Path planning method and system based on automatic three-dimensional warehouse four-way shuttle vehicle

Abstract

The invention discloses a path planning method and system based on an automatic three-dimensional warehouse four-way shuttle vehicle, and the method comprises the steps: building a storage environment model through a grid method, making traffic rules according to a grid map, and building a map table; based on the map table, generating a task list by using a data memorization processing technology, and sorting according to task priorities; the distributor performs task distribution on the shuttle vehicle according to the task list, performs path planning by using an improved A * algorithm, divides an obtained path into a plurality of road sections, generates time window list information of the road sections, checks whether a time window conflicts with a time window of a planned path node or not, shields the road section corresponding to the time window if the time window conflicts with the time window of the planned path node, and does not shield the path corresponding to the time window if the time window conflicts with the time window of the planned path node. Re-planning the path; otherwise, time window dynamic adjustment is carried out, and the path is executed. According to the invention, conflict judgment is carried out through the time window table of the shuttle vehicle, the possibility of conflict occurrence is further reduced, and the operation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning for shuttle cars in automated warehouses, and particularly to a path planning method and system for four-way shuttle cars based on automated warehouses. Background Art

[0002] In recent years, with the emergence of new business models such as e-commerce and new retail, and the continuous development of modern information technology, the total logistics volume has been continuously increasing, but the logistics efficiency is still at a relatively low level. The automation and intelligent transformation of intelligent warehousing logistics have become the key ways to improve logistics efficiency.

[0003] Intelligent warehousing systems improve warehousing efficiency and management level through intelligent technologies, and have advantages such as high efficiency, low cost, high safety, and high transparency. It can realize operations such as automatic classification, warehousing, storage, and outbound of goods, and quickly meet the market's demand for obtaining goods anytime and anywhere. In addition, intelligent warehousing systems also optimize the warehouse layout and goods locations through data analysis and algorithm models, providing more efficient and customer-friendly logistics services.

[0004] As a typical representative of an innovative intelligent warehousing system, the shuttle car three-dimensional warehouse uses advanced vertical storage technology to store and retrieve goods in three-dimensional space. Compared with the traditional flat storage method, it can increase the storage density by several times, thus greatly saving warehousing space. In today's increasingly tense land resources, shuttle car three-dimensional warehouses have become the choice for many enterprises to improve space utilization.

[0005] Shuttle cars operate in multi-layer automated warehouses, switch floors through lifting mechanisms, and can move in four directions in the same layer of shelves. Their flexible mobility enables shuttle cars to reach any position in the automated warehouse, and the number of deployed shuttle cars can be increased according to the system's load pressure. The above advantages have made shuttle cars surpass stacker cranes and become the first choice in high-density storage systems with high efficiency as the primary indicator. To achieve high throughput efficiency in the warehouse, an efficient scheduling system is also required. The functions that the scheduling system needs to achieve are as follows: task allocation, path planning, traffic control, and equipment adaptation. Among them, the A* algorithm is mostly used for path planning. However, the path obtained under the conventional A* algorithm planning is only the shortest path in terms of space, not necessarily the shortest path in terms of time, because the planned path often has intermediate bends, and in actual operation, the direction change of the shuttle car will seriously affect the operation efficiency. Summary of the Invention

[0006] The object of the present invention is to provide a path planning method and system based on an automated storage four-way shuttle vehicle. On the basis of the conventional A* algorithm, the cost of path bending is introduced, the path planner is constrained to reduce turning points, the running time of the output path is reduced, the running efficiency of the shuttle vehicle is improved, and by using a dynamic scheduling strategy based on time windows, it provides guarantee for the concurrent and efficient operation of multiple shuttle vehicles.

[0007] The present invention adopts the following technical solutions:

[0008] A path planning method based on an automated storage four-way shuttle vehicle, comprising the following steps:

[0009] S1. Use the grid method to establish a warehousing environment model, which includes warehouses, areas, aisles and nodes. According to the grid map, formulate traffic rules and establish a map table.

[0010] S2. Based on the map table, use the data in-memory processing technology to generate a task list and sort it according to the task priorities.

[0011] S3. The allocator assigns tasks to the shuttle vehicles according to the task list, uses an improved A* algorithm for path planning, divides the obtained path into multiple sections, generates the time window list information of the sections, checks whether the time window conflicts with the time windows of the nodes of the already planned path. If there is a conflict, the section corresponding to the time window is blocked and the path is re-planned; otherwise, dynamic time window adjustment is performed and the path is executed.

[0012] Further, in step S1, establishing the map table includes the following contents:

[0013] S101. Set the width of the driving channel of the shuttle vehicle to the width of one grid.

[0014] S102. The driving channels are divided into horizontal channels and vertical channels, both of which are two-way driving.

[0015] S103. The shuttle vehicle can only drive horizontally or vertically and switches directions through a reversing action.

[0016] S104. Only one shuttle vehicle can be accommodated at all points at the same time.

[0017] S105. Each shuttle vehicle only executes one task at the same time.

[0018] S106. The shuttle vehicle updates the status of the relevant positions in the map table after each position change.

[0019] S107. All shuttle vehicle models, performances and parameters are the same.

[0020] S108. The shuttle vehicle performs up and down layer changing operations through a lifting mechanism.

[0021] S109. A region is equivalent to a layer in a stereoscopic warehouse. The region includes a set number of aisles, and each aisle includes a set number of nodes.

[0022] S110. Nodes are classified into storage location nodes, road nodes, charging nodes, parking nodes, lifting mechanism nodes, lifting mechanism connection points, and obstacle nodes according to their types.

[0023] Further, in step S2, the task list includes the following content:

[0024] The task list includes task type, task target location, equipment for executing the task, and task priority; the process of the shuttle vehicle executing the task includes picking up goods, discharging goods, moving, and charging.

[0025] Among them, the process of picking up goods is that the shuttle vehicle travels from the current position to the picking point to pick up goods. After arriving at the picking point, it scans the code for verification. After confirming that there is no error, it lifts the goods through the lifting mechanism; the process of discharging goods is that the shuttle vehicle carries the goods to the target point. After arriving at the target point, it lowers the lifting mechanism to place the goods at the target position; the moving process is that the shuttle vehicle moves to the target point; the charging process is that when the battery level of the shuttle vehicle is lower than 20, a charging task is triggered. If the shuttle vehicle is in the task execution stage, it will travel empty to the target charging point for charging after the task ends. If the shuttle vehicle is in the idle stage, it will charge directly.

[0026] Within a set time period, the tasks in the task list are refreshed and arranged according to the task priorities, and the task with the highest priority is executed first, where the task with the highest priority is the task with the largest assigned value; the priority of the task to be executed is sent down by the upstream system docking after the task is generated.

[0027] Further, in step S3, using the improved A* algorithm for path planning includes the following content:

[0028] S301. Initialize and create an empty open list and a close list, set the starting point and the target point. The open list stores the positions to be detected, and the close list stores the positions that have been traveled. Place the starting point in the open list, calculate the points in the open list using the estimated cost function, move the point with the minimum estimated cost in the open list to the close list, and set it as the current position.

[0029] S302. Add the turning cost t_turn to the estimated cost function to obtain a new estimated cost function. The specific expression is:

[0030] f(n) = g(n) + h(n) + i * t_turn

[0031] Among them, f(n) represents the estimated cost from point n to the target point; g(n) represents the actual cost from the starting point to point n; h(n) represents the estimated cost from point n to the target point and the estimated cost is the Manhattan distance from point n to the target point; i represents the turning mark.

[0032] S303. Calculate the estimated costs of the adjacent positions above, below, left, and right of the current position that are not locked by other task paths according to the traffic rules and the map table in step S1, store the estimated costs in the open list, check whether the target point is in the open list. If the target point is in the open list, the path planning ends and a path is generated; otherwise, find the node with the minimum estimated cost, add it to the close list, and set this point as the current position.

[0033] S304. Repeat S303 until all the positions to be detected are calculated.

[0034] Furthermore, in step S3, the dynamic adjustment of the time window includes the following content:

[0035] The main scheduler receives a heartbeat message from the shuttle during operation, obtains the real-time status information of the shuttle by parsing, recalibrates the time window according to this information, and judges the conflict type.

[0036] The conflict types include encounter conflict, intersection conflict, and rear-end conflict; if it is an encounter conflict, an avoidance scheme is adopted; if it is an intersection conflict, a replanning scheme is adopted; if it is a rear-end conflict, a scheme of inserting a waiting time slice is adopted.

[0037] Update the time window again for conflict checking until there is no conflict.

[0038] Furthermore, the real-time status information includes the position information, executed action information, and fault information of the shuttle.

[0039] Furthermore, the present invention also proposes a path planning system based on an automated storage and retrieval four-way shuttle, including:

[0040] A map table establishment module for establishing a warehousing environment model using the grid method. The model includes warehouses, regions, aisles, and nodes, formulating traffic rules according to the grid map, and establishing a map table.

[0041] A task list generation module for generating a task list based on the map table, using data in-memory processing technology, and sorting according to task priorities.

[0042] The path planning module is used for the allocator to assign tasks to the shuttle vehicle according to the task list, use the improved A* algorithm for path planning, divide the obtained path into multiple sections, generate the time window list information of the sections, check whether the time window conflicts with the time window of the planned path nodes. If there is a conflict, the section corresponding to the time window will be blocked and the path will be replanned; otherwise, dynamic time window adjustment will be performed and the path will be executed.

[0043] Furthermore, the present invention also proposes 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, the steps of the path planning method based on the four-way shuttle vehicle in the automated storage library are implemented.

[0044] Furthermore, the present invention also proposes a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is run by a processor, it executes the path planning method based on the four-way shuttle vehicle in the automated storage library.

[0045] Compared with the prior art, the present invention adopts the above technical solutions and has the following technical effects:

[0046] The method proposed by the present invention reduces the inflection points of the shuttle vehicle's driving path, avoids the increased running time caused by frequent turning of the shuttle vehicle; at the same time, using the above conflict resolution strategy avoids the occurrence of various conflicts, greatly improving the stability of scheduling and the success rate of tasks. Description of the Drawings

[0047] Figure 1 is the overall implementation flowchart of the present invention.

[0048] Figure 2 is the grid map of the warehousing environment in the embodiment of the present invention.

[0049] Figure 3 is the time window scheduling flowchart of the present invention.

[0050] Figure 4 is the path map planned by the traditional A* algorithm of the present invention.

[0051] Figure 5 is the path map planned by the improved A* algorithm of the present invention. Detailed Embodiments

[0052] The present invention will be further described below with reference to the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and cannot be used to limit the protection scope of the present invention.

[0053] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device.

[0054] To achieve the above object, the present invention proposes a path planning method based on an automated vertical warehouse four-way shuttle vehicle, as Figure 1 shown, the specific steps are as follows:

[0055] S1. Use the grid method to establish a warehouse environment model, as Figure 2 shown, the model includes a warehouse, areas, aisles, horizontal channels (main channels), vertical channels (sub-channels) and nodes, formulate traffic rules according to the grid map, and establish a map table; the specific content is:

[0056] S101. Set the width of the shuttle vehicle driving channel to the width of one grid; the size of the grid is just the size required to accommodate the pallet goods.

[0057] S102. The driving channels are divided into horizontal channels and vertical channels, both of which are two-way driving.

[0058] S103. It is impossible to pass through adjacent aisles and between adjacent aisles and sub-channels. The shuttle vehicle can only drive horizontally or vertically and switches directions through a reversing action.

[0059] S104. Only one shuttle vehicle can be accommodated at all points at the same time.

[0060] S105. Each shuttle vehicle only executes one task at the same time.

[0061] S106. The shuttle vehicle updates the status of relevant positions in the map table after each position change.

[0062] S107. All shuttle vehicle models, performances and parameters are the same.

[0063] S108. The shuttle vehicle performs up and down layer-changing operations through a lifting mechanism to ensure that the shuttle vehicle can reach any position in the vertical warehouse. An empty shuttle vehicle (lifting mechanism not raised) can pass under the cargo storage location, while a loaded shuttle vehicle cannot pass through.

[0064] S109. Establish a map data table, which includes a warehouse table, a zone table, a roadway table, and a node table. The warehouse table and the zone table are unique. The combination of the zone table and the node table can uniquely determine a certain location.

[0065] A zone is equivalent to a floor in a stereoscopic warehouse. A zone includes a set number of roadways, and each roadway includes a set number of nodes. After a certain cargo roadway is locked by a certain task, other tasks cannot operate and occupy it.

[0066] S110. Nodes are classified into cargo nodes, road nodes, charging nodes, parking nodes, lifting mechanism nodes, lifting mechanism connection points, and obstacle nodes according to their types.

[0067] During the subsequent task execution process, for any map node where the task is planned into a corresponding path, corresponding time window locking information will be generated and written into the corresponding map node data table. When the corresponding task node is completed, the time window information will be dynamically synchronized and deleted so that the node can be released for subsequent tasks.

[0068] S111. After each state change of the shuttle car, it is necessary to update the relevant state information in the equipment data table, as well as the associated tasks and map data table information.

[0069] S2. After the map table is established, corresponding equipment can be added. Initialize the location information of the equipment, the corresponding speed parameters (providing a basis for subsequent time window calculation), network interfaces, etc. according to the actual location of the equipment. Considering that the time for the shuttle car to load and unload goods is generally fixed, the loading and unloading time information may be entered into the system. Use the data in-memory processing technology to generate a task list and sort it according to the task priority. The specific content is as follows:

[0070] The task list includes task type, task target location, equipment for executing the task, and task priority. The process of the shuttle car executing a task includes picking up goods, unloading goods, moving, and charging. The charging task has the highest priority.

[0071] Among them, the process of picking up goods is as follows: The shuttle car travels from the current location to the picking point to pick up goods. After arriving at the picking point, it scans the code for verification. After confirmation, it lifts the goods through the lifting mechanism. The process of unloading goods is as follows: The shuttle car carries the goods to the target point. After arriving at the target point, it lowers the lifting mechanism to place the goods at the target location. The moving process is as follows: The shuttle car moves to the target point. The charging process is as follows: Charging tasks are triggered manually or when the battery level of the shuttle car is too low (the low battery level is set in the configuration interface, with the default setting of 20). If the shuttle car is in the task execution stage, it will travel empty to the target charging point for charging after the task ends. If the shuttle car is in the idle stage, it will charge directly.

[0072] All newly created task information will be stored in the task data table and read into the system's task queue simultaneously. In a scheduling cycle, the tasks in the task list are refreshed and arranged according to the task priorities. Tasks with higher priorities will be preferentially executed for scheduling the planned path. When two tasks conflict, the task with a lower priority needs to be replanned to avoid the conflict; the priority of the task to be executed is sent down by the upstream system when the task is generated.

[0073] The task with the highest priority is the one with the largest assigned value.

[0074] S3. After a new task is created, the allocator calculates the matching score for the task based on the status of the shuttle vehicle (executing a task, idle, or faulty), the battery level of the shuttle vehicle, and the distance of the shuttle vehicle from the target point of the task in the task list. The optimal shuttle vehicle is selected according to the matching score to execute the task. The improved A* algorithm is used for path planning, and the obtained path is divided into multiple sections to generate the time window list information of the sections. Check whether the time window conflicts with the time window of a high priority (when the shuttle vehicle has planned and locked the forward path nodes). If there is a conflict, the section corresponding to the time window is blocked and the path is replanned; otherwise, dynamic adjustment of the time window is performed and the path is executed.

[0075] Once the path is sent down, other tasks cannot interrupt it. The current shuttle vehicle needs to reapply for the next section after finishing the current section and release the resources of the previous section until it reaches the target point.

[0076] Among them, using the improved A* algorithm for path planning includes the following:

[0077] The first step: Initialize and create an empty open list and a close list, set the starting point and the target point. The open list stores the positions to be detected, and the close list stores the positions that have been traveled. Place the starting point in the open list, calculate the points in the open list using the estimated cost function, move the point with the minimum estimated cost in the open list to the close list, and set it as the current position.

[0078] The second step: Add the turning cost t_turn to the estimated cost function to obtain a new estimated cost function. The specific expression is:

[0079] f(n) = g(n) + h(n) + i * t_turn

[0080] Among them, f(n) represents the estimated cost from point n to the target point; g(n) represents the actual cost from the starting point to point n; h(n) represents the estimated cost from point n to the target point and the Manhattan distance from point n to the target point as the estimated cost; i represents the turning flag, which is 1 when there is a turn when running to the next position, and 0 otherwise.

[0081] Step 3: Calculate the estimated costs of the drivable positions adjacent to the current position (up, down, left, and right) according to the traffic rules and the map table in step S1 (each position of the sub-road and the main road will be set with the drivable directions during the modeling configuration, which can be up, down, left, or right, and drivable means idle and not locked by other task paths), and store the estimated costs in the open list. Check whether the target point is in the open list. If the target point is in the open list, the path planning ends and the path is generated; otherwise, find the node with the minimum estimated cost, add it to the close list, set this point as the current position, and repeat step 3 until all the positions to be detected are calculated.

[0082] As Figure 3 shown, the dynamic adjustment of the time window includes the following contents:

[0083] During the operation, the main scheduler receives the heartbeat message from the shuttle vehicle, obtains the real-time status information of the shuttle vehicle (including the position information, the executed action information, and the fault information) by parsing, recalibrates the time window according to this information (by obtaining the position and action of the shuttle vehicle in real time, releasing the path points that have been traveled, and adjusting the latest time window), and determines the conflict type. The conflict types include encounter conflict, intersection conflict, and rear-end conflict; if it is an encounter conflict, the avoidance scheme attempt is adopted; if it is an intersection conflict, the replanning scheme attempt is adopted; if it is a rear-end conflict, the scheme of inserting a waiting time slice is adopted; update the time window again, perform conflict checking until there is no conflict, and finally reach the target position to complete the task.

[0084] For the avoidance scheme attempt, when the planned time windows of the two vehicles conflict, the lower-priority party attempts to find an avoidance point near the conflict point, inserts a temporary task to go to this avoidance point and executes it immediately. After the task is completed, the execution of the original task is resumed.

[0085] For the replanning scheme attempt, when the above avoidance scheme attempt fails (unable to find an avoidance point), this scheme is executed. When the planned time windows of the two vehicles conflict, the lower-priority party attempts to disable the conflict section and replan the path, and perform conflict checking until a new non-conflicting path is generated, and the shuttle vehicle executes according to the new path.

[0086] For the waiting time slice solution, when both the above avoidance solution and the re-planning solution fail, this solution is executed to list the points where the paths of the two conflicting vehicles have conflicting spaces (without considering time). The low-priority party waits for avoidance at the previous node before entering the set until the high-priority party's vehicle passes through the set area, and the low-priority party resumes the task.

[0087] Set the shuttle state to idle, use the improved A* algorithm to plan a path from the current position back to its nearby parking location, return to wait for the execution of the next task, and directly trigger the charging task if the battery is low.

[0088] By simulating the traditional A* algorithm and the improved A* algorithm respectively, we can get the following results: Figure 4 and Figure 5 The simulation results show that the traditional A* algorithm does not consider the turning point problem in path planning. Too many mid-course switching operations will significantly increase the shuttle's running time and reduce efficiency. The improved A* algorithm introduces the turning cost, which intentionally reduces the turning points in path planning, makes the path smoother, and improves the execution efficiency of the task.

[0089] The map modeling method of the present invention is the grid method, which models the warehouse road conditions with a discrete idea and processes them in a digital way. The specific method is to refine the warehouse floor into countless but limited grids of the same size. Each grid represents a location point, and each location point contains digital location information such as coordinates, allowed direction of passage, occupied or not, etc. The countless and limited location points in the space can establish a spatial coordinate system, so that each grid has a unique coordinate to achieve the purpose of positioning in space. Many adjacent unoccupied grids form a passable path. The specific implementation method in the present invention is to simulate the grid in the form of a QR code landmark or an RF electronic tag, and affix the QR code or electronic tag containing the point information to the divided path ground, and the location information has been entered into the system. The camera on the shuttle obtains the point information by scanning the QR code or reading the RF electronic tag to complete the driving of the task path.

[0090] The embodiment of the present invention also proposes a path planning system based on an automated four-way shuttle in a vertical warehouse, including a map table establishment module, a task list generation module, a path planning module, and a computer program that can be run on a processor. It should be noted that each module in the above system corresponds to the specific steps of the method provided in the embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not described in detail in this embodiment, please refer to the method provided in the embodiment of the present invention.

[0091] An embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor. It should be noted that when the processor executes the computer program, it corresponds to the specific steps of the method provided by the embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. For the technical details not described in detail in this embodiment, reference may be made to the method provided by the embodiment of the present invention.

[0092] An embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program. It should be noted that when the computer program is run by a processor, it corresponds to the specific steps of the method provided by the embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. For the technical details not described in detail in this embodiment, reference may be made to the method provided by the embodiment of the present invention.

[0093] The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A path planning method based on a four-way shuttle vehicle in an automated vertical warehouse, characterized in that: include: S1. Use the grid method to establish a warehouse environment model, which includes warehouses, areas, lanes and nodes, formulate traffic rules based on the grid map, and establish a map table; S2. Based on the map table, a task list is generated using data memory processing technology and sorted according to task priority; S3. The distributor assigns tasks to the shuttle according to the task list, uses the improved A* algorithm for path planning, and divides the obtained path into multiple sections, generates a time window list information for the section, and checks whether the time window conflicts with the time window of the planned path node. If there is a conflict, the section corresponding to the time window is blocked and the path is replanned; otherwise, the time window is dynamically adjusted to execute the path.

2. The path planning method based on the four-way shuttle vehicle in the automated vertical warehouse according to claim 1 is characterized in that: In step S1, establishing a map table includes the following contents: S101, setting the width of the shuttle vehicle driving channel to the width of one grid; S102, the driving channel is divided into a transverse channel and a longitudinal channel, both of which are bidirectional; S103, the shuttle can only travel horizontally or vertically, and switch directions through reversing actions; S104, each point can only accommodate one shuttle at a time; S105. Each shuttle vehicle performs only one task at a time; S106, the shuttle updates the status of the relevant position in the map table after each position change; S107, all shuttle models, performance and parameters are the same; S108, the shuttle car performs up and down layer changing operation through the lifting mechanism; S109, one area is equivalent to one floor in a stereoscopic warehouse, the area includes a set number of lanes, and each lane includes a set number of nodes; S110. Nodes are divided into cargo space nodes, road nodes, charging nodes, parking nodes, lifting mechanism nodes, lifting mechanism connection points and obstacle nodes according to their types.

3. The path planning method based on the four-way shuttle vehicle in the automated vertical warehouse according to claim 1 is characterized in that: In step S2, the task list includes the following contents: The task list includes the task type, the task target location, the equipment to perform the task and the task priority; the process of the shuttle vehicle performing the task includes picking up, unloading, moving and charging; Among them, the picking process is that the shuttle car goes from the current position to the pickup point to pick up the goods. After arriving at the pickup point, it scans the code for verification. After confirmation, the goods are lifted up by the lifting mechanism; the unloading process is that the shuttle car carries the goods to the target point. After arriving at the target point, the lifting mechanism is lowered to place the goods at the target position; the moving process is that the shuttle car moves to the target point; the charging process is that the charging task is triggered when the power of the shuttle car is less than 20. If the shuttle car is in the task execution stage, it will go to the target charging point for charging empty after the task is completed. If the shuttle car is in the idle stage, it will be charged directly; Within the set time period, the tasks in the task list are refreshed and arranged according to their priorities. The highest priority task is executed first, where the highest priority task is the task with the largest numerical value. The priority of the task to be executed is issued by the upstream system after the task is generated.

4. The path planning method based on the four-way shuttle vehicle in the automated vertical warehouse according to claim 1 is characterized in that: In step S3, path planning using the improved A* algorithm includes the following: S301, initialize and create an empty open list and a close list, set the starting point and the target point, store the positions to be detected in the open list, store the traveled positions in the close list, place the starting point in the open list, calculate the points in the open list using the estimated cost function, move the point with the smallest estimated cost in the open list to the close list, and set it as the current position; S302, adding the turning cost t_turn to the estimated cost function to obtain a new estimated cost function, the specific expression of which is: f(n)=g(n)+h(n)+i*t_turn Where f(n) represents the estimated cost from point n to the target point; g(n) represents the actual cost from the starting point to point n; h(n) represents the estimated cost from point n to the target point and the Manhattan distance between the estimated cost of point n and the target point; i represents the turning mark; S303, according to the traffic rules and the map table in step S1, calculate the estimated cost of the positions adjacent to the current position and not locked by other task paths, and store the estimated cost in the open list, check whether the target point is in the open list, if the target point is in the open list, the path planning is completed and the path is generated; otherwise, find the node with the smallest estimated cost, add it to the close list, and set this point as the current position; S304, repeat S303 until all positions to be detected are calculated.

5. The path planning method based on the four-way shuttle vehicle in the automated vertical warehouse according to claim 1 is characterized in that: In step S3, the time window dynamic adjustment includes the following contents: The main dispatcher receives the heartbeat message from the shuttle during operation, obtains the real-time status information of the shuttle through parsing, recalibrates the time window based on the information, and determines the conflict type; Conflict types include encounter conflicts, intersection conflicts, and rear-end conflicts; If it is an encounter conflict, then the avoidance plan is attempted; If it is a conflict at an intersection, then the solution to try the replanning scheme is adopted; If it is a rear-end collision, the solution of inserting a waiting time slice is adopted; Update the time window again to check for conflicts until there are no conflicts.

6. The path planning method based on the four-way shuttle vehicle in the automated vertical warehouse according to claim 5 is characterized in that: Real-time status information includes the shuttle's location information, executed action information, and fault information.

7. A system for the path planning method based on the automated four-way shuttle vehicle in claim 1, characterized in that: include: A map table building module is used to build a warehouse environment model using a grid method. The model includes warehouses, areas, lanes and nodes. Traffic rules are formulated based on the grid map to build a map table. The task list generation module is used to generate a task list based on the map table and use data memory processing technology, and sort the task list according to the task priority; The path planning module is used for the distributor to assign tasks to the shuttle according to the task list, use the improved A* algorithm for path planning, and divide the obtained path into multiple sections, generate the time window list information of the section, check whether the time window conflicts with the time window of the planned path node, if there is a conflict, the section corresponding to the time window is blocked and the path is replanned; otherwise, the time window is dynamically adjusted to execute the path.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the path planning method based on the automated vertical warehouse four-way shuttle vehicle according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the path planning method based on an automated vertical warehouse four-way shuttle vehicle according to any one of claims 1 to 6 is executed.

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