An AGV scheduling method, system, device and terminal for a storage warehouse

Abstract

The application belongs to the technical field of AGV scheduling, and discloses an AGV scheduling method, system, device and terminal for a storage warehouse, abstracts scheduling information planned in an AGV carrying system of the storage warehouse as a set G and runs loading, calculates a shortest routing table D through a dijkstra algorithm, filters a vehicle type and a state of an AGV performing a task through a task type, obtains an AGV list List AGV , selects the AGV performing the task and the routing D i , segments the D i , adopts an AGV collision-free path planning method based on a time window and a hybrid area control model scheduling method to cut the task routing and issue, displays an AGV position in real time, draws a safe anti-collision detection area far enough in a running direction forward, and divides the safe anti-collision detection area into a deceleration area and a stop area. The application adopts a two-stage algorithm design, reduces real-time operation amount of the AGV moving task, and can process a larger-scale AGV running map in real time.

Description

Technical Field

[0001] This invention belongs to the field of AGV scheduling technology, and particularly relates to an AGV scheduling method, system, equipment and terminal for storage warehouses. Background Technology

[0002] Currently, AGVs, as key equipment in the transportation process of product inbound and outbound goods, play an important role in automated storage and warehousing logistics systems, significantly improving the automation level of storage facilities and thus finding widespread application across various industries. To ensure efficient product inbound and outbound operations, an AGV conveying system in a storage facility often includes multiple conveyor vehicles. In this case, the AGV scheduling system acts as the central hub for multi-vehicle scheduling, providing functions such as AGV vehicle selection, AGV route planning, and AGV collision avoidance to the handling system, forming a complete AGV handling system together with the AGVs. Product storage warehouses are often space-constrained, placing high demands on the operational efficiency and safety of the AGV handling system, which poses a challenge to the scheduling capabilities of the AGV scheduling system. From an economic perspective, the AGV scheduling system should not have excessively high requirements for the operating hardware environment, which challenges the efficiency of the core algorithm of the AGV scheduling system.

[0003] Based on the above analysis, the existing technology has the following problems and shortcomings: the existing AGV handling system has low operating efficiency and safety, poor scheduling capabilities, and high requirements for the operating hardware environment. The computing power requirement of the scheduling system in the AGV handling system will increase exponentially with the increase in the number of AGVs to be scheduled, so it is necessary to optimize the efficiency of the main algorithms of each scheduling link. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides an AGV scheduling method, system, equipment, and terminal for storage warehouses.

[0005] This invention is implemented as follows: an AGV scheduling method for a storage warehouse, comprising: abstracting the planned scheduling information of the storage warehouse AGV handling system into a set G and loading it; calculating the shortest route table D using Dijkstra's algorithm; and filtering the AGVs performing tasks by their vehicle type and status to obtain an AGV list List. AGV And select the AGV to perform the task and route D. i D i The system is segmented, and task routes are trimmed and issued using a time window-based AGV collision-free path planning method and a hybrid region control model scheduling method. The position of the AGV is displayed in real time, and a safe anti-collision detection area that is far enough forward in the running direction is drawn, which is divided into a deceleration zone and a stopping zone.

[0006] Furthermore, the AGV scheduling method for storage warehouses also includes: creating a set of nodes and a set of edges, constructing a map, and using Dijkstra's algorithm to create a shortest route table during the offline phase;

[0007] During the offline phase, vehicle type criteria are filtered, and the shortest route is selected using the shortest route table; the task is segmented and time windows are initialized, and task segments are trimmed; time window conflict detection is performed and it is determined whether a conflict exists; if a time window conflict exists, the process returns to the task segment trimming step; if no time window conflict exists, regional conflict detection is performed and it is determined whether a conflict exists; if a regional conflict exists, the process returns to the task segment trimming step; if no regional conflict exists, the task is issued.

[0008] The task begins execution and graphic overlap detection is performed to determine if there is any overlapping of stopping areas. If there is overlapping of stopping areas, a stop command is sent and the process returns to the graphic overlap detection step. If there is no overlapping of stopping areas, the process checks if there is overlapping of deceleration areas. If there is overlapping of deceleration areas, a deceleration command is sent and the process returns to the graphic overlap detection step. If there is no overlapping of deceleration areas, a recovery command is sent and the process checks if the endpoint has been reached. If the endpoint has not been reached, the process returns to the graphic overlap detection step. If the endpoint has been reached, the task ends.

[0009] Furthermore, the AGV scheduling method for storage warehouses includes the following steps:

[0010] Step 1, Offline Algorithm Stage: The scheduling information planned in the storage warehouse AGV handling system is abstracted into a set using the map pre-planning module, and the shortest route table is constructed using Dijkstra's algorithm;

[0011] Step 2, Online Algorithm Stage: The AGV selection module, path planning module, and AGV display and collision avoidance module are used to segment and trim the queried routes and display the AGV positions in real time.

[0012] Furthermore, the offline algorithm stage in step one includes:

[0013] The scheduling information planned in the AGV handling system of the storage warehouse is abstracted into a set G(V, E), where V is the set of all nodes in the AGV operation map, and E is the node V. i and V i Directly connected node V j The set of edges between them. Set V includes all AGV transfer / lifting points, operation points, error correction points, curve entry and exit points, spin points, and horizontal / oblique movement start and end points. Elements E in set E i Includes attribute l, l is used to mark E iThe weighted values ​​from the starting point to the destination. The AGV operation map abstract set G is a directed weighted graph. G is confirmed based on the scheme design and actual coordinates measured on site during the construction of the AGV handling system in the storage warehouse and stored as a data file of the map pre-planning module.

[0014] After the set G is constructed, the map pre-planning module loads the dataset G and instantiates sets V and E into a list of objects; it then calculates and stores the shortest route table D between any two elements in V using Dijkstra's algorithm.

[0015] Furthermore, for elements V in set V... i It also includes the attribute k, which is used to mark a certain AGV model and whether the status allows it to be in the V i Node access.

[0016] Furthermore, the online algorithm phase in step two includes:

[0017] When the AGV scheduling system receives a task, if the task does not specify an AGV number, the AGV selection module filters the AGVs performing the task based on the task type, vehicle type, and status, resulting in a list of AGVs that meet the criteria. AGV ; Traverse List AGV For all AGV positions, query table D to obtain the element closest to the destination position, which will be the final selected AGV to execute the task. Simultaneously, record the retrieved route as D. i .

[0018] After the AGV executing the task is confirmed, the path planning module will assign D... i The process involves segmenting the task routes and employing a time-window-based AGV collision-free path planning method and a hybrid regional control model scheduling method to trim task routes and control the timing of sending each segment's task route to the AGV.

[0019] When the AGV is running, the AGV display and collision avoidance module displays the AGV's position in real time, and draws a safety collision avoidance detection area that is far enough forward in the running direction, which is divided into a deceleration zone and a stop zone. While drawing, it detects in real time whether the drawn areas overlap. When the deceleration zone overlaps, it issues an acceleration command to the AGV, and when the stop zone overlaps, it issues a stop command to the AGV.

[0020] Another objective of this invention is to provide an AGV scheduling system for a storage warehouse that applies the aforementioned AGV scheduling method for storage warehouses. The AGV scheduling system for storage warehouses includes: a map pre-planning module, an AGV selection module, a path planning module, and an AGV display and collision avoidance module.

[0021] The map pre-planning module is used to abstract the planned scheduling information of the storage warehouse AGV handling system into a set G and run it for loading. It calculates the shortest route table D using the Dijkstra algorithm and stores it.

[0022] The AGV selection module is used to filter the AGVs performing tasks by their type and status, resulting in an AGV list. AGV And select the AGV to perform the task and route D. i ;

[0023] The path planning module is used to... i The task routes are segmented, and a time-window-based AGV collision-free path planning method and a hybrid area control model scheduling method are used to prune the task routes and distribute them.

[0024] The AGV display and collision avoidance module is used to display the position of the AGV in real time, and at the same time draw a safe collision avoidance detection area that is far enough forward in the running direction, which is divided into a deceleration area and a stop area.

[0025] Another object of the present invention is to provide a computer device including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the AGV scheduling method for a storage warehouse.

[0026] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the AGV scheduling method for a storage warehouse.

[0027] Another objective of this invention is to provide an information data processing terminal for implementing the AGV scheduling system for storage warehouses.

[0028] Based on the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solution to be protected by this invention are as follows:

[0029] First, addressing the technical problems existing in the prior art and the difficulty of solving them, this paper closely analyzes, in conjunction with the technical solution to be protected by this invention and the results and data obtained during the research and development process, how the technical solution of this invention solves the technical problems, and the inventive technical effects brought about by solving these problems. The specific description is as follows:

[0030] This invention provides an AGV scheduling method for storage warehouses. It employs a two-stage algorithm design to reduce the real-time computation load during AGV movement tasks, enabling real-time processing of larger-scale AGV operation maps with the same hardware configuration. This invention combines the AGV operation status display function with collision avoidance function, achieving real-time display of AGV position status while performing collision pre-detection, avoiding redundant calculations and further reducing the real-time computation load. This invention uses a routing table-based vehicle selection method to ensure the dispatch of appropriate AGVs to perform tasks. This invention employs a time window and hybrid area control model scheduling method, which has high safety and efficiency. This invention adopts a modular design, with clear and readable code and good maintainability. Therefore, this invention is suitable for AGV scheduling systems in storage warehouses with high requirements for safety and operational efficiency.

[0031] Second, considering the technical solution as a whole or from a product perspective, the technical effects and advantages of the technical solution to be protected by this invention are specifically described as follows:

[0032] In view of the requirements of AGV scheduling system for AGV handling system in storage warehouse, the purpose of this invention is to provide an AGV scheduling system for storage warehouse, which can improve the operating efficiency and safety of AGV handling system, and its core algorithm has high computational efficiency.

[0033] Third, as supplementary evidence of the inventive step of the claims of this invention, it is also reflected in the following important aspects:

[0034] (1) The expected benefits and commercial value of the technical solution of the present invention after transformation are as follows: Due to the improvement of algorithm efficiency, the demand for server computing power can be reduced. The same computing power server can schedule more AGVs, and the same number of AGVs can be scheduled using a server with lower computing power, thereby greatly reducing the economic cost of scheduling server in AGV handling system.

[0035] (2) The technical solution of the present invention fills the technical gap in the industry at home and abroad: The present invention is original in that it introduces the calculation results in the display module into the scheduling module for reuse and performs collision detection, thereby reducing the waste of system resources and improving efficiency.

[0036] (3) The technical solution of the present invention solves the technical problem that people have long wanted to solve but have never been able to succeed in: The present invention provides an optimized method for the application scheduling problem of large maps and multiple AGVs, which helps to solve the problem of large maps and multiple AGVs.

[0037] (4) The technical solution of the present invention overcomes technical bias: The present invention breaks through the conventional software functional module division of the AGV scheduling system, and organically combines the display module and the scheduling module together. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a flowchart of an AGV scheduling method for a storage warehouse provided in an embodiment of the present invention;

[0040] Figure 2 This is a schematic diagram of the AGV scheduling method for storage warehouses provided in an embodiment of the present invention;

[0041] Figure 3 This is a structural diagram of an AGV scheduling system for a storage warehouse provided in an embodiment of the present invention;

[0042] Figure 4 This is an example map of an AGV scheduling system for storage warehouses provided in an embodiment of the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0044] To address the problems existing in the prior art, the present invention provides an AGV scheduling method, system, equipment, and terminal for storage warehouses. The present invention will be described in detail below with reference to the accompanying drawings.

[0045] like Figure 1 As shown, the AGV scheduling method for storage warehouses provided in this embodiment of the invention includes the following steps:

[0046] S101, abstract the planned scheduling information of the storage warehouse AGV handling system into a set G and run the loading, and calculate the shortest route table D through Dijkstra's algorithm;

[0047] S102, filter the AGVs performing the tasks by their vehicle type and status to obtain an AGV list. AGV And select the AGV to perform the task and route D. i ;

[0048] S103, D iThe task is segmented, and a time-window-based AGV collision-free path planning method and a hybrid area control model scheduling method are used to trim and distribute the task routes.

[0049] S104 displays the AGV's position in real time and simultaneously draws a safe anti-collision detection area that is far enough forward in the running direction, which is divided into a deceleration zone and a stop zone.

[0050] As a preferred embodiment, such as Figure 2 As shown, the AGV scheduling method for storage warehouses provided in this embodiment of the invention adopts a two-stage control scheduling strategy. Stage I is the offline algorithm stage, and Stage II is the online algorithm stage, which specifically includes the following steps:

[0051] a. Stage I: The offline algorithm stage is implemented by the map pre-planning module.

[0052] The main task of this stage is to abstract the planned scheduling information of the AGV handling system in the storage warehouse into a set G(V, E), where V is the set of all nodes in the AGV operation map, and E is the node V. i and V i Directly connected node V j The set of edges between. The set V should contain all (if any) AGV transfer / lifting points, operating points, error correction points, curve entry / exit points, spin points, and horizontal / diagonal movement start / end points. For each element V in V... i There should also be an attribute k, which is used to mark a certain AGV model and whether the status allows it to be in the V i Node access. Elements E in set E. i It should include the attribute l, which is used to mark E. i The weighted values ​​from the starting point to the destination. Clearly, the AGV operation map abstraction set G is a directed weighted graph. G is typically determined during the construction of the AGV handling system in the storage warehouse based on the scheme design and actual coordinates measured on-site, and is stored as a data file for the map and planning modules.

[0053] After set G is constructed, the map and planning module loads the dataset G and instantiates sets V and E as a list of objects. Using Dijkstra's algorithm, the shortest route table D between any two elements in V is calculated and stored. The calculation process is as follows:

[0054] S1: Specify a starting point v.

[0055] S2: Introduce two arrays, D and U. D records the vertices for which the shortest path has been found and the corresponding shortest path length, while U records the vertices for which the shortest path has not yet been found and the distance from that vertex to the starting point v.

[0056] S3: Initially, array D contains only the starting point v; array U contains all vertices except the starting point v, and array U records the distance from each vertex to the starting point v. If a vertex is not adjacent to the starting point v, the distance is infinite.

[0057] S4: Find the vertex K with the shortest path from array U and add it to array D; at the same time, remove vertex K from array v. Then, update the distance from each vertex in array v to the starting point v.

[0058] Repeat step S4 until all vertices have been traversed.

[0059] b. Stage II: The online algorithm stage is implemented by the AGV selection module, the path planning module, and the AGV display and collision avoidance module.

[0060] When the AGV scheduling system receives a task, if the task does not specify an AGV number, the AGV selection module filters the AGVs performing the task based on the task type, vehicle type, and status to obtain a list of AGVs that meet the criteria. AGV For example, a task to retrieve goods A requires filtering for empty AGVs that can carry type A goods. Then, the List is iterated through. AGV For all AGV positions, query table D to obtain the element closest to the destination position, which will be the final selected AGV to execute the task. Simultaneously, record the retrieved route as D. i .

[0061] After the AGV executing the task is confirmed, the path planning module will assign D... i The task routes are segmented, and a time-window-based AGV collision-free path planning method and a hybrid area control model scheduling method are adopted to trim the task routes and control the timing when the task routes of each segment are sent to the AGV.

[0062] When the AGV is running, the AGV display and collision avoidance module will show the AGV's position in real time and draw a safe collision avoidance detection area that is far enough ahead in the running direction, divided into a deceleration zone and a stop zone. While drawing, it will detect whether the drawn areas overlap in real time based on whether the pixels in the collision avoidance zone have been colored by other AGVs. When the deceleration zone overlaps, it will issue an acceleration command to the AGV; when the stop zone overlaps, it will issue a stop command to the AGV.

[0063] like Figure 3 As shown, the AGV scheduling system for storage warehouses provided in this embodiment of the invention includes: a map pre-planning module, an AGV selection module, a path planning module, and an AGV display and collision avoidance module.

[0064] The map pre-planning module is used to abstract the planned scheduling information of the storage warehouse AGV handling system into a set G and run it for loading. It calculates the shortest route table D using the Dijkstra algorithm and stores it.

[0065] The AGV selection module is used to filter the AGVs performing tasks by their type and status, resulting in an AGV list. AGV And select the AGV to perform the task and route D. i ;

[0066] The path planning module is used to... i The task routes are segmented, and a time-window-based AGV collision-free path planning method and a hybrid area control model scheduling method are used to prune the task routes and distribute them.

[0067] The AGV display and collision avoidance module is used to display the position of the AGV in real time, and at the same time draw a safe collision avoidance detection area that is far enough forward in the running direction, which is divided into a deceleration area and a stop area.

[0068] The embodiments of the present invention construct a such Figure 4 The diagram shows the AGV operation map. Let A1 and A2 be type A cargo AGVs, with A1 stopping at node 5 and A2 at node 11; let B1 be a type B cargo AGV, stopping at node 1. Node 10 is the type A cargo pickup node, and node 15 is the type B cargo pickup node. Nodes 7 and 8 are modeled as a region. For ease of description, assume all edges have a weight of 1 and bidirectional passage is allowed; both type A and type B AGVs are allowed to pass through all nodes. Assume the AGV scheduling system receives two tasks: a type A cargo pickup task and a type B cargo pickup task.

[0069] Taking the above working condition as an example, the scheduling process of the AGV scheduling system for storage warehouses provided in this embodiment of the invention will be described as follows:

[0070] In the offline algorithm phase, the map pre-planning module creates a map object G, which contains two list members, list V and list E. Objects containing nodes 1 to 15 are stored in list V, and edge objects containing edges 1 to 15 are stored in list E. The shortest route table D between any two elements in V is calculated using Dijkstra's algorithm and stored.

[0071] During the online algorithm phase, for the A-type cargo pickup task, the AGV selection module filters A1 and A2 based on vehicle type to execute the task. A lookup in table D shows that the route from A1 to pickup node 15 is 5-6-7-8-9-10, and the route from A2 to pickup node 15 is 11-12-6-7-8-9-10. Therefore, the route weighting value for A1 is 5l, and the route weighting value for A2 is 6l. Thus, the vehicle selection module decides to assign the A-type cargo pickup task to A1. Similarly, the vehicle selection module decides to assign the B-type cargo pickup task to B1.

[0072] The path planning module segments task A1 (5-10) into segments 5-6, 6-7, 7-8, 8-9, and 9-10; and segments task B1 (1-15) into segments 1-4, 4-8, 8-13, 13-14, and 14-15. Using a time window algorithm, when A1 executes 7-8, node 8 is occupied by B1. According to the hybrid region control model scheduling method, when B1 occupies node 8, node 7 is also occupied by B1. Therefore, task 1-4-8-13-14-15 is sent to B1, and task 5-6 is sent to A1. After B1 reaches node 13, task 7-8-9-10 is sent to A1.

[0073] Create respective display graphics P based on the top views of A1, A2, and B1. A1 P A2 P B1 Based on vehicle speed and parking performance, safety collision detection zones, deceleration zones, and stopping zones are created. The deceleration zone graphic for A1 is P. A1Slow The stopping region is P. A1Stop The AGV display and collision avoidance module displays P in real time. A1 P A2 P B1 P A1Slow P A1Stop The graphic positions are determined, and overlap detection is performed. When the AGV display and collision avoidance module detect P... A1Slow With P A2 P B1 When an overlap occurs, the system will send a deceleration command to A1, causing A1 to slow down; when the AGV display and collision avoidance module detects P... A1Stop With P A2 P B1 When an overlap occurs, the system will send a stop command to A1 to stop A1.

[0074] It should be noted that embodiments of the present invention can be implemented in hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the above-described devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented by hardware circuitry such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of the above-described hardware circuitry and software, such as firmware.

[0075] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention, and within the spirit and principles of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An AGV scheduling method for a storage warehouse, characterized in that, The AGV scheduling method for storage warehouses includes the following steps: Step 1, Offline Algorithm Stage: The scheduling information planned in the storage warehouse AGV handling system is abstracted into a set using the map pre-planning module, and the shortest route table is constructed using Dijkstra's algorithm; Step 2, Online Algorithm Stage: The AGV selection module, path planning module, and AGV display and collision avoidance module are used to segment and trim the queried routes and display the AGV positions in real time; The offline algorithm phase in step one includes: The scheduling information planned in the AGV handling system of the storage warehouse is abstracted into a set G(V, E), where V is the set of all nodes in the AGV operation map, and E is the node V. i and V i Directly connected node V j The set of edges between; set V includes all AGV transfer / lifting points, operation points, error correction points, curve entry and exit points, spin points, and horizontal / oblique movement start and end points; elements E in set E i Includes attribute l, l is used to mark E i The weighted values ​​from the starting point to the end point; G is a directed weighted graph of the AGV operation map abstract set; G is confirmed based on the scheme design and actual coordinates measured on site during the construction of the AGV handling system in the storage warehouse and stored as a data file of the map pre-planning module; After the set G is constructed, the map pre-planning module loads the dataset G and instantiates sets V and E into a list of objects; it then calculates and stores the shortest route table D between any two elements in V using Dijkstra's algorithm. The online algorithm phase in step two includes: When the AGV scheduling system receives a task, if the task does not specify an AGV number, the AGV selection module filters the AGVs performing the task based on the task type, vehicle type, and status, resulting in a list of AGVs that meet the criteria. AGV ; Traverse List AGV For all AGV positions, query table D to obtain the element closest to the destination position, which will be the final selected AGV to execute the task. Simultaneously, record the retrieved route as D. i ; After the AGV executing the task is confirmed, the path planning module will assign D... i The task routes are segmented; a time window-based AGV collision-free path planning method and a hybrid area control model scheduling method are adopted to trim the task routes and control the timing of sending each segment of the task route to the AGV. When the AGV is running, the AGV display and collision avoidance module displays the AGV's position in real time, and draws a safety collision avoidance detection area that is far enough forward in the running direction, which is divided into a deceleration zone and a stop zone. While drawing, it detects in real time whether the drawn areas overlap. When the deceleration zone overlaps, it issues an acceleration command to the AGV, and when the stop zone overlaps, it issues a stop command to the AGV.

2. The AGV scheduling method for a storage warehouse as described in claim 1, characterized in that, The AGV scheduling method for storage warehouses also includes: creating a set of nodes and edges, constructing a map, and using Dijkstra's algorithm to create a shortest route table during the offline phase; During the offline phase, vehicle type criteria are filtered, and the shortest route is selected using the shortest route table; the task is segmented and time windows are initialized, and task segments are trimmed; time window conflict detection is performed and it is determined whether a conflict exists; if a time window conflict exists, the process returns to the task segment trimming step; if no time window conflict exists, regional conflict detection is performed and it is determined whether a conflict exists; if a regional conflict exists, the process returns to the task segment trimming step; if no regional conflict exists, the task is issued. The task begins execution and graphic overlap detection is performed to determine if there is any overlapping of stopping areas. If there is overlapping of stopping areas, a stop command is sent and the process returns to the graphic overlap detection step. If there is no overlapping of stopping areas, the process checks if there is overlapping of deceleration areas. If there is overlapping of deceleration areas, a deceleration command is sent and the process returns to the graphic overlap detection step. If there is no overlapping of deceleration areas, a recovery command is sent and the process checks if the endpoint has been reached. If the endpoint has not been reached, the process returns to the graphic overlap detection step. If the endpoint has been reached, the task ends.

3. The AGV scheduling method for a storage warehouse as described in claim 1, characterized in that, For elements V in set V i It also includes the attribute k, which is used to mark a certain AGV model and whether the status allows it to be in the V i Node access.

4. An AGV scheduling system for a storage warehouse that applies the AGV scheduling method for a storage warehouse as described in any one of claims 1 to 3, characterized in that, AGV scheduling systems used in storage warehouses include: The map pre-planning module is used to abstract the planned scheduling information of the storage warehouse AGV handling system into a set G and run it for loading. It calculates the shortest route table D using the Dijkstra algorithm and stores it. The AGV selection module is used to filter the AGVs performing tasks by their type and status, resulting in an AGV list. AGV And select the AGV to perform the task and route D. i ; The path planning module is used to... i The task routes are segmented, and a time-window-based AGV collision-free path planning method and a hybrid area control model scheduling method are used to prune the task routes and distribute them. The AGV display and collision avoidance module is used to display the position of the AGV in real time, and at the same time draw a safe collision avoidance detection area that is far enough forward in the running direction, which is divided into a deceleration area and a stop area.

5. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the AGV scheduling method for a storage warehouse as described in any one of claims 1 to 3.

6. A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the AGV scheduling method for a storage warehouse as described in any one of claims 1 to 3.

7. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the AGV scheduling system for storage warehouses as described in claim 4.

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