Robot path planning method, device, medium and equipment considering turning cost

Abstract

The present invention proposes a robot path planning method, device, medium and equipment that considers turning costs, adds the first-class node to the priority queue, and records the lowest cost path and corresponding path cost of the first-class node; if the target node in the priority queue is not the task end point, remove the target node from the priority queue; add each second-class node corresponding to the target node to the priority queue; after all the second-class nodes corresponding to the target node are added to the priority queue, determine a new target node, and repeatedly determine whether the target node is the task end point until the target node is the task end point or the priority queue is empty. The path cost is determined based on the path length and the number of turns on the path, and a step-by-step iterative method is used to find the lowest cost path from the task start point to the task end point, so as to ensure the optimal operating efficiency of the mobile robot when moving along the task path.

Description

Technical Field

[0001] The present invention relates to the field of robot control scheduling, and in particular to a robot path planning method, device, medium and equipment taking turning cost into consideration. Background Art

[0002] In the field of logistics and warehousing, automation and intelligent control technologies have developed rapidly. With the continuous increase in land and labor costs, intensive transit warehouses have higher operating efficiency because they can fully utilize space efficiency and reduce labor demand accordingly. With the popularization of stereoscopic warehouse applications, logistics mobile robots can complete integrated warehouse transportation and verification operations to meet the efficiency requirements of intensive storage in and out of the warehouse, and have become widely used transportation vehicles.

[0003] The advantage of logistics mobile robots is that they can work across lanes and have good flexibility. In an overall movement area, multiple logistics mobile robots work simultaneously, but this leads to problems of path planning and path conflicts. Therefore, technicians in this field begin to pay attention to the problem of how to complete path planning. Summary of the invention

[0004] The object of the present invention is to provide a robot path planning method, device, medium and equipment taking into account turning cost, so as to at least partially improve the above-mentioned problems.

[0005] In order to achieve the above purpose, the technical solution adopted by the embodiment of the present invention is as follows:

[0006] In a first aspect, an embodiment of the present invention provides a robot path planning method considering turning cost, the method comprising:

[0007] Add the first type of nodes to the priority queue, and record the lowest cost path and the corresponding path cost of the first type of nodes; wherein the first type of nodes are idle nodes adjacent to the task starting point;

[0008] Determine whether the target node is the task endpoint, wherein the target node is the node with the lowest path cost in the priority queue;

[0009] If the target node is the end point of the task, the minimum cost path of the target node is determined as the task path of the mobile robot;

[0010] If the target node is not the task endpoint, the target node is removed from the priority queue and a verification mark is added to the target node;

[0011] Add each second-type node corresponding to the target node to a priority queue, and record the lowest cost path and the corresponding path cost of the second-type node; wherein the second-type node is an idle node adjacent to the target node and not carrying a verification tag;

[0012] After all the second-category nodes corresponding to the target node are added to the priority queue, a new target node is determined, and whether the target node is the task endpoint is repeatedly determined until the target node is the task endpoint or the priority queue is empty.

[0013] Optionally, the step of adding each second-type node corresponding to the target node to a priority queue and recording the lowest cost path and the corresponding path cost of the second-type node includes:

[0014] Obtaining a target path cost along a target path to a second type of node, wherein the target path is a shortest path from the task starting point along a least-cost path of the target node to the second type of node;

[0015] If the second type of node is not added to the priority queue, the second type of node is added to the priority queue, the target path is used as the lowest cost path of the second type of node, and the target path cost is recorded as the corresponding path cost of the second type of node.

[0016] Optionally, the step of adding each second-type node corresponding to the target node to a priority queue and recording the lowest cost path and the corresponding path cost of the second-type node further includes:

[0017] If the second type of node has been added to the priority queue, determining whether the target path cost is less than the path cost of the second type of node in the priority queue;

[0018] If it is less than, the target path is used as the lowest cost path for the second type of nodes, and the target path cost is recorded as the path cost corresponding to the second type of nodes;

[0019] If it is greater, the minimum cost path of the second type of nodes remains unchanged.

[0020] Optionally, the step of obtaining a target path cost for moving along the target path to the second type of node includes:

[0021] Obtaining the path length of the target path;

[0022] Obtaining an estimated cost from the second type of node to the task endpoint;

[0023] The target path cost is determined based on the path length and the estimated cost.

[0024] Optionally, the step of obtaining an estimated cost from the second type of node to the task endpoint includes:

[0025] Obtaining the Manhattan distance between the task endpoint and the second type of node;

[0026] If turning is required to move from the target node to the second type of node, the turning cost is determined according to a single turning time and a speed of the mobile robot;

[0027] An estimated cost from the second-type node to a task endpoint is determined based on the Manhattan distance and the turning cost.

[0028] Optionally, the formula for the turning cost is:

[0029]

[0030] Where t(x) represents the turning cost, T represents the single turning time, and V represents the speed of the mobile robot.

[0031] Optionally, before determining the new target node, the method further includes:

[0032] Determining whether the priority queue is empty;

[0033] If it is not empty, determine the new target node.

[0034] In a second aspect, an embodiment of the present invention provides a robot path planning device considering turning cost, the device comprising:

[0035] A first processing unit is used to add a first type of node to a priority queue and record the lowest cost path and the corresponding path cost of the first type of node; wherein the first type of node is an idle node adjacent to the task starting point;

[0036] a second processing unit, configured to determine whether a target node is a task endpoint, wherein the target node is a node with the lowest path cost in the priority queue;

[0037] The second processing unit is further configured to determine the minimum cost path of the target node as the task path of the mobile robot if the target node is the task end point;

[0038] The second processing unit is further configured to remove the target node from the priority queue and add a verification mark to the target node if the target node is not the task endpoint;

[0039] The second processing unit is further used to add each second-type node corresponding to the target node to a priority queue, and record the lowest cost path and the corresponding path cost of the second-type node; wherein the second-type node is an idle node adjacent to the target node and does not carry a verification tag;

[0040] The second processing unit is also used to determine a new target node after all second-type nodes corresponding to the target node are added to the priority queue, and repeatedly determine whether the target node is the task endpoint until the target node is the task endpoint or the priority queue is empty.

[0041] In a third aspect, an embodiment of the present invention provides a storage medium having a computer program stored thereon, and the computer program implements the above method when executed by a processor.

[0042] In a fourth aspect, an embodiment of the present invention provides an electronic device, comprising: a processor and a memory, wherein the memory is used to store one or more programs; when the one or more programs are executed by the processor, the above method is implemented.

[0043] Compared with the prior art, the embodiments of the present invention provide a robot path planning method, device, medium and equipment that considers turning costs, add a first-class node to a priority queue, and record the minimum cost path and corresponding path cost of the first-class node; wherein the first-class node is an idle node adjacent to the task starting point; determine whether the target node is the task end point, wherein the target node is the node with the lowest path cost in the priority queue; if the target node is the task end point, the minimum cost path of the target node is determined as the task path of the mobile robot; if the target node is not the task end point, the target node is removed from the priority queue, and a verification mark is added to the target node; each second-class node corresponding to the target node is added to the priority queue, and the minimum cost path and corresponding path cost of the second-class node are recorded; wherein the second-class node is an idle node adjacent to the target node and does not carry a verification mark; after all the second-class nodes corresponding to the target node are added to the priority queue, determine a new target node, and repeatedly determine whether the target node is the task end point until the target node is the task end point or the priority queue is empty. The path cost is determined based on the path length and the number of turns on the path. A step-by-step iterative approach is used to find the lowest-cost path from the task starting point to the task end point, ensuring the optimal operating efficiency of the mobile robot when moving along the task path.

[0044] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0047] Figure 2 One of the flowchart diagrams of the robot path planning method considering the turning cost provided in the embodiment of the present invention.

[0048] Figure 3 A schematic diagram of a grid node provided for the implementation of the present invention.

[0049] Figure 4 The second flowchart of the robot path planning method considering the turning cost provided in the embodiment of the present invention.

[0050] Figure 5 A schematic diagram of a unit of a robot path planning device taking turning cost into consideration provided by an embodiment of the present invention.

[0051] In the figure: 10 - processor; 11 - memory; 12 - bus; 13 - communication interface; 201 - first processing unit; 202 - second processing unit. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0053] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description, and do not necessarily require or imply any such actual relationship or order between these entities or operations, and cannot be understood as indicating or implying relative importance.

[0055] Moreover, the terms "comprises," "comprising," or any other variation thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0056] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0057] The embodiment of the present invention provides an electronic device, which may be a server device, a mobile device, a computer device, etc. The electronic device may be connected to a mobile robot running on a rail network. The mobile robot may be, but is not limited to, a four-way shuttle. Figure 1 , a schematic diagram of the structure of an electronic device. The electronic device includes a processor 10, a memory 11, and a bus 12. The processor 10 and the memory 11 are connected via the bus 12, and the processor 10 is used to execute an executable module stored in the memory 11, such as a computer program.

[0058] The processor 10 can be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the robot path planning method considering the turning cost can be completed by the hardware integrated logic circuit in the processor 10 or the instructions in the form of software. The above-mentioned processor 10 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0059] The memory 11 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory.

[0060] The bus 12 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. Figure 1 Although only one bidirectional arrow is used in the figure, it does not mean that there is only one bus 12 or only one type of bus 12 .

[0061] The memory 11 is used to store programs, such as programs corresponding to a robot path planning device that considers turning costs. The robot path planning device that considers turning costs includes at least one software function module that can be stored in the memory 11 in the form of software or firmware or solidified in the operating system (OS) of the electronic device. After receiving the execution instruction, the processor 10 executes the program to implement the robot path planning method that considers turning costs.

[0062] Possibly, the electronic device provided by the embodiment of the present invention further includes a communication interface 13. The communication interface 13 is connected to the processor 10 via a bus.

[0063] It should be understood that Figure 1The structure shown is only a schematic diagram of a portion of the electronic device. The electronic device may also include Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown. Figure 1 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0064] A robot path planning method considering turning cost provided by an embodiment of the present invention can be applied to, but not limited to, Figure 1 For detailed procedures, please refer to the electronic equipment shown in Figure 2 ,Robot path planning methods considering turning costs include: S10, S20, S30, S40, S50 and S70, which are described in detail as follows.

[0065] S10, adding the first type of nodes to the priority queue, and recording the minimum cost path and the corresponding path cost of the first type of nodes.

[0066] Among them, the first type of node is an idle node adjacent to the task starting point, and the path cost of the minimum cost path of the first type of node is related to the path length of the minimum cost path of the first type of node and the Manhattan distance from the first type of node to the task end point.

[0067] It should be noted that when performing robot path planning that takes turning costs into consideration, the task start point and task end point of the target task are known, and the status information of each node in the current track network (whether it is an idle node) is also known.

[0068] Please refer to Figure 3 , Figure 3 A schematic diagram of a grid node provided for the implementation of the present invention. In which, a filled box indicates a node that has been occupied and / or is scheduled to be occupied, a blank box indicates an idle node, and a dotted arrow indicates the direction of path extension. Node A and Node B are idle nodes adjacent to the starting point of the task, that is, Node A and Node B are first-class nodes.

[0069] Because the first-class node is adjacent to the task starting point, the minimum cost path corresponding to the first-class node is the shortest path from the task starting point directly to the first-class node. Taking node A as an example, you can move directly to node A from the task starting point, or you can go to node A via node B. Therefore, the minimum cost path corresponding to the first-class node needs to be defined here.

[0070] It should be understood that when moving from the task starting point to an adjacent idle node, no turning is required by default, and the path length of the minimum cost path of the first type of node is unit length. Therefore, the path cost corresponding to the minimum cost path corresponding to the first type of node can be determined based on the unit length and the Manhattan distance from the first type of node to the task end point.

[0071] In an optional implementation, the task starting point may be first added to the priority queue, and then the task starting point is used as the target node, and then the idle nodes (first type nodes) adjacent to the task starting point are added to the priority queue.

[0072] S20, determine whether the target node is the task end point. If yes, execute S30; if no, execute S40.

[0073] The target node is the node with the lowest path cost in the priority queue. When there are multiple nodes with equal and lowest path costs in the priority queue, any one of them can be used as the target node.

[0074] S30, determining the minimum cost path of the target node as the task path of the mobile robot.

[0075] S40, removing the target node from the priority queue and adding a verification mark to the target node.

[0076] If the target node is not the end point of the task, you need to continue to search backwards and plan the path. In order to avoid the computational burden and interference caused by repeated consideration of the target node, you can remove the target node from the priority queue and add a verification mark to the target node. Nodes with verification marks will no longer be added to the priority queue, thereby reducing repeated interference and improving computational efficiency.

[0077] S50, adding each second-type node corresponding to the target node to a priority queue, and recording the minimum cost path of the second-type node and the corresponding path cost.

[0078] The second type of nodes are idle nodes that are adjacent to the target node and do not carry a verification tag.

[0079] Please continue to refer to Figure 3 When the target node is node B, the second type of node corresponding to node B is node C; when the target node is node A, the second type of nodes corresponding to node A include node D, node E and node F.

[0080] Among them, the path cost corresponding to the second type of node is related to the path length of the minimum cost path of the second type of node, the Manhattan distance from the second type of node to the task end point, and the turning cost of moving from the target node to the second type of node. When turning is required to move from the target node to the second type of node, there is a turning cost, which is related to the single turning time and the speed of the mobile robot. When turning is not required, the turning cost is zero. The path length of the minimum cost path of the second type of node is equal to the path length of the minimum cost path of the target node plus the unit length.

[0081] It should be noted that, in the embodiment of the present invention, the path with the lowest path cost and the path with the lowest cost are both determined based on a track network of a known range.

[0082] After all the second-type nodes corresponding to the target node are added to the priority queue, S70 is executed to determine whether the task end point has been reached.

[0083] S70: Determine a new target node.

[0084] The node with the lowest path cost in the priority queue is determined as the new target node.

[0085] After S70 , S20 is repeatedly executed to determine whether the target node is the task endpoint, until the target node is the task endpoint or the priority queue is empty.

[0086] The robot path planning method taking turning costs into consideration provided by the embodiment of the present invention determines the path cost based on the path length and the number of turns on the path, and uses a step-by-step iterative approach to find the lowest-cost path from the task starting point to the task end point, thereby ensuring the optimal operating efficiency of the mobile robot when moving along the task path.

[0087] Based on the above, regarding the content in S50, the embodiment of the present invention also provides an optional implementation, please refer to the following. S50, adding each second-class node corresponding to the target node to the priority queue, and recording the minimum cost path of the second-class node and the corresponding path cost, includes: S51, S52, S53, S54, S55 and S56, which are specifically described as follows.

[0088] S51, obtaining a target path cost for moving along the target path to a node of the second type.

[0089] The target path is the shortest path from the task starting point along the lowest cost path of the target node to the second type of node. The target path is the shortest path along the lowest cost path of the target node to the second type of node. Because the second type of node is adjacent to the target node, the shortest path from the target node to the second type of node is added after the lowest cost path along the target node, which is the target path.

[0090] The target path cost is related to the target path length, the Manhattan distance from the second-type node to the task end point, and the turning cost of moving from the target node to the second-type node.

[0091] S52, determine whether the second type of node has been added to the priority queue. If the second type of node has not been added to the priority queue, execute S53; if the second type of node has been added to the priority queue, execute S54.

[0092] S53, adding the second type of nodes to the priority queue, taking the target path as the lowest cost path of the second type of nodes, and recording the target path cost as the path cost corresponding to the second type of nodes.

[0093] S54, determine whether the target path cost is less than the path cost of the second type of node in the priority queue. If so, execute S55; if so, execute S56.

[0094] When the target path cost is equal to the path cost of the second type of node in the priority queue, either S55 or S56 can be executed.

[0095] S55, taking the target path as the lowest cost path of the second type of nodes, and recording the target path cost as the path cost corresponding to the second type of nodes.

[0096] When the target path cost is less than the path cost of the second type of node in the priority queue, it means that the comprehensive cost of moving from the task starting point to the second type of node along the target path is lower, so it is necessary to update the minimum cost path of the second type of node, use the target path as the minimum cost path of the second type of node, and record the target path cost as the path cost corresponding to the second type of node.

[0097] S56, keep the minimum cost path of the second type of nodes unchanged.

[0098] Based on the above, regarding the content in S51, the embodiment of the present invention further provides an optional implementation, please refer to the following: S51, the step of obtaining the target path cost of moving along the target path to the second type of node includes: S511, S512 and S513, which are specifically described as follows.

[0099] S511, obtaining the path length of the target path.

[0100] S512, obtaining an estimated cost from the second type of node to the task endpoint.

[0101] Optionally, S512, the step of obtaining an estimated cost from the second type of node to the task endpoint, includes: S512A, S512B and S512C, which are specifically described as follows.

[0102] S512A, obtain the Manhattan distance between the task endpoint and the second type of node.

[0103] The formula for Manhattan distance is:

[0104]

[0105] Wherein, S(x) represents the Manhattan distance of the target path, that is, the Manhattan distance between the task endpoint and the second type of node, x1 represents the X-axis coordinate of the task endpoint, y1 represents the Y-axis coordinate of the task endpoint, x2 represents the X-axis coordinate of the second type of node, and y2 represents the Y-axis coordinate of the second type of node. In the embodiment of the present invention, the coordinates of each node are determined using the basic coordinate system of the track network.

[0106] S512B: If turning is required to move from the target node to the second type of node, the turning cost is determined according to a single turning time and the speed of the mobile robot.

[0107] Optionally, the formula for the steering cost is:

[0108]

[0109] Among them, t(x) represents the turning cost, T represents the single turning time, and V represents the speed of the mobile robot (which can be but is not limited to the average speed).

[0110] If no turning is required when moving from the target node to the second type of node, the turning cost is 0.

[0111] S512C, determine the estimated cost from the second type of node to the task endpoint based on Manhattan distance and turning cost.

[0112] Optionally, the estimated cost of the target path is calculated as:

[0113]

[0114] Among them, S(x) represents the Manhattan distance of the target path, t(x) represents the turning cost of the target path, and h(x) represents the estimated cost of the target path.

[0115] S513, determining the target path cost according to the path length and the estimated cost.

[0116] Optionally, the sum of the path length and the estimated cost is determined as the target path cost.

[0117] The formula for the target path cost is:

[0118]

[0119] Among them, h(x) represents the estimated cost of the target path, g(x) represents the path length of the target path, and f(x) represents the target path cost.

[0120] exist Figure 2 Based on this, the embodiment of the present invention also provides an optional implementation method, please refer to Figure 4, after all the second-category nodes corresponding to the target node are added to the priority queue and before determining the new target node, the robot path planning method considering the turning cost also includes: S60, which is specifically described as follows.

[0121] S60, determine whether the priority queue is empty. If not, execute S70; if it is empty, it means that there is no path that can complete the target task, and end.

[0122] See also Figure 5 , Figure 5 A robot path planning device taking turning costs into consideration is provided in an embodiment of the present invention. Optionally, the robot path planning device taking turning costs into consideration is applied to the electronic device described above.

[0123] The robot path planning device considering turning cost includes: a first processing unit 201 and a second processing unit 202 .

[0124] The first processing unit 201 is used to add the first type of nodes to the priority queue and record the lowest cost path and the corresponding path cost of the first type of nodes; wherein the first type of nodes are idle nodes adjacent to the task starting point;

[0125] The second processing unit 202 is used to determine whether the target node is the end point of the task, wherein the target node is the node with the lowest path cost in the priority queue;

[0126] The second processing unit 202 is further configured to determine the minimum cost path of the target node as the task path of the mobile robot if the target node is the task end point;

[0127] The second processing unit 202 is further configured to remove the target node from the priority queue and add a verification mark to the target node if the target node is not the task endpoint;

[0128] The second processing unit 202 is further used to add each second-type node corresponding to the target node to the priority queue, and record the minimum cost path and the corresponding path cost of the second-type node; wherein the second-type node is an idle node adjacent to the target node and does not carry a verification tag;

[0129] The second processing unit 202 is further configured to determine a new target node after all the second-category nodes corresponding to the target node are added to the priority queue, and repeatedly determine whether the target node is the task endpoint until the target node is the task endpoint or the priority queue is empty.

[0130] Optionally, the first processing unit 201 is used to execute the above S10, and the second processing unit 202 is used to execute the above S20-S70.

[0131] It should be noted that the robot path planning device considering the turning cost provided in this embodiment can execute the method flow shown in the above method flow embodiment to achieve the corresponding technical effect. For the sake of brief description, for the parts not mentioned in this embodiment, please refer to the corresponding content in the above embodiment.

[0132] The embodiment of the present invention further provides a storage medium, which stores computer instructions and programs, which, when read and run, execute the robot path planning method considering the turning cost of the above embodiment. The storage medium may include a memory, a flash memory, a register, or a combination thereof.

[0133] The following provides an electronic device, which may be a server device, a mobile device, a computer device, etc. Figure 1 As shown, the above-mentioned robot path planning method considering turning cost can be implemented; specifically, the electronic device includes: a processor 10, a memory 11, and a bus 12. The processor 10 can be a CPU. The memory 11 is used to store one or more programs. When the one or more programs are executed by the processor 10, the robot path planning method considering turning cost of the above-mentioned embodiment is executed.

[0134] In summary, the embodiments of the present invention provide a robot path planning method, device, medium and equipment that considers turning costs, add a first-class node to a priority queue, and record the minimum cost path and corresponding path cost of the first-class node; wherein the first-class node is an idle node adjacent to the task starting point; determine whether the target node is the task end point, wherein the target node is the node with the lowest path cost in the priority queue; if the target node is the task end point, the minimum cost path of the target node is determined as the task path of the mobile robot; if the target node is not the task end point, the target node is removed from the priority queue, and a verification mark is added to the target node; each second-class node corresponding to the target node is added to the priority queue, and the minimum cost path and corresponding path cost of the second-class node are recorded; wherein the second-class node is an idle node adjacent to the target node and does not carry a verification mark; after all the second-class nodes corresponding to the target node are added to the priority queue, determine a new target node, and repeatedly determine whether the target node is the task end point until the target node is the task end point or the priority queue is empty. The path cost is determined based on the path length and the number of turns on the path. A step-by-step iterative approach is used to find the lowest-cost path from the task starting point to the task end point, ensuring the optimal operating efficiency of the mobile robot when moving along the task path.

[0135] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0136] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A robot path planning method considering turning cost, characterized in that: The method comprises: Add the first type of nodes to the priority queue, and record the lowest cost path and the corresponding path cost of the first type of nodes; wherein the first type of nodes are idle nodes adjacent to the task starting point; Determine whether the target node is the task endpoint, wherein the target node is the node with the lowest path cost in the priority queue; If the target node is the end point of the task, the minimum cost path of the target node is determined as the task path of the mobile robot; If the target node is not the task endpoint, the target node is removed from the priority queue and a verification mark is added to the target node; Add each second-class node corresponding to the target node to a priority queue, and record the minimum cost path and corresponding path cost of the second-class node; wherein the second-class node is an idle node adjacent to the target node and not carrying a verification tag, and the path cost corresponding to the second-class node is related to the path length of the minimum cost path of the second-class node, the Manhattan distance from the second-class node to the task endpoint, and the turning cost of moving from the target node to the second-class node; After all the second-type nodes corresponding to the target node are added to the priority queue, a new target node is determined, and whether the target node is the task endpoint is repeatedly determined until the target node is the task endpoint or the priority queue is empty; The step of adding each second-type node corresponding to the target node to a priority queue and recording the lowest cost path and the corresponding path cost of the second-type node includes: Obtaining a target path cost along a target path to a second type of node, wherein the target path is a shortest path from the task starting point along a least-cost path of the target node to the second type of node; If the second-type node is not added to the priority queue, add the second-type node to the priority queue, use the target path as the lowest cost path of the second-type node, and record the target path cost as the corresponding path cost of the second-type node; The step of obtaining the target path cost of moving along the target path to the second type of node includes: obtaining the path length of the target path; obtaining the estimated cost from the second type of node to the task end point; determining the target path cost according to the path length and the estimated cost; The step of obtaining the estimated cost from the second type of node to the task endpoint includes: obtaining the Manhattan distance between the task endpoint and the second type of node; if turning is required to move from the target node to the second type of node, determining the turning cost based on a single turning time and a speed of the mobile robot; and determining the estimated cost from the second type of node to the task endpoint based on the Manhattan distance and the turning cost.

2. The robot path planning method considering turning cost as claimed in claim 1, characterized in that: The step of adding each second-type node corresponding to the target node to a priority queue and recording the lowest cost path and the corresponding path cost of the second-type node further includes: If the second type of node has been added to the priority queue, determining whether the target path cost is less than the path cost of the second type of node in the priority queue; If it is less than, the target path is used as the lowest cost path for the second type of nodes, and the target path cost is recorded as the path cost corresponding to the second type of nodes; If it is greater, the minimum cost path of the second type of nodes remains unchanged.

3. The robot path planning method considering turning cost as claimed in claim 1, characterized in that: The formula for the turning cost is: Where t(x) represents the turning cost, T represents the single turning time, and V represents the speed of the mobile robot.

4. The robot path planning method considering turning cost as claimed in claim 1, characterized in that: Before determining the new target node, the method further includes: Determining whether the priority queue is empty; If it is not empty, determine the new target node.

5. A robot path planning device considering turning cost, characterized in that: The device comprises: A first processing unit is used to add a first type of node to a priority queue and record the lowest cost path and the corresponding path cost of the first type of node; wherein the first type of node is an idle node adjacent to the task starting point; a second processing unit, configured to determine whether a target node is a task endpoint, wherein the target node is a node with the lowest path cost in the priority queue; The second processing unit is further configured to determine the minimum cost path of the target node as the task path of the mobile robot if the target node is the task end point; The second processing unit is further configured to remove the target node from the priority queue and add a verification mark to the target node if the target node is not the task endpoint; The second processing unit is also used to add each second-type node corresponding to the target node to a priority queue, and record the minimum cost path and corresponding path cost of the second-type node; wherein the second-type node is an idle node adjacent to the target node and does not carry a verification tag, and the path cost corresponding to the second-type node is related to the path length of the minimum cost path of the second-type node, the Manhattan distance from the second-type node to the task endpoint, and the turning cost of moving from the target node to the second-type node; The second processing unit is further used to determine a new target node after all the second-type nodes corresponding to the target node are added to the priority queue, and repeatedly determine whether the target node is the task endpoint until the target node is the task endpoint or the priority queue is empty; The adding of each second-type node corresponding to the target node to the priority queue and recording the minimum cost path and corresponding path cost of the second-type node includes: obtaining the target path cost of moving along the target path to the second-type node, wherein the target path is the shortest path from the task starting point along the minimum cost path of the target node to the second-type node; if the second-type node is not added to the priority queue, adding the second-type node to the priority queue, using the target path as the minimum cost path of the second-type node, and recording the target path cost as the corresponding path cost of the second-type node; The step of obtaining the target path cost of moving along the target path to the second type of node includes: obtaining the path length of the target path; obtaining the estimated cost from the second type of node to the task end point; and determining the target path cost according to the path length and the estimated cost. The obtaining of the estimated cost from the second type of node to the task endpoint includes: obtaining the Manhattan distance between the task endpoint and the second type of node; if turning is required to move from the target node to the second type of node, determining the turning cost based on a single turning time and a speed of the mobile robot; and determining the estimated cost from the second type of node to the task endpoint based on the Manhattan distance and the turning cost.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

7. An electronic device, characterized in that: include: A processor and a memory, the memory being used to store one or more programs; When the one or more programs are executed by the processor, the method according to any one of claims 1 to 4 is implemented.

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