Path planning method, device and equipment of mechanical arm actuator, medium and product

Abstract

The invention discloses a path planning method, device and equipment for a mechanical arm actuator, a medium and a product. The method comprises the steps that a motion starting point and a motion end point of a mechanical arm actuator are obtained, and a grid map of a mechanical arm motion space is generated; taking the motion starting point as a current node, determining adjacent nodes of the current node in the grid map, and determining joint angle data matched with each adjacent node; according to the joint angle data of the mechanical arm at the current node and the joint angle data matched with the adjacent nodes, the next node is determined in the adjacent nodes; and updating the motion path, updating the next node as the current node, returning to the execution of determining the adjacent node of the current node in the grid map until the next node is a motion end point, and outputting a path planning result of the mechanical arm actuator. According to the technical scheme, the problem that the movement efficiency of the mechanical arm actuator is low is solved, the rotation energy consumption of the mechanical arm joint can be effectively reduced, and the movement efficiency of the mechanical arm actuator is improved.

Description

Technical Field

[0001] The present invention relates to the field of path planning technology, and in particular to a path planning method, device, equipment, medium and product for a robotic arm actuator. Background Art

[0002] Robotic arms are an important part of industrial automation, service robots and other fields, and are widely used in tasks such as assembly, welding and material handling. Robotic arms usually need to perform high-precision real-time path planning in a three-dimensional space with multiple degrees of freedom to ensure the completion of the task.

[0003] In the prior art, the path planning of the robot arm is mainly to find the shortest feasible motion path based on the path planning algorithm under the joint motion constraints and environmental constraints, such as the Probabilistic Roadmap Method (PRM) based on sample points and the Rapidly Exploring Random Tree (RRT) and other path planning algorithms.

[0004] However, the shortest feasible motion path only indicates the optimal motion distance of the robot arm actuator, and cannot guarantee the optimal energy consumption of the robot arm motion. At the same time, in order to execute the shortest feasible motion path, the robot arm may perform very complex joint rotations, resulting in low motion efficiency of the robot arm actuator. Summary of the invention

[0005] The present invention provides a path planning method, device, equipment, medium and product for a robotic arm actuator to solve the problem of low movement efficiency of the robotic arm actuator. Path planning is performed based on the robotic arm joint angle data between adjacent nodes, which can effectively reduce the rotational energy consumption of the robotic arm joint and improve the movement efficiency of the robotic arm actuator.

[0006] According to one aspect of the present invention, a path planning method for a robot actuator is provided, the method comprising:

[0007] Obtaining a movement start point and a movement end point of a robot arm actuator, and generating a grid map of the robot arm movement space according to the movement start point and the movement end point;

[0008] Taking the movement starting point as the current node, determining the adjacent nodes of the current node in the grid map, and determining the joint angle data matched by each adjacent node; the joint angle data matched by the adjacent nodes is the joint angle data of the robotic arm when the robotic arm actuator reaches the adjacent node;

[0009] According to the joint angle data of the robot arm at the current node and the matching joint angle data of each adjacent node, the next node is determined in each adjacent node;

[0010] According to the grid edge from the current node to the next node, the motion path is updated, the next node is updated to the current node, and the execution is returned to determine the adjacent nodes of the current node in the grid map until the next node is the end point of the motion, and the path planning result of the robotic arm actuator is output.

[0011] According to another aspect of the present invention, a path planning device for a robot arm actuator is provided, the device comprising:

[0012] A grid map generation module is used to obtain the movement start point and the movement end point of the robot arm actuator, and generate a grid map of the robot arm movement space according to the movement start point and the movement end point;

[0013] A joint angle determination module, used to take the movement starting point as the current node, determine the adjacent nodes of the current node in the grid map, and determine the joint angle data matched by each adjacent node; the joint angle data matched by the adjacent nodes is the joint angle data of the robotic arm when the robotic arm actuator reaches the adjacent node;

[0014] The next node planning module is used to determine the next node among the adjacent nodes according to the joint angle data of the robot arm at the current node and the joint angle data matched by each adjacent node;

[0015] The planning result output module is used to update the motion path according to the grid edge from the current node to the next node, update the next node to the current node, return to execute the adjacent nodes of the current node determined in the grid map until the next node is the end point of the motion, and output the path planning result of the robotic arm actuator.

[0016] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0017] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the path planning method for the robotic arm actuator described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the path planning method for a robotic arm actuator described in any embodiment of the present invention when executed.

[0019] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the path planning method for a robotic arm actuator according to any embodiment of the present invention is implemented.

[0020] The technical solution of the embodiment of the present invention is to obtain the starting point and end point of the movement of the robot arm actuator, and generate a grid map of the robot arm movement space according to the starting point and end point of the movement; take the starting point of the movement as the current node, determine the adjacent nodes of the current node in the grid map, and determine the joint angle data matched by each adjacent node; the joint angle data matched by the adjacent node is the joint angle data of the robot arm when the robot arm actuator reaches the adjacent node; according to the joint angle data of the robot arm at the current node and the joint angle data matched by each adjacent node, determine the next node in each adjacent node; according to the grid edge from the current node to the next node, update the movement path, update the next node to the current node, return to execute the adjacent nodes of the current node determined in the grid map, until the next node is the movement end point, and output the path planning result of the robot arm actuator. This technical solution solves the problem of low movement efficiency of the robot arm actuator. Based on the robot arm joint angle data between adjacent nodes, path planning can effectively reduce the rotation energy consumption of the robot arm joint and improve the movement efficiency of the robot arm actuator.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 is a flow chart of a path planning method for a robotic arm actuator provided according to a first embodiment of the present invention;

[0024] Figure 2 is a flow chart of a path planning method for a robotic arm actuator provided according to a second embodiment of the present invention;

[0025] Figure 3 is a schematic structural diagram of a path planning device for a robotic arm actuator provided according to a third embodiment of the present invention;

[0026] Figure 4 It is a schematic diagram of the structure of an electronic device for implementing the path planning method of a robotic arm actuator according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The acquisition, storage, use, processing, etc. of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0029] Embodiment 1

[0030] Figure 1 A flow chart of a path planning method for a robotic arm actuator is provided for the first embodiment of the present invention. This embodiment can be applied to robotic arm control scenarios, especially multi-degree-of-freedom robotic arm control scenarios. The method can be executed by a path planning device for a robotic arm actuator, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0031] S110, obtaining a movement start point and a movement end point of a robot arm actuator, and generating a grid map of the robot arm movement space according to the movement start point and the movement end point.

[0032] This solution can be executed by the controller of the robotic arm. The robotic arm can include one or more joints for realizing rotation of each degree of freedom. The end of the robotic arm is usually equipped with an actuator for realizing mechanical operations such as welding and grasping. The actuators at the end of the robotic arm are usually different for different application scenarios. The controller of the robotic arm can obtain the starting point and end point of the actuator. The starting point of the movement can be the current position of the actuator, and the end point of the movement can be the target position to which the actuator needs to move. The controller can discretize the three-dimensional space where the robotic arm is located into a grid map. Each grid can be a square with 4 vertices. Each vertex can be used as a motion node. The starting point and end point of the robotic arm actuator can be two different nodes in the grid map.

[0033] The controller can define an undirected graph to represent the grid map. The expression of the undirected graph is: G = (V, E), where V represents the set of nodes in the grid map and E represents the set of edges connecting the nodes. The weight of each edge can be calculated based on the change in the joint angle of the robot arm.

[0034] S120. Take the movement starting point as the current node, determine the adjacent nodes of the current node in the grid map, and determine the joint angle data matched by each adjacent node; the joint angle data matched by the adjacent nodes is the joint angle data of the robotic arm when the robotic arm actuator reaches the adjacent node.

[0035] The controller can use the starting point of the actuator's movement as the current node and plan the next node in the grid map. Specifically, the controller can determine the adjacent nodes of the current node in the grid map, and determine the joint angle data of the robotic arm when the robotic arm actuator reaches each adjacent node, so as to evaluate each adjacent node according to the joint angle data matched by each adjacent node, and then determine the next node. It can be understood that the joint angle data can include the rotation angle of each joint of the robotic arm.

[0036] S130 , determining a next node among the adjacent nodes according to the joint angle data of the robot arm at the current node and the joint angle data matched by the adjacent nodes.

[0037] The controller can calculate the joint angle change data based on the joint angle data of the robot arm when the actuator is located at the current node and the joint angle data of each adjacent node, and then evaluate the effort-saving degree of the robot arm movement when the actuator reaches each adjacent node based on the joint angle change data, and then plan to determine the next node in each adjacent node based on the effort-saving degree of reaching each adjacent node.

[0038] S140. Update the motion path according to the grid edge from the current node to the next node, update the next node to the current node, return to execute the adjacent nodes of the current node determined in the grid map until the next node is the end point of the motion, and output the path planning result of the robotic arm actuator.

[0039] After determining the next node, the controller can use the grid edge from the current node to the next node as the motion path, update the next node to the current node, return to execute the adjacent nodes determined in the grid map of the current node, plan the next node according to the joint angle data matched by each adjacent node and the joint angle data of the robot arm when the actuator is located at the current node, and extend the motion path according to the next node until the next node is the motion terminal, stop path planning, and output the path planning result executed by the robot arm.

[0040] The technical solution of the embodiment of the present invention is to obtain the starting point and end point of the movement of the robot arm actuator, and generate a grid map of the robot arm movement space according to the starting point and end point of the movement; take the starting point of the movement as the current node, determine the adjacent nodes of the current node in the grid map, and determine the joint angle data matched by each adjacent node; the joint angle data matched by the adjacent node is the joint angle data of the robot arm when the robot arm actuator reaches the adjacent node; according to the joint angle data of the robot arm at the current node and the joint angle data matched by each adjacent node, determine the next node in each adjacent node; according to the grid edge from the current node to the next node, update the movement path, update the next node to the current node, return to execute the adjacent nodes of the current node determined in the grid map, until the next node is the movement end point, and output the path planning result of the robot arm actuator. This technical solution solves the problem of low movement efficiency of the robot arm actuator. Based on the robot arm joint angle data between adjacent nodes, path planning can effectively reduce the rotation energy consumption of the robot arm joint and improve the movement efficiency of the robot arm actuator.

[0041] Embodiment 2

[0042] Figure 2 This is a flow chart of a path planning method for a robot arm actuator provided in Embodiment 2 of the present invention. This embodiment is refined based on the above embodiment. Figure 2 As shown, the method includes:

[0043] S210, obtaining a movement start point and a movement end point of a robot arm actuator, using the movement start point and the movement end point as nodes in a grid map respectively, and generating a grid map of the robot arm movement space according to a preset grid size.

[0044] In this solution, the controller can use the movement starting point and the movement terminal as nodes in the grid map, respectively, and use them as two different nodes in the grid map, and generate a grid map of the robot's movement space according to the preset grid size. The grid size can be determined based on the distance range that the actuator can move. The controller can determine the maximum and minimum distances that the actuator can move based on attribute information such as the total length of the robot arm, the number of joints, the length of each joint, and the rotation angle range of each joint, thereby obtaining the distance range that the actuator can move. The controller can select a grid size within the distance range that the actuator can move, for example, using the midpoint distance in the distance range as the side length of the square grid.

[0045] S220. Take the movement starting point as the current node, determine the adjacent nodes of the current node in the grid map, and determine the joint angle data matched by each adjacent node; the joint angle data matched by the adjacent nodes is the joint angle data of the robotic arm when the robotic arm actuator reaches the adjacent node.

[0046] In this embodiment, determining the joint angle data matched by each adjacent node includes:

[0047] If the robot arm actuator reaches multiple robot arm rotation modes at the adjacent node, the target rotation mode is determined among the robot arm rotation modes based on the joint angle data of the robot arm at the current node, and the joint angle data of the target rotation mode is used as the joint angle data for matching the adjacent node.

[0048] It can be understood that if the robot includes multiple degrees of freedom, that is, multiple rotatable joints, so that the actuator can reach another node from one node, there may be multiple ways of rotating the robot. The controller can determine the joint angle change data of the actuator moving from the current node to the adjacent node under each robot rotation mode based on the joint angle data of the robot at the current node and the joint angle data of the robot at the adjacent node under each robot rotation mode. Based on the joint angle change data of the actuator moving from the current node to the adjacent node under each robot rotation mode, the controller can select a target rotation mode from each robot rotation mode, and use the joint angle data of the target rotation mode as the joint angle data matching the adjacent node.

[0049] In a specific example, the robot has three degrees of freedom. From node A to node B, the robot can rotate joint 1 by 90°, keep joints 2 and 3 stationary, or keep joint 1 stationary, rotate joint 2 by 20°, and rotate joint 3 by 36°. The joint angle change data of mode 1 can be expressed as (90°, 0, 0), and the joint angle change data of mode 2 can be expressed as (0, 20°, 36°). The joint angles of mode 1 need to rotate 90° in total, and the joint angles of mode 2 need to rotate 56° in total. The controller can select the robot rotation mode with the smallest joint angle change as the target rotation mode, that is, mode 2 is used as the target rotation mode. The joint angle data of mode 2 is used as the joint angle data matching node B.

[0050] S230. Determine the joint angle change data matched by each adjacent node based on the joint angle data of the robotic arm at the current node and the joint angle data matched by each adjacent node; the joint angle change data matched by the adjacent nodes is the joint angle change data of the robotic arm when the robotic arm actuator moves from the current node to the adjacent node.

[0051] It is easy to understand that by subtracting the joint angle data of the robot at the current node from the joint angle data of each adjacent node, the joint angle change data of each adjacent node can be obtained. The joint angle change data is used to represent the angle change of each joint of the robot when the actuator moves from one node to another.

[0052] S240 , determining the path cost from the current node to each adjacent node according to the joint angle change data matched by each adjacent node.

[0053] After obtaining the joint angle change data matched by each adjacent node, the controller can determine the path cost from the current node to each adjacent node based on the joint angle change data matched by each adjacent node. Specifically, the path cost can be determined based on the absolute value of the joint angle change data matched by each adjacent node, for example, it can be expressed as It can also be expressed as Among them, C(v t ,v t+1 ) represents the current node v t To the adjacent node v t+1 The path cost value is, N represents the number of movable joints of the robot arm, i represents the joint index of the robot arm, θ i,t Indicates that the robot arm actuator is at the current node v t The angle of the robot arm joint i at time θ i,t+1 Indicates that the robot arm actuator is at the current node v t+1 The angle of the robot arm joint i at this time.

[0054] Based on the above solution, optionally, the path cost expression is:

[0055]

[0056] Among them, C(v t ,v t+1 ) represents the current node v t To the adjacent node v t+1 The path cost value is, N represents the number of movable joints of the robot arm, i represents the joint index of the robot arm, θ i,t Indicates that the robot arm actuator is at the current node v t The angle of the robot arm joint i at time θ i,t+1 Indicates that the robot arm actuator is at the current node v t+1 The angle of the robot arm joint i at this time.

[0057] Defining the path cost based on the sum of squares of joint angle change data helps to avoid interference from the direction of joint rotation and better capture the discreteness of joint angle change data.

[0058] In a feasible solution, determining the path cost from the current node to each adjacent node according to the joint angle change data matched by each adjacent node includes:

[0059] If there is a target adjacent node matching the joint angle change data that exceeds the joint angle motion range, the path cost from the current node to the target adjacent node is set to infinity.

[0060] In a preferred solution, after determining the path cost from the current node to each adjacent node, the method further includes:

[0061] If there is an obstacle on the grid edge from the current node to the target adjacent node, the path cost from the current node to the target adjacent node is set to infinity.

[0062] It should be noted that if the joint angle change data matched by the adjacent node exceeds the joint angle motion range, it means that the robot cannot reach the adjacent node. Therefore, the controller can set the path cost from the current node to the target adjacent node to infinity. If there is an obstacle on the grid edge from the current node to the target adjacent node, it means that there is an obstacle on the way for the robot to reach the adjacent node. Therefore, the controller can also set the path cost from the current node to the target adjacent node to infinity.

[0063] In a specific example, the path cost can be expressed as:

[0064]

[0065] Among them, C(v t,v t+1 ) represents the current node v t To the adjacent node v t+1 The path cost value is, N represents the number of movable joints of the robot arm, i represents the joint index of the robot arm, θ i,t Indicates that the robot arm actuator is at the current node v t The angle of the robot arm joint i at time θ i,t+1 Indicates that the robot arm actuator is at the current node v t+1 The angle of the robot arm joint i at time θ max represents the maximum value of joint angle movement, e t,t+1 Represents the current node v t To the adjacent node v t+1 Grid edges.

[0066] S250: Determine a next node among the adjacent nodes of the current node according to the path cost from the current node to each adjacent node.

[0067] The controller may sort the path costs from the current node to each adjacent node, and select the adjacent node with the smallest path cost as the next node.

[0068] S260. Update the motion path according to the grid edge from the current node to the next node, update the next node to the current node, return to execute the adjacent nodes of the current node determined in the grid map until the next node is the end point of the motion, and output the path planning result of the robotic arm actuator.

[0069] After determining the next node, the controller can perform path planning based on the Dijkstra algorithm. The steps are as follows:

[0070] In step 1, the controller may initialize two node sets S and U, where S represents a node set for which the shortest path has been determined, and U represents a node set for which the shortest path has not been determined.

[0071] Step 2: The controller can take the starting point of the movement as the current node, add the current node to the set S, and add other nodes in the grid map to the set U.

[0072] Step 3: The path cost between the current node and each adjacent node is used as the weight of the corresponding grid edge, and the initial path cost of the remaining nodes in the set U is set to infinity.

[0073] Step 4: Select the node corresponding to the grid edge with the smallest weight from U, add it to S, and update the path cost of the current node and each node in U.

[0074] Step 5: Repeat steps 3-4 until all nodes in set U are traversed, and output the path planning result of the robot arm actuator.

[0075] The technical solution of the embodiment of the present invention is to obtain the starting point and end point of the movement of the robot arm actuator, and generate a grid map of the robot arm movement space according to the starting point and end point of the movement; take the starting point of the movement as the current node, determine the adjacent nodes of the current node in the grid map, and determine the joint angle data matched by each adjacent node; the joint angle data matched by the adjacent node is the joint angle data of the robot arm when the robot arm actuator reaches the adjacent node; according to the joint angle data of the robot arm at the current node and the joint angle data matched by each adjacent node, determine the next node in each adjacent node; according to the grid edge from the current node to the next node, update the movement path, update the next node to the current node, return to execute the adjacent nodes of the current node determined in the grid map, until the next node is the movement end point, and output the path planning result of the robot arm actuator. This technical solution solves the problem of low movement efficiency of the robot arm actuator. Based on the robot arm joint angle data between adjacent nodes, path planning can effectively reduce the rotation energy consumption of the robot arm joint and improve the movement efficiency of the robot arm actuator.

[0076] Embodiment 3

[0077] Figure 3 This is a schematic diagram of the structure of a path planning device for a robotic arm actuator provided in Embodiment 3 of the present invention. Figure 3 As shown, the device comprises:

[0078] A grid map generation module 310 is used to obtain a movement start point and a movement end point of a robot arm actuator, and generate a grid map of the robot arm movement space according to the movement start point and the movement end point;

[0079] The joint angle determination module 320 is used to take the movement starting point as the current node, determine the adjacent nodes of the current node in the grid map, and determine the joint angle data matched by each adjacent node; the joint angle data matched by the adjacent nodes is the joint angle data of the robot arm when the robot arm actuator reaches the adjacent node;

[0080] The next node planning module 330 is used to determine the next node among the adjacent nodes according to the joint angle data of the robot arm at the current node and the joint angle data matched by each adjacent node;

[0081] The planning result output module 340 is used to update the motion path according to the grid edge from the current node to the next node, update the next node to the current node, return to execute the adjacent nodes of the current node determined in the grid map until the next node is the end point of the motion, and output the path planning result of the robotic arm actuator.

[0082] In this solution, the grid map generation module 310 is specifically used for:

[0083] The movement starting point and the movement terminal are respectively used as nodes in a grid map, and a grid map of the robot arm movement space is generated according to a preset grid size.

[0084] In a feasible solution, the next node planning module 330 is specifically used to:

[0085] According to the joint angle data of the robot arm at the current node and the joint angle data matched by each adjacent node, the joint angle change data matched by each adjacent node is determined; the joint angle change data matched by the adjacent node is the joint angle change data of the robot arm when the robot arm actuator moves from the current node to the adjacent node;

[0086] Determine the path cost from the current node to each adjacent node according to the joint angle change data matched by each adjacent node;

[0087] According to the path cost from the current node to each adjacent node, a next node is determined among the adjacent nodes of the current node.

[0088] Based on the above solution, the path cost expression is:

[0089]

[0090] Among them, C(v t ,v t+1 ) represents the current node v t To the adjacent node v t+1 The path cost value is, N represents the number of movable joints of the robot arm, i represents the joint index of the robot arm, θ i,t Indicates that the robot arm actuator is at the current node v t The angle of the robot arm joint i at time θ i,t+1 Indicates that the robot arm actuator is at the current node v t+1 The angle of the robot arm joint i at this time.

[0091] In a feasible solution, determining the path cost from the current node to each adjacent node according to the joint angle change data matched by each adjacent node includes:

[0092] If there is a target adjacent node matching the joint angle change data that exceeds the joint angle motion range, the path cost from the current node to the target adjacent node is set to infinity.

[0093] In a preferred embodiment, the device is also used for:

[0094] After determining the path cost from the current node to each adjacent node, if there is an obstacle on the grid edge from the current node to the target adjacent node, the path cost from the current node to the target adjacent node is set to infinity.

[0095] In this embodiment, the joint angle determination module 320 is specifically used for:

[0096] If the robot arm actuator reaches multiple robot arm rotation modes at the adjacent node, the target rotation mode is determined among the robot arm rotation modes based on the joint angle data of the robot arm at the current node, and the joint angle data of the target rotation mode is used as the joint angle data for matching the adjacent node.

[0097] The path planning device for a robotic arm actuator provided in an embodiment of the present invention can execute the path planning method for a robotic arm actuator provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0098] Embodiment 4

[0099] Figure 4 A schematic diagram of an electronic device 410 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0100] like Figure 4 As shown, the electronic device 410 includes at least one processor 411, and a memory connected to the at least one processor 411 in communication, such as a read-only memory (ROM) 412, a random access memory (RAM) 413, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 411 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 412 or the computer program loaded from the storage unit 418 to the random access memory (RAM) 413. In the RAM 413, various programs and data required for the operation of the electronic device 410 can also be stored. The processor 411, the ROM 412, and the RAM 413 are connected to each other via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0101] Multiple components in the electronic device 410 are connected to the I / O interface 415, including: an input unit 416, such as a keyboard, a mouse, etc.; an output unit 417, such as various types of displays, speakers, etc.; a storage unit 418, such as a disk, an optical disk, etc.; and a communication unit 419, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 419 allows the electronic device 410 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0102] The processor 411 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 411 executes the various methods and processes described above, such as a path planning method for a robotic arm actuator.

[0103] In some embodiments, the path planning method for the robot arm actuator may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 410 via the ROM 412 and / or the communication unit 419. When the computer program is loaded into the RAM 413 and executed by the processor 411, one or more steps of the path planning method for the robot arm actuator described above may be performed. Alternatively, in other embodiments, the processor 411 may be configured to execute the path planning method for the robot arm actuator in any other appropriate manner (e.g., by means of firmware).

[0104] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0105] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable robot actuator path planning device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0106] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0107] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0108] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0109] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0110] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0111] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A path planning method for a robotic arm actuator, characterized in that: The method comprises: Obtaining a movement start point and a movement end point of a robot arm actuator, and generating a grid map of the robot arm movement space according to the movement start point and the movement end point; Taking the movement starting point as the current node, determining the adjacent nodes of the current node in the grid map, and determining the joint angle data matched by each adjacent node; the joint angle data matched by the adjacent nodes is the joint angle data of the robotic arm when the robotic arm actuator reaches the adjacent node; According to the joint angle data of the robot arm at the current node and the matching joint angle data of each adjacent node, the next node is determined in each adjacent node; According to the grid edge from the current node to the next node, the motion path is updated, the next node is updated to the current node, and the execution is returned to determine the adjacent nodes of the current node in the grid map until the next node is the end point of the motion, and the path planning result of the robotic arm actuator is output.

2. The method according to claim 1, characterized in that The step of generating a grid map of the robot arm motion space according to the motion starting point and the motion end point comprises: The movement starting point and the movement terminal are respectively used as nodes in a grid map, and a grid map of the robot arm movement space is generated according to a preset grid size.

3. The method according to claim 1, characterized in that The method of determining the next node in each adjacent node according to the joint angle data of the robot arm at the current node and the joint angle data matched by each adjacent node comprises: According to the joint angle data of the robot arm at the current node and the joint angle data matched by each adjacent node, the joint angle change data matched by each adjacent node is determined; the joint angle change data matched by the adjacent node is the joint angle change data of the robot arm when the robot arm actuator moves from the current node to the adjacent node; Determine the path cost from the current node to each adjacent node according to the joint angle change data matched by each adjacent node; According to the path cost from the current node to each adjacent node, a next node is determined among the adjacent nodes of the current node.

4. The method according to claim 3, characterized in that The path cost expression is: Among them, C(v t ,v t+1 ) represents the current node v t To the adjacent node v t+1 The path cost value is, N represents the number of movable joints of the robot arm, i represents the joint index of the robot arm, θ i,t Indicates that the robot arm actuator is at the current node v t The angle of the robot arm joint i at time θ i,t+1 Indicates that the robot arm actuator is at the current node v t+1 The angle of the robot arm joint i at this time.

5. The method according to claim 1, characterized in that Determining the path cost from the current node to each adjacent node according to the joint angle change data matched by each adjacent node includes: If there is a target adjacent node matching the joint angle change data that exceeds the joint angle motion range, the path cost from the current node to the target adjacent node is set to infinity; After determining the path cost from the current node to each adjacent node, the method further includes: If there is an obstacle on the grid edge from the current node to the target adjacent node, the path cost from the current node to the target adjacent node is set to infinity.

6. The method according to claim 1, characterized in that The determining of the joint angle data matched by each adjacent node includes: If the robot arm actuator reaches multiple robot arm rotation modes at the adjacent node, the target rotation mode is determined among the robot arm rotation modes based on the joint angle data of the robot arm at the current node, and the joint angle data of the target rotation mode is used as the joint angle data for matching the adjacent node.

7. A path planning device for a robotic arm actuator, characterized in that: The device comprises: A grid map generation module is used to obtain the movement start point and the movement end point of the robot arm actuator, and generate a grid map of the robot arm movement space according to the movement start point and the movement end point; A joint angle determination module, used to take the movement starting point as the current node, determine the adjacent nodes of the current node in the grid map, and determine the joint angle data matched by each adjacent node; the joint angle data matched by the adjacent nodes is the joint angle data of the robotic arm when the robotic arm actuator reaches the adjacent node; The next node planning module is used to determine the next node among the adjacent nodes according to the joint angle data of the robot arm at the current node and the joint angle data matched by each adjacent node; The planning result output module is used to update the motion path according to the grid edge from the current node to the next node, update the next node to the current node, return to execute the adjacent nodes of the current node determined in the grid map until the next node is the end point of the motion, and output the path planning result of the robotic arm actuator.

8. An electronic device, characterized in that: The electronic device comprises: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the path planning method for the robotic arm actuator described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the path planning method for a robotic arm actuator according to any one of claims 1 to 6 when executed.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the path planning method for a robot arm actuator according to any one of claims 1 to 6.

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