Cold chain warehouse article taking and placing method based on unmanned aerial vehicle

Abstract

The invention discloses a cold chain warehouse article taking and placing method based on an unmanned aerial vehicle, and relates to the field of unmanned aerial vehicle path planning, and the method comprises a cold chain warehouse space where a rasterizing reagent shelf is located and an unmanned aerial vehicle delivery verification area; the unmanned aerial vehicle takes off after receiving the article taking and placing task from the delivery verification area, carries out path planning to take articles from a reagent shelf, and then carries out path planning to return to the delivery verification area; and planning a path when the unmanned aerial vehicle takes off and returns, wherein the path planning is as follows: planning the path for reaching the destination in the three-dimensional space in the shortest time according to the rasterized goods shelf grid occupation condition. According to the cold chain library article taking and placing method based on the unmanned aerial vehicle, rasterization path planning is applied, reagent taking and placing efficiency is guaranteed, and reagent taking and placing tasks are carried out intelligently and orderly.

Description

Technical Field

[0001] The present invention relates to the field of drone path planning, and in particular to a method for taking and placing items in a cold chain warehouse based on a drone. Background Art

[0002] Currently, RFID technology is widely used in cold chain warehouse projects. However, during the process of taking and placing items in cold chain warehouses, there are inconsistencies between the actual items and the RFID tag reading records. In order to confirm that the data is consistent and correct, manual verification at the operating table and other measures are required to avoid errors.

[0003] In the prior art, during the process of picking up and placing items in cold chain warehouses, the low temperature environment of the cold storage is 2-6 degrees, which will cause the personnel who enter the warehouse to pick up the goods to feel uncomfortable. Therefore, it is considered to add drones to the cold chain warehouses, but the flight paths of multiple drones intersect each other when receiving the pickup order data for the picking process, which is prone to flight accidents. Considering that cold storage is a special occasion, drone paths are set and the orderly picking and placing process is managed.

[0004] Therefore, there is an urgent need for a method for picking up and placing items in cold chain warehouses based on drones. Summary of the invention

[0005] The present invention discloses a method for taking and placing items in a cold chain warehouse based on an unmanned aerial vehicle, which solves the problems of the prior art.

[0006] In a first aspect, the present invention provides a method for taking and placing items in a cold chain warehouse based on a drone, comprising: The cold chain warehouse space where the grid reagent shelves are located and the drone delivery inspection area; Plan the path when the drone takes off and returns. The planned path is as follows: After the drone takes off and picks up the reagents, it returns to the delivery inspection area to perform path planning. The planned path is as follows: Plan the shortest path to the destination in three-dimensional space based on the gridded shelf grid occupancy; Among them, the drone takes off, that is, the drone takes off from the delivery and inspection area to receive the item placement mission, and plans the path to the reagent shelf to pick up the items; the drone returns, that is, the drone plans the path from the reagent shelf to the delivery and inspection area.

[0007] Further, it includes: partitioning the gridded cold chain warehouse space into a picking area and a shelf area; In the picking area, the drone waiting time is planned according to the flow control in the flight area; The shelf area is divided into a pickup area and a hovering area. The hovering area is the gridded airspace from the top of the shelf to the ceiling, that is, the drone hovers in the space between the top of the shelf and the ceiling. The reagent pickup area corresponding to the drone's pickup task and the adjacent hovering area are determined to determine whether there is a path occupation in the right-angle turning path from the drone taking off to the corresponding hovering area; The right-angle turning path is a path passing through the center of the three-dimensional space grid and the turning is a right-angle turn; Plan the drone flight path.

[0008] Further, when it is determined that there is an obstacle drone at the corresponding position of the pickup area when the drone arrives at the pickup area through the right-angle turning path, the number of times the obstacle drone appears and the position where the obstacle drone appears are analyzed; When the obstacle drone appears in the pickup area, the current drone will be required to wait for a longer time in the hovering area, waiting for the obstacle drone to take out the reagents and return to the hovering area. Avoidance action strategy: When the obstacle drone appears in the hovering area, the flight path of the obstacle drone is corrected, and the grid where the intersection occurs and the adjacent grid are used as the avoidance area. The obstacle drone and the current drone perform arc avoidance actions synchronously; Analyze whether there are other obstacle drones in the grid occupied by the arc avoidance action, and synchronously execute the avoidance action strategy on other obstacle drones, Furthermore, the right-angle turning path is optimized, and the optimization strategy is: The arc flight path correction is performed on the right-angle turning path based on the grid where the turning point is located and the adjacent grids, and it is analyzed whether the arc flight path causes interference to other UAVs. When interference occurs, the avoidance action strategy is synchronously executed on the other UAVs that cause interference in the grid that causes interference.

[0009] Furthermore, it also includes: iteratively adjusting the optimization strategy until all drones execute the avoidance action strategy.

[0010] Furthermore, when the obstacle drone appears in the picking area, the waiting time of the current drone in the hovering area is increased according to the picking waiting time required by the picking area window and the time when the corresponding obstacle drone leaves the picking area.

[0011] Furthermore, when there is an obstacle corresponding to the hovering zone and the drone performs a hovering flight action, the execution conditions of the avoidance action strategy are not met; The current drone corrects its flight path to the grid near the hovering zone grid occupied by the obstacle drone.

[0012] Furthermore, the current drone corrects the flight path to a grid near the hovering zone grid occupied by the obstacle drone, specifically including: When the current UAV performs a hovering waiting flight operation, the hovering waiting flight operation is performed in a grid near the hovering area grid occupied by the obstacle UAV; When the current UAV performs arc flight path correction, the grid of the hovering area occupied by the obstacle UAV is used as the arc flight direction, and the grid near the grid of the hovering area occupied by the obstacle UAV is used as the flight path point to perform a detour.

[0013] The present invention provides a cold chain warehouse item picking and placing method based on drone, which uses rasterized path planning to ensure the reagent picking efficiency, and the reagent picking and placing tasks are carried out intelligently and orderly. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of the present invention, and do not constitute a limitation of the embodiments of the present invention. In the drawings: Figure 1 A flow chart of a method for retrieving and placing items in a cold chain warehouse based on a drone is provided as an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0015] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0016] The specific application scenario of the present invention is the path planning for the use of reagents by drones in medical cold storage.

[0017] The present invention provides a method for taking and placing items in a cold chain warehouse based on a drone, aiming to solve the above technical problems of the prior art.

[0018] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0019] Embodiment 1: This embodiment provides a method for taking and placing items in a cold chain warehouse based on a drone, such as Figure 1 As shown, including: S1, the cold chain warehouse space where the grid reagent shelves are located and the drone delivery inspection area; The drone takes off from the delivery inspection area to receive the item placement task, performs path planning to pick up items from the reagent shelf, and then plans the path back to the delivery inspection area; the gridded cold chain warehouse space is divided into a picking area and a shelf area; the shelf area is divided into a picking area and a hovering area. The hovering area is the airspace area from the top of the gridded shelf to the ceiling, that is, the drone hovers in the space between the top of the shelf and the ceiling; S2: After the drone takes off and gets the reagents, it returns to the delivery inspection area to perform path planning. The planned path is as follows: Plan the shortest path to the destination in three-dimensional space based on the grid occupancy of the gridded shelves.

[0020] S21. In the picking area, the drone waiting time is planned according to the flow control in the flight area; S22, determining whether there is a path occupancy in the right-angle turning path from the take-off of the drone to the corresponding hovering area, in the pickup area and the adjacent hovering area corresponding to the reagent pickup task of the drone; The right-angle turning path is a path passing through the center of the three-dimensional space grid and the turning is a right-angle turn; S221, when it is determined that there is an obstacle drone at the corresponding position of the pickup area when the drone arrives at the pickup area through the right-angle turning path, the number of times the obstacle drone appears and the position where the obstacle drone appears are analyzed; S2211: Analyze that when the obstacle drone appears in the pickup area, execute S21: increase the waiting time in the hovering area for the current drone, and wait for the obstacle drone to take out the reagent and return to the hovering area; S2212: When the obstacle drone appears in the picking area, the waiting time of the current drone in the hovering area is increased according to the picking waiting time required by the picking area window and the time when the corresponding obstacle drone leaves the picking area.

[0021] S2213, avoidance action strategy: When the obstacle UAV appears in the hovering area, the flight path of the obstacle UAV is corrected, and the grid where the intersection occurs and the adjacent grid are used as the avoidance area. The obstacle UAV and the current UAV perform arc avoidance actions synchronously; S22131. Analyze whether there are other obstacle drones in the grid occupied by the arc avoidance action; Execute S2213 and simultaneously execute avoidance action strategies for other obstacle drones; S22132: When the obstacle drone corresponding to the hovering zone performs a hovering flight action and the execution conditions of the avoidance action strategy are not met, the current drone corrects the flight path to a grid near the hovering zone grid occupied by the obstacle drone.

[0022] S221321. The current UAV corrects its flight path to a grid near the hovering area grid occupied by the obstacle UAV, including: S221322. When the current UAV is performing a hovering waiting flight operation, the hovering waiting flight operation is performed in a grid near the hovering zone grid occupied by the obstacle UAV; S221323. When the current UAV performs arc flight path correction, the grid of the hovering area occupied by the obstacle UAV is used as the arc flight direction, and the grid near the grid of the hovering area occupied by the obstacle UAV is used as the flight path point to perform a detour.

[0023] S23, optimizing the right-angle turning path, the optimization strategy is: The arc flight path correction is performed on the right-angle turning path based on the grid where the turning point is located and the adjacent grids, and it is analyzed whether the arc flight path interferes with other UAVs. When interference occurs, the avoidance action strategy is synchronously executed on other UAVs that cause interference in the grid that causes interference.

[0024] S231. Iteratively adjust the optimization strategy until all drones execute the avoidance action strategy in step S2213.

[0025] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0026] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0027] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0028] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

[0029] Those skilled in the art will appreciate that the embodiments of the present invention may be provided as methods or systems. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects.

[0030] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0031] The above are only embodiments of the present invention and are 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 substitution, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.

[0032] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The description and examples are to be considered exemplary only, and the true scope and spirit of the present invention is indicated by the claims above.

[0033] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for taking and placing items in a cold chain warehouse based on drones, characterized in that: include: The cold chain warehouse space where the grid reagent shelves are located and the drone delivery inspection area; The drone takes off from the delivery inspection area to receive the item placement mission, plans a path to pick up the item from the reagent shelf, and then plans a path back to the delivery inspection area; Plan the path when the drone takes off and returns. The planned path is as follows: Plan the shortest path to the destination in three-dimensional space based on the grid occupancy of the gridded shelf.

2. A method for taking and placing items in a cold chain warehouse based on a drone according to claim 1, characterized in that: include: The grid-type cold chain warehouse space is divided into picking area and shelf area; In the picking area, the drone waiting time is planned according to the flow control in the flight area; The shelf area is divided into a pickup area and a hovering area. The hovering area is the gridded airspace from the top of the shelf to the ceiling, that is, the drone hovers in the space between the top of the shelf and the ceiling. The reagent pickup area corresponding to the drone's pickup task and the adjacent hovering area are determined to determine whether there is a path occupation in the right-angle turning path from the drone taking off to the corresponding hovering area; The right-angle turning path is a path passing through the center of the three-dimensional space grid and the turning is a right-angle turn; Plan the drone flight path.

3. A method for taking and placing items in a cold chain warehouse based on a drone according to claim 2, characterized in that: When it is determined that there is an obstacle drone at the corresponding position of the pickup area when the drone arrives at the pickup area through a right-angle turning path, the number of times the obstacle drone appears and the location where the obstacle drone appears are analyzed; When the obstacle drone appears in the pickup area, the current drone will be required to wait for a longer time in the hovering area, waiting for the obstacle drone to take out the reagents and return to the hovering area. Avoidance action strategy: When the obstacle drone appears in the hovering area, the flight path of the obstacle drone is corrected, and the grid where the intersection occurs and the adjacent grid are used as the avoidance area. The obstacle drone and the current drone perform arc avoidance actions synchronously; Analyze whether there are other obstacle drones in the grid occupied by the arc avoidance action, and synchronously execute the avoidance action strategy on other obstacle drones.

4. A method for taking and placing items in a cold chain warehouse based on a drone according to claim 3, characterized in that: The right-angle turning path is optimized, and the optimization strategy is: The arc flight path correction is performed on the right-angle turning path based on the grid where the turning point is located and the adjacent grids, and it is analyzed whether the arc flight path causes interference to other UAVs. When interference occurs, the avoidance action strategy is synchronously executed on the other UAVs that cause interference in the grid that causes interference.

5. A method for taking and placing items in a cold chain warehouse based on a drone according to claim 4, characterized in that: Also includes: The optimization strategy is iteratively adjusted until all drones execute the avoidance action strategy.

6. A method for taking and placing items in a cold chain warehouse based on a drone according to claim 5, characterized in that: It also includes increasing the waiting time of the current drone in the hovering area when the obstacle drone appears in the picking area according to the picking waiting time required by the picking area window and the time when the corresponding obstacle drone leaves the picking area.

7. A method for taking and placing items in a cold chain warehouse based on a drone according to claim 5 or 3, characterized in that: When there is an obstacle corresponding to the hovering area and the drone performs a hovering flight action, the execution conditions of the avoidance action strategy are not met; The current drone corrects its flight path to the grid near the hovering zone grid occupied by the obstacle drone.

8. The method for taking and placing items in a cold chain warehouse based on a drone according to claim 7 is characterized in that: The current UAV corrects the flight path to a grid near the hovering area grid occupied by the obstacle UAV, specifically including: When the current UAV performs a hovering waiting flight operation, the hovering waiting flight operation is performed in a grid near the hovering area grid occupied by the obstacle UAV; When the current UAV performs arc flight path correction, the grid of the hovering area occupied by the obstacle UAV is used as the arc flight direction, and the grid near the grid of the hovering area occupied by the obstacle UAV is used as the flight path point to perform a detour.

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