Air-ground collaborative material transportation method and device, electronic equipment and storage medium

Abstract

The invention provides an air-ground cooperative material transportation method and device, electronic equipment and a storage medium, and belongs to the technical field of path planning. In the method, the difference value between the robot time cost of a robot to a target handover point and the unmanned aerial vehicle time cost of a target unmanned aerial vehicle corresponding to the target handover point to the target handover point is minimum; the method has the advantages that the space-ground cooperative transportation of space-ground cooperation is greatly enhanced, the efficiency of the space-ground cooperative transportation is improved, in addition, the optimal material transportation path of the target unmanned aerial vehicle is planned by adopting the time cost hindered A star algorithm, and the space-ground cooperative transportation efficiency is improved. According to the invention, when the target unmanned aerial vehicle flies according to the optimal material transportation path, the target unmanned aerial vehicle does not collide with other unmanned aerial vehicles in a flying state, so that mutual collision of the unmanned aerial vehicles in multi-unmanned aerial vehicle transportation is avoided, and the safety is good.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning, and in particular to an air-ground coordinated material transportation method, device, electronic equipment and storage medium. Background Art

[0002] With the rapid development of technology, the logistics and transportation industry is undergoing profound changes. Traditional logistics and transportation methods are particularly inadequate in certain scenarios, especially when facing public health emergencies. Therefore, developing new logistics and transportation methods, particularly for transporting supplies within the complex environments of specialized hospitals, is crucial.

[0003] Robots have been widely used in the logistics sector. For example, in warehouse management, robots can automatically navigate to storage locations and accurately pick goods, significantly improving efficiency. In order processing, automated order processing systems and intelligent sorting systems enable rapid and efficient order processing. Furthermore, robots can be used for inventory management, providing real-time monitoring of inventory status and automatic updates of inventory data.

[0004] Drone technology has also made significant progress in the logistics sector in recent years. Drones can deliver goods quickly and flexibly, making them particularly suitable for remote areas or those with inaccessible transportation. Drone delivery not only significantly reduces delivery times but also improves customer satisfaction. Furthermore, drones offer advantages such as low cost and flexible dispatch, potentially filling gaps in traditional air transport capacity.

[0005] Currently, transporting materials within the air-land collaborative system faces numerous challenges. For one thing, the collaboration between land robots and aerial drones involves waiting time, significantly reducing transport efficiency if tasks are not properly allocated. Furthermore, multiple drones simultaneously carrying materials pose a risk of collision.

[0006] In summary, how to strengthen air-ground collaborative transportation and avoid collisions between drones in multi-UAV transportation have become technical problems that need to be solved urgently. Summary of the Invention

[0007] In view of this, the purpose of the present invention is to provide an air-ground coordinated material transportation method, device, electronic equipment and storage medium to alleviate the technical problems of low efficiency of traditional air-ground coordinated air-ground transportation and collisions between drones in multi-drone transportation.

[0008] In a first aspect, an embodiment of the present invention provides an air-ground coordinated material transportation method, comprising: When the robot located inside the material warehouse receives materials, it calculates the time cost of the robot to each handover point and obtains the time cost of the drone associated with each handover point to reach the corresponding handover point, where the handover point is the position where the robot transfers the materials to the drone; According to the time cost of the robot to each handover point and the time cost of each drone to reach the corresponding handover point, a target handover point is determined among each handover point, and then the robot transports the materials to the target handover point, where the target handover point is the one with the smallest difference between the time cost of the robot to the target handover point and the time cost of the target drone corresponding to the target handover point to reach the target handover point; When the target drone receives the materials at the target handover point, it uses the A* algorithm with time cost obstacle to plan the path of the target drone, and obtains the optimal material transportation path of the target drone, so that the target drone transports the materials to the destination of the materials according to the optimal material transportation path. When the target drone flies according to the optimal material transportation path, it will not collide with other drones in the flying state.

[0009] Further, using the A* algorithm with time cost obstacle to plan the path of the target drone includes: Calculating the total time cost of the drones in the flying state to fly to each flight node, where each flight node is a flyable node obtained by using the A* algorithm with time cost obstacle / A* algorithm to plan the path of the drone; Put the target handover point into the first list as the starting node; Judge whether the first list is empty; If it is empty, the search fails; If there is a target node in the first list, the search is successful, where the target node is the end point of the flight of the target drone, and the end point is the destination of the materials; Take out the node with the smallest f value from the first list as the current node and add it to the second list. The node with the smallest f value taken for the first time is the starting node, and the f value represents the total consumption from the starting node through this node to the target node; Calculate all the reachable adjacent nodes of the current node, and then obtain a set of child nodes; For each child node: If the child node is a flight node of other drones, calculate the absolute value of the difference between the total time cost required for the target drone to reach the child node from the starting node and the total time cost of other drones flying to the child node; If the absolute value of the difference is less than a preset time threshold, discard the child node; If the child node is in the second list, discard the child node; If the child node is in the first list, check whether the f value calculated through the current node is smaller. If it is smaller, update its f value and set its parent node to the current node; If the child node is not in the first list, add it as a node to the first list, calculate its f value through the current node, and set its parent node to the current node; Return to execute the step of judging whether the first list is empty.

[0010] Furthermore, the node includes: a truncated octahedron with an edge length of a preset value.

[0011] Furthermore, according to the time cost calculation formula Calculate the time cost from the current node to its adjacent reachable child nodes, where represents the current node to its adjacent reachable child nodes of the time cost, represents the current node of the average speed function, represents the edge length of the truncated octahedron.

[0012] Furthermore, the total time cost required for the target UAV to reach the child node from the starting node is: , where represents the total time cost required for the target UAV to reach the child node from the starting node required, represents the total time cost required for the target UAV to reach the parent node of the child node from the starting node required, represents the parent node to the child node of the time cost.

[0013] Furthermore, calculating its f value through the current node includes: According to the f value calculation formula Calculate the f value of the child node, where represents the f value of the child node of, represents the estimated consumption from the starting node to the child node required, represents the child node to the target node of the estimated consumption, Indicates a child node Other factors of affect consumption.

[0014] Furthermore, the handover point is arranged outside the material warehouse.

[0015] In a second aspect, an embodiment of the present invention further provides a material transportation device for air-ground cooperation, including: A calculation and acquisition unit, configured to calculate the robot time cost of the robot located inside the material warehouse to each handover point and acquire the drone time cost of the drone associated with each handover point reaching the corresponding handover point when the robot receives the material. Wherein, the handover point is the position where the robot transfers the material to the drone; A determination and transportation unit, configured to determine a target handover point among each handover point according to the robot time cost of the robot to each handover point and the drone time cost of each drone reaching the corresponding handover point. Furthermore, the robot transports the material to the target handover point, where the target handover point is the one with the smallest difference between the robot time cost of the robot to the target handover point and the drone time cost of the target drone corresponding to the target handover point reaching the target handover point; A planning unit, configured to, when the target drone receives the material at the target handover point, use the A* algorithm with time cost obstacle to plan the path of the target drone to obtain the optimal material transportation path of the target drone, so that the target drone transports the material to the destination of the material according to the optimal material transportation path. When the target drone flies according to the optimal material transportation path, it will not collide with other drones in a flying state.

[0016] In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method according to any one of the above first aspects.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium stores machine-executable instructions. When the machine-executable instructions are called and run by the processor, the machine-executable instructions cause the processor to run the method according to any one of the above first aspects.

[0018] In an embodiment of the present invention, a method for air-ground collaborative material transportation is provided, including: when a robot located inside a material warehouse receives materials, calculating the robot time cost for the robot to reach each transfer point, and obtaining the drone time cost for a drone associated with each transfer point to reach the corresponding transfer point, where the transfer point is the position where the robot transfers the materials to the drone; determining a target transfer point among the transfer points according to the robot time cost for the robot to reach each transfer point and the drone time cost for each drone to reach the corresponding transfer point, and then the robot transports the materials to the target transfer point, where the target transfer point is the one with the smallest difference between the robot time cost for the robot to reach the target transfer point and the drone time cost for the target drone corresponding to the target transfer point to reach the target transfer point; when the target drone receives the materials at the target transfer point, using the A* algorithm with time cost obstacle to plan the path of the target drone, obtaining the optimal material transportation path of the target drone, so that the target drone transports the materials to the destination of the materials according to the optimal material transportation path, where when the target drone flies according to the optimal material transportation path, it will not collide with other drones in the flying state. Through the above description, it can be seen that in the air-ground collaborative material transportation method of the present invention, the difference between the robot time cost for the robot to reach the target transfer point and the drone time cost for the target drone corresponding to the target transfer point to reach the target transfer point is the smallest, that is, the waiting time between the robot and the target drone at the target transfer point is the shortest, which greatly enhances the air-ground collaborative transportation of air-ground cooperation and improves the efficiency of air-ground collaborative transportation. In addition, the optimal material transportation path of the target drone planned by using the A* algorithm with time cost obstacle can ensure that when the target drone flies according to the optimal material transportation path, it will not collide with other drones in the flying state, that is, it avoids the collision of drones in multi-drone transportation, has good safety, and alleviates the technical problems of low efficiency of traditional air-ground collaborative transportation of air-ground cooperation and collision of drones in multi-drone transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0020] Figure 1 It is a flowchart of a method for air-ground collaborative material transportation provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of a truncated octahedron provided by an embodiment of the present invention; Figure 3Schematic diagram of the truncated octahedron for tiling provided by an embodiment of the present invention; Figure 4 Schematic diagram of a ground-air collaborative material transportation device provided by an embodiment of the present invention; Figure 5 Schematic diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0021] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0022] The traditional ground-air collaborative transportation efficiency of ground-air cooperation is low, and there is a risk of collision between unmanned aerial vehicles (UAVs) in multi-UAV transportation.

[0023] Based on this, in the ground-air collaborative material transportation method of the present invention, the difference between the robot time cost of the robot reaching the target handover point and the UAV time cost of the target UAV corresponding to the target handover point reaching the target handover point is minimized, that is, the waiting time between the robot and the target UAV at the target handover point is the shortest, which greatly enhances the ground-air collaborative transportation of ground-air cooperation and improves the efficiency of ground-air collaborative transportation. In addition, the optimal material transportation path of the target UAV planned by the A* algorithm with time cost obstruction can ensure that when the target UAV flies along the optimal material transportation path, it will not collide with other UAVs in the flight state, that is, it avoids the collision between UAVs in multi-UAV transportation and has good safety.

[0024] For the convenience of understanding this embodiment, a ground-air collaborative material transportation method disclosed in an embodiment of the present invention will be introduced in detail first.

[0025] Embodiment 1: According to an embodiment of the present invention, an embodiment of a ground-air collaborative material transportation method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0026] Figure 1 is a flowchart of a ground-air collaborative material transportation method according to an embodiment of the present invention. As Figure 1 shown, the method includes the following steps: Step S102, when the robot located inside the material warehouse receives the material, calculate the time cost of the robot to each transfer point, and obtain the time cost of the UAV associated with each transfer point to reach the corresponding transfer point, where the transfer point is the position where the robot transfers the material to the UAV. In the embodiments of the present invention, the unmanned aerial vehicle is abbreviated as "UAV", and its English abbreviation is "UAV". It is an unpiloted aircraft controlled by a radio remote control device and a self - contained program control device, or is completely or intermittently autonomously operated by an on - board computer.

[0027] The method of the present invention is realized by the collaborative transportation of the robot and the UAV. Professional transportation intelligent robots are deployed inside the material warehouse, and professional transportation UAVs are deployed outside the material warehouse. The robot picks up the material in the warehouse and delivers it to the target transfer point. At the target transfer point, the material is handed over between the robot and the UAV, and then the UAV transports the material to the destination of the material.

[0028] The present invention allocates the cooperation between the aerial UAV and the ground robot in the time dimension. When the robot located inside the material warehouse receives the material, calculate the time cost of the robot to each transfer point, and obtain the time cost of the UAV associated with each transfer point to reach the corresponding transfer point. The above - mentioned robot time cost is specifically the time required for the robot to reach each transfer point, and the UAV time cost is specifically the time required for the UAV to reach the corresponding transfer point.

[0029] Professional intelligent robots are deployed inside the material warehouse. The robot can automatically navigate to the designated area according to the instruction, pick up the goods through the grabbing module, and then deliver them. The robot body is equipped with a variety of sensors, with reliable environmental perception and dynamic obstacle avoidance capabilities, and can achieve high - precision positioning and navigation in a complex environment. At the transfer point, the robot can transport the material to the UAV. The UAV receives the material and then quickly and accurately delivers the goods to the destination of the material. Through the UAV, the enterprise can cover a wider geographical area and reach more potential customers.

[0030] Step S104, based on the time cost of the robot to each transfer point and the time cost of each UAV to reach the corresponding transfer point, determine the target transfer point among the transfer points. Then the robot transports the material to the target transfer point, where the target transfer point is the one with the smallest difference between the time cost of the robot to the target transfer point and the time cost of the target UAV corresponding to the target transfer point to reach the target transfer point. Step S106, when the target UAV receives the supplies at the target handover point, use the A* algorithm with time-cost obstacle to plan the path of the target UAV, and obtain the optimal supply transportation path of the target UAV, so that the target UAV transports the supplies to the destination of the supplies according to the optimal supply transportation path. When the target UAV flies along the optimal supply transportation path, it will not collide with other UAVs in the flight state.

[0031] Specifically, the traditional A* algorithm is a classic heuristic search algorithm, which is evolved by combining the advantages of the Dijkstra algorithm and the BFS (Breadth-First Search) algorithm. The A* algorithm with time-cost obstacle of the present invention adds time-cost obstacle (i.e., calculating the obstacles in path finding with the time dimension to form path planning) on the basis of the traditional A* algorithm (i.e., the path finding algorithm of the UAV) to prevent UAVs in different time dimensions from colliding. That is, when the target UAV flies along the optimal supply transportation path (planned by the A* algorithm with time-cost obstacle), it will not collide with other UAVs in the flight state.

[0032] In an embodiment of the present invention, a method for air-ground collaborative material transportation is provided, including: when a robot located inside a material warehouse receives materials, calculating the robot time cost of the robot to each transfer point, and obtaining the drone time cost of the drone associated with each transfer point to reach the corresponding transfer point, where the transfer point is the position where the robot transfers the materials to the drone; determining a target transfer point among the transfer points according to the robot time cost of the robot to each transfer point and the drone time cost of each drone to reach the corresponding transfer point, and then the robot transports the materials to the target transfer point, where the target transfer point is the one with the smallest difference between the robot time cost of the robot to the target transfer point and the drone time cost of the target drone corresponding to the target transfer point to reach the target transfer point; when the target drone receives the materials at the target transfer point, using the A* algorithm with time cost obstacle to plan the path of the target drone, obtaining the optimal material transportation path of the target drone, so that the target drone transports the materials to the destination of the materials according to the optimal material transportation path, where when the target drone flies according to the optimal material transportation path, it will not collide with other drones in the flying state. Through the above description, it can be seen that in the air-ground collaborative material transportation method of the present invention, the difference between the robot time cost of the robot to the target transfer point and the drone time cost of the target drone corresponding to the target transfer point to reach the target transfer point is the smallest, that is, the waiting time between the robot and the target drone at the target transfer point is the shortest, which greatly strengthens the air-ground collaborative transportation of air-ground cooperation and improves the efficiency of air-ground collaborative transportation. In addition, the optimal material transportation path of the target drone planned by using the A* algorithm with time cost obstacle can make the target drone not collide with other drones in the flying state when flying according to the optimal material transportation path, that is, it avoids the collision of drones in multi-drone transportation, has good safety, and alleviates the technical problems of low efficiency of traditional air-ground collaborative transportation of air-ground cooperation and collision of drones in multi-drone transportation.

[0033] The above content briefly introduces the air-ground collaborative material transportation method of the present invention, and the following will describe the specific content involved in detail.

[0034] In an optional embodiment of the present invention, using the A* algorithm with time cost obstacle to plan the path of the target drone specifically includes the following steps: (1) Calculating the total time cost of the drones in the flying state to fly to each flight node, where each flight node is a flyable node obtained by planning the path of the drone using the A* algorithm with time cost obstacle / A* algorithm. Specifically, before this step, determine the starting nodes and target nodes of all running drones, and convert the longitude, latitude, and altitude information of the drones at the current moment into scene coordinates (x, y, z). The same coordinate system facilitates calculations. This process is to establish a scene coordinate system, and further convert the longitude, latitude, and altitude information of the drones into the scene coordinate system.

[0035] When the drone is the first drone, the flight nodes are the flyable nodes obtained by using the A* algorithm to plan the path of the first drone. It should be noted that when the drones take off, they take off one by one in sequence, rather than multiple drones taking off simultaneously. That is, after the path planning of one drone is completed, another drone that receives the supplies can take off.

[0036] The calculation process of the above total time cost is as follows: First, calculate the time cost of the drone from one flight node to another adjacent flight node (the calculation process of the time cost is described below and can be referred to the introduction below), and then sum up the calculated time costs from the current flight node to any flight node to obtain the total time cost of any flight node.

[0037] (2) Put the target handover point as the starting node into the first list; (3) Determine whether the first list is empty; (4) If it is empty, the search fails; (5) If the target node exists in the first list, the search is successful, where the target node is the end point of the target drone's flight, and the end point is the destination of the supplies; Specifically, after the search is successful, the nodes in the second list are used as the flight nodes on the planned optimal material transportation path. When implemented, starting from the target node, continuously search for the stored parent nodes until the starting node is found. The route composed of all nodes is the optimal material transportation path of the target drone. The above first list can specifically be the open list.

[0038] (6) Take the node with the smallest f value from the first list as the current node and add it to the second list, where the node with the smallest f value taken for the first time is the starting node, and the f value represents the total consumption from the starting node through this node to the target node; Specifically, the above node is specifically the node corresponding to the f value. The above second list can specifically be the close list.

[0039] (7) Calculate all adjacent reachable nodes of the current node to obtain a set of child nodes; (8) For each child node: If the child node is a flight node of another UAV, calculate the absolute value of the difference between the total time cost required for the target UAV to reach this child node from the starting node and the total time cost for the other UAVs to fly to this child node; Specifically, the above-mentioned other UAVs are specifically other UAVs in a flying state.

[0040] If the absolute value of the difference is less than the preset time threshold, discard this child node; Specifically, when the absolute value of the difference is less than the preset time threshold, it indicates that the target UAV will collide with other UAVs in a flying state, and this child node cannot be used as a flight node of the target UAV. The above operation can avoid the planned path of the target UAV from meeting other flying UAVs at the same time. That is, when calculating f(n) in the topological grid of the traditional A* algorithm, calculate a new total time cost at the same time, and draw the real-time state of the topological grid reached by the current A* algorithm according to the result obtained by comparing the total time costs. After discarding this child node, calculate the f value of the remaining child nodes through the current node.

[0041] If this child node is in the second list, discard this child node; Specifically, after discarding this child node, calculate the f value of the remaining child nodes through the current node.

[0042] If this child node is in the first list, check whether the f value calculated through the current node is smaller. If it is smaller, update its f value and set its parent node to the current node; Specifically, if this child node is already in the first list and the f value of this child node in the first list is greater than the f value of this child node calculated through the current node, use the smaller f value to update the f value of this child node in the first list and set its parent node to the current node.

[0043] If this child node is not in the first list, add it as a node to the first list, calculate its f value through the current node, and set its parent node to the current node; Specifically, after the f value is calculated, store the f value in the current node, that is, obtain the f value of the current node, and set its parent node to the current node.

[0044] (9) Return to the step of judging whether the first list is empty.

[0045] In an optional embodiment of the present invention, the node includes: a truncated octahedron with an edge length of a preset value.

[0046] Specifically, the nodes here include the parent node, child node, flight node, starting node, target node and node in the above text, and they are all truncated octahedrons with an edge length of a preset value, such as Figure 2As shown, the schematic diagram of the corresponding truncated octahedron for tiling is as Figure 3 shown.

[0047] The truncated octahedron is a semiregular polyhedron with fourteen faces, belonging to the Archimedean solids and also a parallelepiped. It is composed of 6 squares and 8 regular hexagons, with a total of 14 faces, 36 edges, and 24 vertices. Since each face has point symmetry properties, the truncated octahedron is also a zonotope. It can be seen that for the pathfinding algorithm in three-dimensional space in the present invention, the flight area of the unmanned aerial vehicle is tiled with truncated octahedrons with an edge length of a preset value and used as the basic table of A*, on the one hand, the truncated octahedron can tile the space, and on the other hand, the truncated octahedron has enough faces compared with the cube, and the flight directions of the unmanned aerial vehicle are more comprehensive and rich.

[0048] In an alternative embodiment of the present invention, according to the time cost calculation formula calculate the time cost from the current node to the reachable child nodes adjacent to it, where represents the current node to the reachable child nodes adjacent to it the time cost of, represents the current node the average speed function of, represents the edge length of the truncated octahedron.

[0049] In an alternative embodiment of the present invention, the total time cost required for the target unmanned aerial vehicle to reach the child node from the starting node is: , where represents the total time cost required for the target unmanned aerial vehicle to reach the child node from the starting node, represents the total time cost required for the target unmanned aerial vehicle to reach the parent node of the child node from the starting node, represents the parent node to the child node the time cost of.

[0050] In an alternative embodiment of the present invention, calculating its f value through the current node includes: According to the f value calculation formula calculate the f value of the child node, where represents the f value of the child node , represents the estimated consumption from the starting node to the child node , represents the child node to the estimated consumption of the target node, represents the child node the consumption affected by other factors of.

[0051] Specifically, the process of calculating the f value is the same as that in the traditional technology and will not be elaborated here.

[0052] In an alternative embodiment of the present invention, the handover point is set outside the material warehouse.

[0053] It should be noted that hereafter, every time a new unmanned aerial vehicle (UAV) takes off from the starting node or takes off from the target node and returns to the starting node, the above operation of planning the path of the target UAV using the A* algorithm with time cost obstruction is repeated.

[0054] The method of the present invention can solve the transportation problems in scenarios where it is not suitable for human transportation due to infection risks, etc.; it can solve the transportation problems in scenarios where it is not suitable for land transportation due to terrain problems, etc.; it can solve the problems of UAV collisions and strengthen air-ground cooperation in multi-UAV transportation; a path planning method for avoiding multi-UAV collisions in the time dimension.

[0055] The method of the present invention realizes the intelligent planning and dynamic adjustment of the UAV flight path by introducing truncated octahedron tiling, the A* algorithm, as well as the time cost function and the f value calculation method. This path planning method can be flexibly adjusted according to the actual situation to ensure that the UAV can complete the task efficiently and accurately.

[0056] Embodiment 2: The embodiment of the present invention also provides an air-ground collaborative material transportation device, which is mainly used to execute the air-ground collaborative material transportation method provided in Embodiment 1 of the present invention. The following is a specific introduction to the air-ground collaborative material transportation device provided by the embodiment of the present invention.

[0057] Figure 4 is a schematic diagram of an air-ground collaborative material transportation device according to an embodiment of the present invention. As Figure 4 shown, the device mainly includes: a calculation and acquisition unit 10, a determination and transportation unit 20, and a planning unit 30, where: The calculation and acquisition unit is used to calculate the robot time cost from the robot located inside the material warehouse to each handover point and acquire the UAV time cost for the UAV associated with each handover point to reach the corresponding handover point when the robot receives the material, where the handover point is the position where the robot transfers the material to the UAV; A determination and transportation unit, which is used to determine a target handover point among various handover points according to the robot time cost of the robot reaching each handover point and the drone time cost of each drone reaching the corresponding handover point, and then the robot transports the supplies to the target handover point, where the target handover point is the one with the smallest difference between the robot time cost of the robot reaching the target handover point and the drone time cost of the target drone corresponding to the target handover point reaching the target handover point; A planning unit, which is used to, when the target drone receives the supplies at the target handover point, use the A* algorithm with time cost obstruction to plan the path of the target drone, and obtain the optimal supply transportation path of the target drone, so that the target drone transports the supplies to the destination of the supplies according to the optimal supply transportation path, where when the target drone flies according to the optimal supply transportation path, it will not collide with other drones in a flying state.

[0058] In an embodiment of the present invention, a ground-air collaborative supply transportation device is provided, including: when a robot located inside a supply warehouse receives supplies, it calculates the robot time cost of the robot reaching each handover point, and obtains the drone time cost of the drone associated with each handover point reaching the corresponding handover point, where the handover point is the position where the robot transfers the supplies to the drone; according to the robot time cost of the robot reaching each handover point and the drone time cost of each drone reaching the corresponding handover point, a target handover point is determined among various handover points, and then the robot transports the supplies to the target handover point, where the target handover point is the one with the smallest difference between the robot time cost of the robot reaching the target handover point and the drone time cost of the target drone corresponding to the target handover point reaching the target handover point; when the target drone receives the supplies at the target handover point, use the A* algorithm with time cost obstruction to plan the path of the target drone, and obtain the optimal supply transportation path of the target drone, so that the target drone transports the supplies to the destination of the supplies according to the optimal supply transportation path, where when the target drone flies according to the optimal supply transportation path, it will not collide with other drones in a flying state. Through the above description, it can be seen that in the ground-air collaborative supply transportation device of the present invention, the difference between the robot time cost of the robot reaching the target handover point and the drone time cost of the target drone corresponding to the target handover point reaching the target handover point is the smallest, that is, the waiting time between the robot and the target drone at the target handover point is the shortest, which greatly strengthens the ground-air collaborative transportation of ground-air cooperation and improves the efficiency of ground-air collaborative transportation. In addition, the optimal supply transportation path of the target drone planned by using the A* algorithm with time cost obstruction can enable the target drone not to collide with other drones in a flying state when flying according to the optimal supply transportation path, that is, it avoids the collision of drones in multi-drone transportation, has good safety, and alleviates the technical problems of low efficiency of traditional ground-air collaborative transportation of ground-air cooperation and collision of drones in multi-drone transportation.

[0059] Optionally, the planning unit is further configured to: calculate the total time cost for the UAV in flight to reach each flight node, where each flight node is a flyable node obtained by planning the path of the UAV using the A* algorithm / A* algorithm with time cost obstruction; put the target handover point as the starting node into the first list; determine whether the first list is empty; if it is empty, the search fails; if the target node exists in the first list, the search succeeds, where the target node is the end point of the target UAV's flight, and the end point is the destination of the supplies; take out the node with the smallest f value from the first list as the current node and add it to the second list, where the node with the smallest f value taken for the first time is the starting node, and the f value represents the total consumption from the starting node through this node to reach the target node; calculate all reachable adjacent nodes of the current node to obtain a set of child nodes; for each child node: if the child node is a flight node of another UAV, calculate the absolute value of the difference between the total time cost required for the target UAV to reach this child node from the starting node and the total time cost for another UAV to fly to this child node; if the absolute value of the difference is less than the preset time threshold, discard this child node; if the child node is in the second list, discard this child node; if the child node is in the first list, check whether the f value calculated through the current node is smaller, and if it is smaller, update its f value and set its parent node to the current node; if the child node is not in the first list, add it as a node to the first list, calculate its f value through the current node, and set its parent node to the current node; return to execute the step of determining whether the first list is empty.

[0060] Optionally, the node includes: a truncated octahedron with an edge length of a preset value.

[0061] Optionally, according to the time cost calculation formula Calculate the time cost from the current node to its reachable adjacent child nodes, where, represents the current node to its reachable adjacent child nodes of the time cost, represents the current node of the average speed function, represents the edge length of the truncated octahedron.

[0062] Optionally, the total time cost required for the target UAV to reach this child node from the starting node is: , where, represents the total time cost required for the target UAV to reach this child node from the starting node required, represents the total time cost required for the target UAV to reach the parent node of this child node from the starting node required, Indicates the parent node to this child node of the time cost.

[0063] Optionally, the planning unit is further configured to: calculate the f-value according to the f-value calculation formula calculate the f-value of this child node, where represents the f-value of this child node of the f-value, represents the estimated consumption from the starting node to the child node of the estimated consumption, represents the child node to the estimated consumption of the target node, represents the child node of the impact of other factors on the consumption.

[0064] Optionally, the handover point is set outside the material warehouse.

[0065] The device provided by the embodiments of the present invention has the same implementation principle and the same technical effects as those of the foregoing method embodiments. For a brief description, for the parts not mentioned in the device embodiments, reference may be made to the corresponding content in the foregoing method embodiments.

[0066] Such as Figure 5 shown, an electronic device 600 provided by an embodiment of the present application includes: a processor 601, a memory 602, and a bus. The memory 602 stores machine-readable instructions executable by the processor 601. When the electronic device runs, the processor 601 communicates with the memory 602 through the bus, and the processor 601 executes the machine-readable instructions to perform the steps of the material transportation method for air-ground cooperation as described above.

[0067] Specifically, the above-mentioned memory 602 and processor 601 can be general-purpose memory and processor, which are not specifically limited here. When the processor 601 runs the computer program stored in the memory 602, it can execute the material transportation method for air-ground cooperation as described above.

[0068] The processor 601 may be an integrated circuit chip with the ability to process signals. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in the processor 601 or the instructions in the form of software. The above-mentioned processor 601 may be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it may also be a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field-programmable gate array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by the combination of the hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory 602, and the processor 601 reads the information in the memory 602 and combines its hardware to complete the steps of the above method.

[0069] Corresponding to the above-mentioned air-ground collaborative material transportation method, an embodiment of the present application further provides a computer-readable storage medium, which stores machine-executable instructions. When the computer-executable instructions are called and run by a processor, the computer-executable instructions cause the processor to run the steps of the above-mentioned air-ground collaborative material transportation method.

[0070] The air-ground collaborative material transportation device provided by the embodiments of the present application may be specific hardware on the device or software or firmware installed on the device, etc. For the device provided by the embodiments of the present application, the implementation principle and the technical effects produced are the same as those of the foregoing method embodiments. For the sake of brief description, for the parts not mentioned in the device embodiments, reference may be made to the corresponding content in the foregoing method embodiments. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can all refer to the corresponding processes in the above method embodiments, and will not be repeated here.

[0071] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some communication interfaces. The indirect coupling or communication connection of the devices or units can be in electrical, mechanical or other forms.

[0072] For another example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment or a part of code, and the module, program segment or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0073] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0074] In addition, the functional units in the embodiments provided in the present application can be integrated in one processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0075] When the above-mentioned function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing an electronic device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the air-ground collaborative material transportation method described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM for short), random access memories (RAM for short), magnetic disks, or optical discs that can store program codes.

[0076] It should be noted that: similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In addition, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0077] Finally, it should be noted that: the above-mentioned embodiments are only specific implementation manners of this application, used to illustrate the technical solution of this application, rather than limiting it. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: any person skilled in the art within the technical scope disclosed in this application can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or make equivalent replacements for some of the technical features; and these modifications, changes, or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A method for material transportation with air-ground cooperation, characterized in that, Including: When a robot inside the material warehouse receives materials, it calculates the robot time cost from the robot to each handover point, and obtains the UAV time cost for the UAV associated with each handover point to reach the corresponding handover point, where the handover point is the position where the robot transfers the materials to the UAV. Based on the robot time cost from the robot to each handover point and the UAV time cost for each UAV to reach the corresponding handover point, a target handover point is determined among the handover points, and then the robot transports the materials to the target handover point, where the target handover point is the one with the smallest difference between the robot time cost from the robot to the target handover point and the UAV time cost for the target UAV corresponding to the target handover point to reach the target handover point. When the target UAV receives the materials at the target handover point, it uses the A* algorithm with time cost obstruction to plan the path of the target UAV, obtaining the optimal material transportation path for the target UAV, so that the target UAV transports the materials to the destination of the materials according to the optimal material transportation path, where when the target UAV flies according to the optimal material transportation path, it will not collide with other UAVs in the flying state.

2. The method according to claim 1, wherein Using the A* algorithm with time cost obstruction to plan the path of the target UAV includes: Calculating the total time cost for the UAVs in the flying state to fly to each flight node, where each flight node is a flyable node obtained by planning the path of the UAV using the A* algorithm with time cost obstruction / A* algorithm. Taking the target handover point as the starting node and putting it into the first list. Judging whether the first list is empty. If it is empty, the search fails. If there is a target node in the first list, the search is successful, where the target node is the end point of the flight of the target UAV, and the end point is the destination of the materials. Taking out the node with the smallest f value from the first list as the current node and adding it to the second list, where the first node with the smallest f value taken is the starting node, and the f value represents the total consumption from the starting node through this node to reach the target node. Calculating all the adjacent reachable nodes of the current node, and thus obtaining a set of child nodes. For each child node: If this child node is the flight node of other UAVs, then calculate the absolute value of the difference between the total time cost required for the target UAV to reach this child node from the starting node and the total time cost for other UAVs to fly to this child node. If the absolute value of the difference is less than the preset time threshold, then discard this child node. If this child node is in the second list, then discard this child node. If this child node is in the first list, then check whether the f value calculated through the current node is smaller. If it is smaller, then update its f value and set its parent node to the current node. If the child node is not in the first list, add it as a node to the first list, calculate its f value through the current node, and set its parent node as the current node; Return to the step of determining whether the first list is empty.

3. The method according to claim 2, wherein The node includes: a truncated octahedron with an edge length of a preset value.

4. The method according to claim 3, wherein According to the time cost calculation formula Calculate the time cost from the current node to its adjacent reachable child nodes, where represents the current node to its adjacent reachable child nodes of the time cost represents the average speed function of the current node of represents the edge length of the truncated octahedron.

5. The method according to claim 4, wherein The total time cost required for the target UAV to travel from the starting node to the child node is: , where represents the total time cost required for the target UAV to travel from the starting node to the child node , represents the total time cost required for the target UAV to travel from the starting node to the parent node of the child node , represents the parent node to the child node time cost.

6. The method according to claim 2, wherein Calculating its f value through the current node includes: Calculate the formula according to the f value Calculate the f value of this child node, where represents this child node of the f value represents the estimated cost from the start node to the child node of represents the child node to the estimated cost of the target node represents the child node of the impact of other factors on consumption 7. The method according to claim 1, wherein The transfer point is set outside the material warehouse.

8. An air-ground collaborative material transportation device, characterized in that, Includes: A calculation and acquisition unit, configured to calculate the robot time cost of the robot located inside the material warehouse to each transfer point and acquire the UAV time cost of the UAV associated with each transfer point to reach the corresponding transfer point when the robot receives materials, wherein the transfer point is the position where the robot transfers the materials to the UAV; A determination and transportation unit, configured to determine a target transfer point among the transfer points according to the robot time cost of the robot to each transfer point and the UAV time cost of each UAV to reach the corresponding transfer point, and then the robot transports the materials to the target transfer point, wherein the target transfer point is the one with the smallest difference between the robot time cost of the robot to the target transfer point and the UAV time cost of the target UAV corresponding to the target transfer point to reach the target transfer point; A planning unit, configured to, when the target UAV receives the materials at the target transfer point, use the A* algorithm with time cost obstacle to plan the path of the target UAV to obtain the optimal material transportation path of the target UAV, so that the target UAV transports the materials to the destination of the materials according to the optimal material transportation path, and when the target UAV flies according to the optimal material transportation path, it will not collide with other UAVs in a flying state.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 above are implemented.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores machine-executable instructions, and when the machine-executable instructions are called and run by the processor, the machine-executable instructions cause the processor to run the method according to any one of claims 1 to 7 above.

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