module is used to acquire the initial position of the material, the assembly position of the material and the position of the static obstacle of the target material; A path generation module, the path generation module is used to generate an assembly path for the target material based on the initial position of the material, the assembly position of the material and the position of the static obstacle; A control instruction generation module, the control instruction generation module is used to generate a movement control instruction based on the assembly path, and the movement control instruction is used to control the grasping device to move the target material from the initial position to the assembly position along the assembly path.

9. A non-volatile storage medium, characterized in that, A computer program is stored in the storage medium, wherein the computer program is set to execute the material assembly path planning method described in any one of claims 1 to 7 when running.

10. A computer program product, comprising computer instructions, characterized in that, When the computer instruction is executed by the processor, the steps of the material assembly path planning method described in any one of claims 1 to 7 are implemented.

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