A scheduling control method and system for warehouse AGV

Abstract

The application discloses a kind of scheduling control method and system for warehousing AGV, it is related to the technical field of AGV intelligent inventory, method includes: receiving the inventory request sent by user;Query warehouse aisle data from the preset warehousing database and call A algorithm;According to warehouse aisle data, A algorithm is optimized, and global path planning is carried out using optimized A algorithm;Global path planning is adjusted and obstacle avoidance using dynamic window method locally, and inventory path graph is generated;According to inventory path graph, generate inventory instruction and execute;Obtain monitoring environment change data, build real-time environment map, update global path in real time and re-plan local path;In dynamic environment, using fusion algorithm avoids dynamic obstacles and unknown static obstacles, meets the requirements of global optimal path and dynamic obstacle avoidance in complex map.The application has the effect of improving AGV inventory efficiency.

Description

Technical Field

[0001] This invention relates to the technical field of AGV control, and more particularly to a scheduling and control method and system for warehouse AGVs. Background Technology

[0002] In recent years, logistics warehousing systems have been widely used in various industries. Warehouse system management includes storage, handling, and sorting. Currently, intelligent handling systems, intelligent storage systems, and intelligent picking systems applied in the logistics industry have automated warehouse storage, handling, and sorting, and can replace human labor to a certain extent.

[0003] An AGV (Automated Guided Vehicle) is a transport vehicle capable of traveling along a predetermined guided path and possessing automatic control functions. It typically consists of a walking mechanism, drive system, control system, sensors, and auxiliary equipment, and can be widely used in industrial enterprises, logistics warehousing, and other fields. In a warehousing environment, AGVs can automatically complete tasks such as handling, storing, and sorting goods, significantly improving warehouse operational efficiency.

[0004] Regarding the aforementioned technologies, the inventors believe that the following defects exist: when AGV forklifts are taking inventory of goods in the warehouse, due to the complex terrain of the warehouse, it is difficult for the AGV to find the optimal path during the operation, resulting in low work efficiency of the AGV. Summary of the Invention

[0005] To improve the inventory management efficiency of AGV forklifts, this invention provides a scheduling and control method and system for warehouse AGVs.

[0006] The present invention provides a scheduling and control method and system for warehouse AGVs, which adopts the following technical solution:

[0007] In a first aspect, the present invention provides a scheduling and control method for warehouse AGVs, comprising the following steps:

[0008] Receive inventory check requests sent by users, the inventory check requests carrying inventory check information for controlling AGVs to conduct inventory checks on warehouse items;

[0009] Query warehouse aisle data from the pre-set warehouse database and retrieve Algorithm A;

[0010] Based on the warehouse aisle data, the A algorithm is optimized, and the optimized A algorithm is used for global path planning;

[0011] The dynamic window method is used to perform local path adjustments and obstacle avoidance on the global path planning, generating a database path map;

[0012] Based on the inventory path diagram, generate and execute inventory instructions;

[0013] Acquire data on changes in the monitoring environment, build a real-time environmental map, and update the global path and replan the local path in real time;

[0014] In dynamic environments, fusion algorithms are used to avoid dynamic obstacles and unknown static obstacles, satisfying the requirements of global optimal path and dynamic obstacle avoidance in complex maps.

[0015] By adopting the above technical solutions, the system can quickly respond to and execute inventory counts of warehouse items by receiving inventory requests from users and carrying inventory information. This improves the efficiency and accuracy of warehouse management and reduces errors and omissions caused by manual operations. Utilizing warehouse aisle data in a pre-set warehouse database, combined with an optimized A algorithm for global path planning, the system ensures that AGVs (Automated Guided Vehicles) move along the optimal path within the warehouse. This not only reduces AGV movement time and energy consumption but also improves the efficiency of inventory count execution. Using a dynamic window method to adjust local paths and avoid obstacles ensures that AGVs can flexibly respond to obstacles or environmental changes, avoiding collisions and stalls. This enhances the system's robustness and adaptability, improving the reliability and safety of inventory count tasks. By acquiring monitoring data on environmental changes and constructing a real-time environmental map, the system can instantly update the global path and replan local paths. This ensures that AGVs always move along the optimal path in dynamic environments, improving the real-time performance and accuracy of inventory count tasks. In dynamic environments, using fusion algorithms to avoid both dynamic and unknown static obstacles ensures that AGVs meet the requirements of globally optimal paths and dynamic obstacle avoidance in complex maps. This further enhances the system's intelligence and flexibility, enabling it to cope with various complex scenarios and challenges.

[0016] Optionally, before the step of generating and executing the disk drive instruction, the method further includes:

[0017] Based on the inventory path diagram, "virtual lanes" are divided in the physical space to guide the AGV to travel along a fixed path, reducing the possibility of conflicts at intersections;

[0018] According to the inventory path diagram, a passage indicator device is installed at the intersection of AGVs to control the right of way in different directions and avoid AGV collisions.

[0019] A scheduling algorithm is used to optimize the task allocation and travel route of each AGV through a central control system and priority settings;

[0020] By using historical data analysis and machine learning models, we can predict peak periods and congestion points, and take measures in advance to disperse traffic. By using modeling and simulation tools, we can simulate the operation of AGVs in different scenarios and identify and resolve potential problems in advance.

[0021] By analyzing obstacle types, key path points are extracted, redundant path points are eliminated, the total number of path turns is reduced, and the global path length is shortened.

[0022] We used modeling software to create a digital twin of the warehouse's interior, tested different path planning strategies, and evaluated their effectiveness.

[0023] Optionally, the step of generating and executing the disk drive instruction specifically includes:

[0024] Real-time acquisition of actual warehouse item identification;

[0025] Retrieve the warehouse item type corresponding to the actual warehouse item identifier from the preset warehouse database;

[0026] Based on the actual warehouse item identifier, the cumulative quantity of warehouse items corresponding to the warehouse item type is generated.

[0027] The type of warehouse item and the quantity of warehouse items corresponding to the type of warehouse item are pushed to the user's smart terminal.

[0028] By adopting the above technical solution, after receiving the inventory request sent by the user, the inventory system generates an inventory instruction based on the pre-stored warehouse aisle data in the database, causing the AGV to travel along the aisle path in the warehouse. During the AGV's movement, the inventory system acquires the actual warehouse item identification in real time, identifies and classifies the acquired item identification, and pushes the identified warehouse item types and the corresponding warehouse item quantities to the user's smart terminal. This allows the AGV to check and count the items in the warehouse while moving, eliminating the need for frequent handling operations and improving the inventory efficiency of the AGV.

[0029] Optionally, prior to the step of obtaining the actual warehouse item identification, the method further includes:

[0030] Real-time acquisition of AGV's position;

[0031] Based on the AGV's travel position, determine the actual shelf position with the smallest distance from the AGV's travel position;

[0032] The actual shelf spacing is determined based on the AGV's travel position and the actual shelf position.

[0033] Query the preset shelf spacing corresponding to the actual shelf spacing from the preset warehouse database;

[0034] If the actual shelf spacing is less than the preset shelf spacing, then the step of obtaining the actual warehouse item identification is performed.

[0035] By adopting the above technical solution, during the movement of the AGV, the inventory system detects whether the AGV is moving close to the shelf that needs to be inventoried. When the AGV moves close to the shelf that needs to be inventoried, the inventory system begins to acquire the actual warehouse item identification. When the AGV has not yet moved close to the shelf that needs to be inventoried, the inventory system does not acquire the actual warehouse item identification, so that the AGV will not acquire the identification of all the items on the shelves it passes during the movement, thereby improving the item checking function of the inventory system and reducing data redundancy.

[0036] Optionally, after the step of obtaining the actual warehouse item identification, the method further includes:

[0037] Based on the actual warehouse item identifier, obtain the location of the actual warehouse item corresponding to the actual warehouse item identifier;

[0038] The actual item spacing is generated based on the actual warehouse item location and the AGV travel position;

[0039] If the actual item spacing is greater than the preset shelf spacing, a label deletion instruction is generated and executed. The label deletion instruction is used to delete the label of the actual warehouse item.

[0040] By adopting the above technical solution, when the inventory system follows the movement of the AGV and performs identification and acquisition operations on the items on the current shelf, the inventory system is prone to misidentifying items on other shelves that are close to each other. At this time, the inventory system determines whether the item is located on the shelf to be scanned by judging the actual distance between the AGV and the item. When the actual distance between the item and the shelf is greater than the preset shelf distance, it means that the item is not located on the shelf to be scanned. At this time, the inventory system generates an identification deletion command to delete the actual warehouse item identification corresponding to the current item, so that the inventory system can orderly identify and count the items on each shelf during the inventory process.

[0041] Optionally, after determining the actual shelf position with the smallest distance from the AGV's travel position, the method further includes:

[0042] Retrieve the pre-stored shelf item identifier corresponding to the actual shelf location from the preset warehouse database;

[0043] If the actual warehouse item identification does not match the pre-stored shelf item identification, then the inconsistent item identification is determined;

[0044] Based on the inconsistent item identifiers, an inventory check order is generated;

[0045] The inventory work order is pushed to the user's smart terminal.

[0046] By adopting the above technical solution, during the inventory operation of a shelf, the inventory system compares the actual warehouse item identification on the shelf with the pre-stored shelf item identification in the database to determine whether the current storage status of the items on the shelf is accurate. When there is a discrepancy between the actual warehouse item identification and the pre-stored shelf item identification, it indicates that there is an error in the placement of the items on the shelf. At this time, the inventory system identifies the inconsistent item identification, generates an inventory work order, and outputs it, so that the user can know the specific item information of the incorrect placement in the warehouse.

[0047] Optionally, after the step of determining the inconsistent item identifier, the method further includes:

[0048] Retrieve the correct shelf label corresponding to the inconsistent item label from the preset warehouse database;

[0049] If the corresponding correct shelf identifier exists, then the incorrect shelf identifier corresponding to the inconsistent item identifier is invoked;

[0050] If the corresponding incorrect shelf identifier exists, an item misplacement instruction is generated and executed. The item misplacement instruction is used to update the record of the correct shelf identifier and the incorrect shelf identifier corresponding to the inconsistent item identifier to the inventory work order.

[0051] If the corresponding incorrect shelf identifier does not exist, an item shortage instruction is generated and executed. The item excess instruction is used to update the record of the correct shelf identifier corresponding to the inconsistent item identifier to the inventory work order.

[0052] By adopting the above technical solution, when the inventory system detects incorrect placement of items, it identifies and judges the type of error. If the item should not be placed on the current shelf but should be placed on another shelf in the warehouse, then the item has a misplacement error. The inventory system generates an item misplacement instruction and adds the correct shelf label and the incorrect shelf label corresponding to the inconsistent item label to the inventory work order. If the inconsistent item label only has a correct shelf label and no incorrect shelf label, it means that the corresponding item that should be placed on the correct shelf label does not exist in the warehouse, indicating that the warehouse is missing the item corresponding to the current item label. In this case, the inventory system generates an item shortage instruction and adds the correct shelf label corresponding to the inconsistent item label to the inventory work order, allowing users to see the specific error type of the misplaced item by browsing the inventory work order.

[0053] Optionally, after the step of querying the correct shelf label corresponding to the inconsistent item label from a preset warehouse database, the method further includes:

[0054] If the corresponding correct shelf identifier does not exist, then the step of calling the incorrect shelf identifier corresponding to the inconsistent item identifier is executed;

[0055] Based on the inconsistent item identifier and the corresponding incorrect shelf identifier, an item over-placement instruction is generated and executed. The item over-placement instruction is used to update the record of the incorrect shelf identifier corresponding to the inconsistent item identifier to the inventory work order.

[0056] By adopting the above technical solution, when the inventory system can only obtain the incorrect shelf identifier corresponding to the current item, but cannot obtain the correct shelf identifier corresponding to the current item, it means that there is an item on a shelf in the current warehouse that should not be stored in this warehouse. The item is redundant for this warehouse. At this time, the inventory system generates an item over-placement instruction and adds the incorrect shelf identifier corresponding to the inconsistent item identifier to the inventory work order, so that the user can take the product out of the warehouse later.

[0057] Optionally, before the step of generating and executing the disk library instruction, the following steps are also included:

[0058] The warehouse partition information corresponding to the warehouse aisle data is retrieved from the preset warehouse database. The warehouse partition information includes the warehouse division area and the warehouse area location corresponding to the warehouse division area.

[0059] Based on the warehouse partitioning information, multiple warehouse partitioning areas are generated, and each warehouse partitioning area includes multiple warehouse partitioning areas.

[0060] Based on the inventory division areas, generate division area numbers corresponding to the inventory division areas;

[0061] Based on the number of areas to be divided in the inventory, an AGV activation command is generated and executed. The AGV activation command is used to start the corresponding number of AGVs according to the number of areas to be divided in the inventory.

[0062] Query the activated AGV serial number from the preset warehouse database;

[0063] Based on the partitioned area number and the activated AGV number, a zone allocation instruction is generated and executed, wherein the zone allocation instruction corresponds to the partitioned area number and the activated AGV number.

[0064] Based on the inventory division area and the warehouse aisle data, an inventory travel path corresponding to the activated AGV sequence number is generated;

[0065] Based on the inventory movement path, execute the steps of generating inventory instructions and performing them;

[0066] Based on the activated AGV sequence number, the inventory control command is pushed to the corresponding AGV.

[0067] By adopting the above technical solution, the inventory system divides the entire warehouse into multiple different inventory areas based on the warehouse zoning information, and plans the inventory movement paths within each inventory area. The inventory system simultaneously activates a number of AGVs corresponding to the number of inventory areas, with each AGV corresponding to one inventory area. The inventory system pushes the inventory movement paths to the corresponding AGVs, enabling multiple AGVs to move simultaneously to perform inventory checks on the warehouse items, thus improving the inventory efficiency of the AGVs.

[0068] Secondly, the present invention provides a scheduling and control system for warehouse AGVs, which adopts the following technical solution:

[0069] A scheduling and control system for warehouse AGVs includes:

[0070] The inventory request receiving module is used to receive inventory requests sent by users, the inventory requests carrying inventory information for controlling AGVs to conduct inventory checks on warehouse items;

[0071] The walkway data query module is used to query warehouse walkway data from a preset warehouse database and retrieve Algorithm A.

[0072] The path planning module is used to optimize the A algorithm based on the warehouse aisle data and use the optimized A algorithm for global path planning.

[0073] The inventory path map generation module is used to perform local path adjustments and obstacle avoidance on the global path planning using a dynamic window method, and generate an inventory path map.

[0074] The inventory check instruction generation module is used to generate and execute inventory check instructions based on the inventory check path diagram.

[0075] The local path planning module is used to acquire monitoring environment change data, build a real-time environment map, update the global path in real time, and replan the local path.

[0076] The obstacle avoidance module is used to avoid dynamic obstacles and unknown static obstacles in dynamic environments using a fusion algorithm, and to meet the requirements of global optimal path and dynamic obstacle avoidance in complex maps.

[0077] In summary, compared with the prior art, the beneficial effects of the above technical solution are:

[0078] (1) After receiving the inventory request sent by the user, the inventory system generates an inventory instruction based on the pre-stored warehouse aisle data in the database, so that the AGV can travel in the warehouse according to the aisle path. During the travel of the AGV, the inventory system obtains the actual warehouse item identification in real time, identifies and classifies the obtained item identification, and pushes the identified warehouse item type and the warehouse item quantity corresponding to the warehouse item type to the user's smart terminal. In this way, the AGV can check and count the items in the warehouse during the movement, without having to perform frequent handling operations on the items, thus improving the inventory efficiency of the AGV.

[0079] (2) During the movement of the AGV, the inventory system detects whether the AGV has moved close to the shelf that needs to be inventoried. When the AGV moves close to the shelf that needs to be inventoried, the inventory system starts to acquire the actual warehouse item identification. When the AGV has not moved close to the shelf that needs to be inventoried, the inventory system does not acquire the actual warehouse item identification, so that the AGV will not acquire the identification of all the items on the shelf it passes through during the movement, thereby improving the item checking function of the inventory system and reducing data redundancy.

[0080] (3) When the inventory system follows the movement of the AGV and performs identification and acquisition operations on the items on the current shelf, the inventory system is prone to misidentifying items on other shelves that are close to each other. At this time, the inventory system determines whether the item is located on the shelf to be scanned by judging the actual distance between the AGV and the item. When the actual distance between the item and the shelf is greater than the preset shelf distance, it means that the item is not located on the shelf to be scanned. At this time, the inventory system generates an identification deletion command to delete the actual warehouse item identification corresponding to the current item, so that the inventory system can identify and check the items on each shelf in an orderly manner during the inventory process. Attached Figure Description

[0081] Figure 1 This is a flowchart illustrating a scheduling and control method for warehouse AGVs according to an embodiment of the present invention.

[0082] Figure 2 This is a schematic diagram of the process of generating and executing a command to misplace an item in an embodiment of the present invention. Detailed Implementation

[0083] The present invention will be further described in detail below with reference to all the accompanying drawings.

[0084] This invention discloses a scheduling and control method and system for warehouse AGVs, referring to... Figure 1 A scheduling and control method for warehouse AGVs, comprising:

[0085] S101: Receive disk access requests sent by users.

[0086] The inventory request carries inventory information used to control the AGV to conduct an inventory check of warehouse items. When a user wants to conduct an inventory check of the items stored in the warehouse, the user sends an inventory request through a smart terminal, enabling the inventory system to understand the user's needs and then begin the subsequent inventory check operation.

[0087] S102: Query warehouse aisle data from the preset warehouse database and retrieve Algorithm A.

[0088] Specifically, based on inventory information, the system queries the relevant warehouse aisle data (such as shelf location, aisle width, etc.) from the warehouse database, and retrieves preset A algorithms (such as Dijkstra's algorithm, A* algorithm, etc.) for path planning, providing necessary data support for subsequent path planning.

[0089] S103: Optimize Algorithm A and use the optimized Algorithm A for global path planning.

[0090] Specifically, based on the actual situation of warehouse aisle data, the system optimizes Algorithm A by optimizing the heuristic function, reducing the number of path points, and smoothing paths. The optimized Algorithm A is then used for global path planning. This optimization of the path planning algorithm makes the generated paths more consistent with the actual warehouse conditions, thus improving inventory counting efficiency.

[0091] S104: Use the dynamic window method to perform local path adjustment and obstacle avoidance on the global path planning, and generate a database path map.

[0092] Specifically, the system uses a dynamic window method to adjust local paths and avoid obstacles in the global path planning, generating a warehouse inventory path map. Based on the global path planning, the system uses dynamic window methods (such as speed, acceleration, and other constraints) to adjust the path locally and avoid obstacles, generating a warehouse inventory path map. This ensures that the AGV can flexibly respond to changes in the local environment during operation, such as avoiding obstacles and adjusting its speed.

[0093] S105: Generate and execute disk access instructions.

[0094] Specifically, the system generates inventory instructions based on the inventory path diagram and sends them to the AGVs for execution. This automates the inventory operation for the AGVs, improving inventory efficiency and accuracy.

[0095] S106: Build a real-time environment map.

[0096] Specifically, the system acquires environmental change data (such as changes in obstacle positions, the addition of new obstacles, etc.) through monitoring devices such as sensors and constructs a real-time environmental map. Based on the real-time environmental map, the system updates the global path and replans local paths in real time. This ensures that the AGV can continuously maintain the optimal path in a dynamic environment, improving inventory efficiency and safety.

[0097] S107: Use a fusion algorithm to avoid dynamic obstacles and unknown static obstacles.

[0098] Specifically, in dynamic environments, the system uses fusion algorithms to avoid both dynamic and unknown static obstacles, satisfying the requirements of globally optimal paths and dynamic obstacle avoidance in complex maps. The system employs fusion algorithms (such as multi-sensor fusion and deep learning) to identify and avoid dynamic obstacles (such as walking personnel and moving forklifts) and unknown static obstacles (such as temporarily stacked goods). This improves the AGV's adaptability in complex maps, ensuring the smooth execution of inventory tasks. Furthermore, by combining globally optimal paths and dynamic obstacle avoidance, it achieves efficient inventory management in dynamic environments.

[0099] In another embodiment, S105 specifically includes the following sub-steps:

[0100] S105.1: Obtain the actual warehouse item identifiers in real time.

[0101] Specifically, during the operation of the AGV, the inventory system uses cameras installed on the AGV to take real-time pictures of the appearance of the items in the warehouse, thereby obtaining the actual warehouse item identification in real time.

[0102] S105.2: Query the warehouse item type corresponding to the actual warehouse item identifier from the preset warehouse database.

[0103] Specifically, the inventory system identifies and categorizes the acquired item identifiers. The system determines the item type of the current item by querying the pre-set warehouse database to find the warehouse item type corresponding to the actual warehouse item identifier.

[0104] S105.3: Accumulate the number of warehouse items generated corresponding to the warehouse item type.

[0105] Specifically, the inventory system generates a cumulative quantity of warehouse items corresponding to their respective types based on the actual warehouse item identifiers. The system uses counters mounted on AGVs to count the items. The system categorizes different item identifiers according to item type and generates a cumulative quantity of warehouse items corresponding to each item type.

[0106] S105.4: Push the warehouse item type and the corresponding warehouse item quantity to the user's smart terminal.

[0107] Specifically, the inventory system will identify the types of warehouse items and the corresponding quantities of warehouse items to the user's smart terminal, thereby enabling the AGV to perform inventory checks and statistics on the items in the warehouse while moving, thus improving the inventory efficiency of the AGV.

[0108] Furthermore, prior to S105, as another implementation method, the present invention may further include the following steps:

[0109] S201: Define "virtual lanes" in the physical space to guide AGVs to travel along fixed paths.

[0110] Specifically, based on the inventory route map, the system uses physical markers (such as landmarks and lighting) or virtual technologies (such as AR / VR) within the warehouse to divide the physical space into "virtual lanes." These lanes clearly indicate the direction and path of the AGVs, ensuring that the AGVs can travel along fixed paths and reducing conflicts at intersections. By dividing the virtual lanes, the system effectively regulates the driving behavior of the AGVs, reduces the risk of collisions between AGVs, improves traffic efficiency within the warehouse, and ensures the smooth progress of inventory tasks.

[0111] S202: Install passage indicator devices at AGV intersections to control the right of way in different directions.

[0112] Specifically, based on the inventory path map, the system installs traffic guidance devices at AGV intersections to control the right-of-way in different directions and prevent AGV collisions. Traffic guidance devices, such as traffic lights or electronic displays, are also installed at intersections of AGV travel paths. These devices can control the right-of-way in different directions according to instructions from the central control system, preventing collisions between AGVs. The traffic guidance devices provide clear travel instructions for the AGVs, ensuring their safe passage at intersections. This improves traffic management within the warehouse and reduces traffic congestion caused by AGV intersections.

[0113] S203: Optimizes task allocation and travel routes for each AGV through a central control system and priority settings.

[0114] Specifically, the system employs a scheduling algorithm to optimize task allocation and travel routes for each AGV through a central control system and priority settings. The central control system uses advanced scheduling algorithms (such as genetic algorithms and particle swarm optimization) to allocate tasks to each AGV. Based on factors such as the AGV's current position, task priority, and path length, an optimal travel route is planned for each AGV. This scheduling algorithm ensures the rational allocation and efficient execution of AGV tasks, improving the overall inventory efficiency of the warehouse. By optimizing travel routes, it reduces AGV travel time and energy consumption, thereby lowering operating costs.

[0115] S204: Predict peak hours and congestion hotspots, and take measures in advance to disperse traffic flow.

[0116] Specifically, the system uses historical data analysis and machine learning models to predict peak periods and congestion points, and takes measures in advance to disperse traffic; through modeling and simulation tools, it simulates the operation of AGVs in different scenarios to identify and resolve potential problems in advance.

[0117] Historical inventory data is collected and analyzed, including AGV travel trajectories and task completion times. Machine learning models (such as neural networks and decision trees) are then used to predict peak hours and congestion hotspots. Through historical data analysis and machine learning models, accurate predictions of warehouse traffic conditions can be made, providing a basis for taking proactive measures to disperse traffic flow and reducing the risk of decreased inventory efficiency due to traffic congestion.

[0118] Modeling and simulation tools (such as MATLAB and Simulink) are used to simulate the operation of AGVs in the warehouse. By setting different parameters and scenarios, the AGV's trajectory, speed, collision situation, and other indicators can be observed. Modeling and simulation tools provide warehouse managers with intuitive visual feedback, which helps to identify and solve potential problems in advance. By simulating the operation of AGVs under different scenarios, path planning strategies can be optimized to improve warehouse inventory efficiency.

[0119] S205: Extract critical path points, eliminate redundant path points, reduce the total number of path turns, and shorten the global path length.

[0120] Specifically, the system analyzes obstacle types, extracts critical path points, eliminates redundant path points, reduces the total number of turns, and shortens the global path length. It performs a detailed analysis of obstacle types within the warehouse, including fixed obstacles (such as shelves and walls) and dynamic obstacles (such as personnel and forklifts). Based on the location and type of obstacles, it extracts critical path points that significantly impact AGV movement and eliminates redundant path points that have little or no impact on AGV operation. By analyzing obstacle types and extracting critical path points, the system simplifies the path planning process, reduces computational complexity, eliminates redundant path points, reduces the total number of turns and the global path length, and improves AGV operating efficiency.

[0121] S206: Use modeling software to create a digital twin of the warehouse interior, test different path planning strategies, and evaluate their effectiveness.

[0122] Specifically, the system uses modeling software to create a digital twin of the warehouse interior, tests different path planning strategies, and evaluates their effectiveness. Using modeling software (such as AutoCAD, SolidWorks, etc.), a digital twin of the warehouse interior is created. This digital twin should accurately reflect the physical layout of the warehouse, the location of obstacles, AGV travel paths, and other information. Different path planning strategies are tested on the digital twin, and their effectiveness is evaluated. The digital twin provides warehouse managers with a virtual testing platform, allowing them to test different path planning strategies without interfering with actual warehouse operations. By testing and evaluating on the digital twin, path planning strategies can be optimized, improving warehouse inventory efficiency and reducing operational risks caused by inappropriate strategies.

[0123] In multi-AGV warehousing and logistics systems, the shortest path may not necessarily lead to the shortest transportation time due to congestion or deadlock. Research has explored using mathematical modeling to introduce conflict-free or deadlock-free strategies to find the shortest path and address issues such as combined scheduling and vehicle quantity. This study uses temporal Petri nets to model the scheduling process of multi-AGV warehouses in a large-scale bidirectional lane environment. After decomposition, individual analysis of each AGV reduces the algorithm's time complexity. A traditional exterior point penalty function method is introduced to construct an objective function with AGV scheduling time as the indicator. By iteratively updating the AGV's running path information, the collision problem during scheduling is solved, and collision type analysis is added. Local path planning is performed based on the principle of optimizing the objective function, achieving optimal scheduling.

[0124] Furthermore, prior to S105.1, the actual warehouse item identification will be obtained based on the actual shelf spacing, specifically including the following steps:

[0125] S301: Real-time acquisition of AGV's travel position.

[0126] Specifically, during the movement of the AGV, the inventory system uses a locator installed inside the AGV to perform real-time positioning operations and determine the AGV's specific location within the warehouse.

[0127] S302: Determine the actual shelf position with the smallest distance from the AGV's travel position.

[0128] Specifically, the inventory system determines the actual shelf location with the smallest distance from the AGV's travel position based on the AGV's movement position. When the AGV moves within the warehouse, which contains multiple shelves at varying distances from the AGV, the inventory system uses cameras to identify the shelf closest to the AGV and retrieves its actual location from the database.

[0129] S303: Determine the actual shelf spacing.

[0130] Specifically, the inventory system determines the actual shelf spacing based on the AGV's travel position and the actual shelf position. The actual shelf spacing reflects the distance between the AGV and the nearest shelf.

[0131] S304: Query the preset shelf spacing corresponding to the actual shelf spacing from the preset warehouse database.

[0132] Specifically, the inventory system queries the preset shelf spacing corresponding to the actual shelf spacing from the preset warehouse database. The preset shelf spacing is generated in advance by the user and is used to represent the maximum distance between the shelf and the AGV when the AGV performs inventory operations on the shelf.

[0133] S305: If the actual shelf spacing is less than the preset shelf spacing, then proceed with the step of obtaining the actual warehouse item identification.

[0134] Specifically, the inventory system monitors in real time whether the AGV is moving close to the shelf that needs to be inventoried. When the AGV moves close to the shelf that needs to be inventoried, the inventory system begins to acquire the actual warehouse item identification. When the AGV has not yet moved close to the shelf that needs to be inventoried, the inventory system does not acquire the actual warehouse item identification, so that the AGV will not acquire the identification of all the items on the shelves it passes during the movement, thereby reducing the data redundancy of the inventory system.

[0135] Furthermore, following S305, as one implementation method, the present invention may further include:

[0136] S306: Obtain the location of the actual warehouse item corresponding to the actual warehouse item identifier.

[0137] Specifically, the inventory system obtains the location of the actual warehouse items based on their identification labels. Once the system obtains the labels on the shelves, it uses a camera and a location transmitter positioned directly beneath the item to determine its location.

[0138] S307: Generate actual object spacing.

[0139] Specifically, the inventory system generates the actual item spacing based on the actual warehouse item location and AGV travel position. The actual item spacing reflects the actual distance between the AGV and the actual item corresponding to the current identifier.

[0140] S308: If the actual distance between items is greater than the preset shelf distance, generate and execute the label deletion command.

[0141] The label deletion command is used to delete the label of an actual warehouse item. When the inventory system follows the movement of the AGV and performs label acquisition operations on the items on the current shelf, the system may misidentify items on other shelves that are close together. In this case, the inventory system determines whether the item is located on the shelf to be scanned by judging the actual distance between the AGV and the item. If the actual distance between the item and the shelf is greater than the preset shelf distance, it means that the item is not located on the shelf to be scanned. At this time, the inventory system generates a label deletion command to delete the actual warehouse item label corresponding to the current item, so that the inventory system can systematically identify and count the items on each shelf during the inventory process.

[0142] Furthermore, following S302, an inventory check work order will be generated based on the pre-stored shelf item identification, specifically including the following steps:

[0143] S401: Retrieve the pre-stored shelf item identifier corresponding to the actual shelf location from the preset warehouse database.

[0144] Specifically, when the inventory system performs corresponding inventory operations on the shelves, the system queries the pre-stored shelf item identifiers corresponding to the actual shelf locations from the preset storage database, and obtains the pre-stored shelf item identifiers corresponding to the current shelf in the database. The pre-stored shelf item identifiers are the theoretical identifiers of the items that should be stored on the current shelf.

[0145] S402: If the actual warehouse item label is inconsistent with the pre-stored shelf item label, then the inconsistent item label shall be determined.

[0146] Specifically, during the inventory counting process on a shelf, the system compares the actual warehouse item labels on the shelf with the pre-stored shelf item labels in the database to determine whether the current storage status of the items on the shelf is accurate. If there is a discrepancy between the actual warehouse item labels and the pre-stored shelf item labels, it indicates that there is an error in the placement of the items on the shelf, and the inventory system identifies the inconsistent item labels.

[0147] S403: Generate inventory work order.

[0148] Specifically, the inventory system generates an inventory work order based on the inconsistent item identifiers. When the inventory system detects inconsistent item identifiers on the current shelf, it reflects the detected inconsistent item identifiers through the inventory work order. For example, when the inventory system finds an item with an inconsistent item identifier of 001 on the current shelf, the inventory system displays "1 item 001" through the inventory work order.

[0149] S404: Push inventory work orders to the user's smart terminal.

[0150] Specifically, the inventory system generates and outputs an inventory work order, which is then pushed to the user's smart terminal, allowing the user to know the specific errors in the placement of items in the warehouse.

[0151] Reference Figure 2 Before S402, a stocktaking work order will be supplemented based on the shelf identification, which includes the following steps:

[0152] S501: Retrieve the correct shelf label corresponding to the inconsistent item label from the pre-set warehouse database.

[0153] The correct shelf identifier is generated in advance by the user. It is used to indicate the correct shelf where the inconsistent item should be placed, so as to facilitate the inventory system to determine the subsequent handling plan for the item.

[0154] S502: Determine whether the correct shelf label exists.

[0155] If the determination is yes, then execute S503 to S506;

[0156] If the determination is negative, then execute steps S507 to S508.

[0157] S503: Invoke the erroneous shelf label corresponding to the inconsistent item label.

[0158] Specifically, if the corresponding correct shelf identifier exists, the incorrect shelf identifier corresponding to the inconsistent item identifier is called. The incorrect shelf identifier is the actual shelf identifier where the current inconsistent item identifier is located.

[0159] S504: Determine whether the erroneous shelf label exists.

[0160] If the determination is yes, then proceed to S505;

[0161] If the result is negative, proceed to step S506.

[0162] S505: Generate and execute the item misplacement command.

[0163] Specifically, if a corresponding incorrect shelf label exists, a misplacement instruction is generated and executed. This instruction updates the correct and incorrect shelf labels corresponding to the inconsistent item labels in the inventory work order. When the inventory system detects incorrect item placement, it identifies the type of error. If the item should not be placed on the current shelf but on another shelf within the warehouse, then the item has a misplacement. The system generates a misplacement instruction, integrating the correct and incorrect shelf labels corresponding to the inconsistent item labels and adding them to the inventory work order.

[0164] S506: Generate and execute the command to reduce the number of items.

[0165] Specifically, if the corresponding incorrect shelf identifier does not exist, an "item under-placement" instruction is generated and executed. The "item over-placement" instruction updates the record of the correct shelf identifier corresponding to the inconsistent item identifier in the inventory work order. If the inconsistent item identifier only has a corresponding correct shelf identifier but no corresponding incorrect shelf identifier, it means that the warehouse does not have the corresponding item that needs to be placed on the current correct shelf identifier. This indicates that the warehouse is missing the item corresponding to the current item identifier. In this case, the inventory system generates an "item under-placement" instruction, adding the correct shelf identifier corresponding to the current inconsistent item identifier to the inventory work order, allowing users to see the specific error type of the incorrectly placed item by browsing the inventory work order.

[0166] S507: Perform the step of calling the erroneous shelf label corresponding to the inconsistent item label.

[0167] Specifically, if the corresponding correct shelf label does not exist, the step of calling the incorrect shelf label corresponding to the inconsistent item label is executed. When the inventory system cannot detect the correct shelf label corresponding to the current inconsistent item label, it means that the current item does not belong to this warehouse. Since the item label is not in the correct placement state at this time, the incorrect shelf label must exist, and the inventory system directly calls the incorrect shelf label corresponding to the inconsistent item label.

[0168] S508: Generate and execute the instruction to place multiple items.

[0169] Specifically, the inventory system generates and executes an "item over-placement" instruction based on the inconsistent item identifier and the corresponding incorrect shelf identifier. This instruction updates the incorrect shelf identifier corresponding to the inconsistent item identifier in the inventory work order. When the inventory system can only retrieve the incorrect shelf identifier for the current item but not the correct one, it indicates that an item on a shelf in the warehouse should not be stored there; the item is redundant. In this case, the system generates an "item over-placement" instruction, adding the incorrect shelf identifier to the inventory work order so the user can retrieve the product from the warehouse later.

[0170] Furthermore, prior to S105, an AGV activation command will be generated based on the warehouse partition information, specifically including the following steps:

[0171] S601: Query the warehouse partition information corresponding to the warehouse aisle data from the preset warehouse database.

[0172] The warehouse zoning information includes the warehouse's divided areas and the corresponding warehouse area locations. The inventory system queries and retrieves relevant information for each storage area within the warehouse.

[0173] S602: Generate multiple disk partitioning areas.

[0174] Specifically, the inventory system generates multiple inventory partitioning areas based on warehouse zoning information, and each inventory partitioning area includes multiple warehouse partitioning areas. The inventory system divides the entire warehouse into multiple distinct inventory partitioning areas based on the warehouse zoning information.

[0175] S603: Generate the partition number corresponding to the partition area of ​​the inventory.

[0176] Specifically, the inventory system generates corresponding zone numbers based on the warehouse's zoning areas. After dividing the entire warehouse into multiple distinct inventory zones, the system then sorts and numbers each of these zones.

[0177] S604: Generate and execute the AGV enable command.

[0178] Specifically, the inventory system generates and executes AGV activation commands based on the number of inventory areas. The AGV activation commands are used to start the corresponding number of AGVs according to the number of inventory areas. The inventory system simultaneously activates the AGVs corresponding to the number of inventory areas.

[0179] S605: Query the activated AGV serial number from the preset warehouse database.

[0180] Specifically, each AGV has a corresponding number stored in the database. The inventory system retrieves the activated AGV serial number from the preset warehouse database.

[0181] S606: Generate and execute interval allocation instructions.

[0182] Specifically, the inventory system generates and executes interval allocation instructions based on the partition area number and the activated AGV number. These interval allocation instructions correspond to the partition area number and the activated AGV number. The inventory system generates interval allocation instructions according to the order of the partition area number and the activated AGV number, ensuring that each AGV corresponds to a partition area in the inventory system.

[0183] S607: Generate the inventory travel path corresponding to the AGV serial number that is enabled.

[0184] Specifically, the inventory system generates inventory movement paths corresponding to the activated AGV serial numbers based on the inventory division areas and warehouse aisle data. The inventory system plans inventory movement paths within each inventory division area, and designs a customized inventory movement path for each AGV.

[0185] S608: Execute the command to generate the disk and the steps to be performed.

[0186] Specifically, the inventory system executes steps to generate and execute inventory instructions based on the inventory movement path, so that each inventory instruction corresponds to an inventory movement path in a different inventory division area.

[0187] S609: Push inventory control instructions to the corresponding AGVs respectively.

[0188] Specifically, the inventory system pushes inventory instructions to the corresponding AGVs based on their activation AGV serial numbers. The system also pushes inventory movement paths to the corresponding AGVs based on the correspondence between zone numbers and activated AGV serial numbers, enabling multiple AGVs to move simultaneously to conduct inventory checks on warehouse items, thus improving AGV inventory efficiency.

[0189] The implementation principle of a scheduling and control method for warehouse AGVs according to an embodiment of the present invention is as follows: During the AGV's movement, the inventory system acquires the actual warehouse item identification in real time, identifies and classifies the acquired item identification, and pushes the identified warehouse item types and the corresponding warehouse item quantities to the user's smart terminal. At the same time, based on the incorrect placement of items, an inventory work order is generated and pushed to the user's smart terminal, thereby enabling the AGV to check and count the items in the warehouse during its movement, improving the inventory efficiency of the AGV.

[0190] Based on the above method, this invention also discloses a scheduling and control system for warehouse AGVs. A scheduling and control system for warehouse AGVs includes:

[0191] The inventory request receiving module is used to receive inventory requests sent by users, the inventory requests carrying inventory information for controlling AGVs to conduct inventory checks on warehouse items;

[0192] The walkway data query module is used to query warehouse walkway data from a preset warehouse database and retrieve Algorithm A.

[0193] The path planning module is used to optimize the A algorithm based on the warehouse aisle data and use the optimized A algorithm for global path planning.

[0194] The inventory path map generation module is used to perform local path adjustments and obstacle avoidance on the global path planning using a dynamic window method, and generate an inventory path map.

[0195] The inventory check instruction generation module is used to generate and execute inventory check instructions based on the inventory check path diagram.

[0196] The local path planning module is used to acquire monitoring environment change data, build a real-time environment map, update the global path in real time, and replan the local path.

[0197] The obstacle avoidance module is used to avoid dynamic obstacles and unknown static obstacles in dynamic environments using a fusion algorithm, and to meet the requirements of global optimal path and dynamic obstacle avoidance in complex maps.

[0198] This invention also discloses an intelligent terminal, which includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described above for a scheduling and control method for warehouse AGVs.

[0199] This invention also discloses a computer-readable storage medium. The computer-readable storage medium stores a computer program that can be loaded by a processor and executed as described above for a scheduling and control method for warehouse AGVs. The computer-readable storage medium includes, for example, various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0200] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on these embodiments, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still combine, add, delete, or otherwise adjust the features of the various embodiments of the present invention according to the circumstances without conflict or creative effort, thereby obtaining different technical solutions that do not fundamentally depart from the concept of the present invention. These technical solutions also fall within the scope of protection of the present invention.

Claims

1. A scheduling and control method for warehouse AGVs, characterized in that, Includes the following steps: Receive inventory check requests sent by users, the inventory check requests carrying inventory check information for controlling AGVs to conduct inventory checks on warehouse items; Query warehouse aisle data from the pre-set warehouse database and retrieve Algorithm A; Based on the warehouse aisle data, the A algorithm is optimized, and the optimized A algorithm is used for global path planning; The dynamic window method is used to perform local path adjustments and obstacle avoidance on the global path planning, generating a database path map; Based on the inventory path diagram, "virtual lanes" are divided in the physical space to guide the AGV to travel along a fixed path, reducing the possibility of conflicts at intersections; According to the inventory path diagram, a passage indicator device is installed at the intersection of AGVs to control the right of way in different directions and avoid AGV collisions. A scheduling algorithm is used to optimize the task allocation and travel route of each AGV through a central control system and priority settings; By using historical data analysis and machine learning models, we can predict peak periods and congestion points, and take measures in advance to disperse traffic. By using modeling and simulation tools, we can simulate the operation of AGVs in different scenarios and identify and resolve potential problems in advance. By analyzing obstacle types, key path points are extracted, redundant path points are eliminated, the total number of path turns is reduced, and the global path length is shortened. We used modeling software to create a digital twin of the warehouse interior, tested different path planning strategies, and evaluated their effectiveness. The warehouse partition information corresponding to the warehouse aisle data is retrieved from the preset warehouse database. The warehouse partition information includes the warehouse division area and the warehouse area location corresponding to the warehouse division area. Based on the warehouse partitioning information, multiple inventory partitioning areas are generated, and each inventory partitioning area includes multiple warehouse partitioning areas. Based on the inventory division areas, generate division area numbers corresponding to the inventory division areas; Based on the number of areas to be divided in the inventory, an AGV activation command is generated and executed. The AGV activation command is used to start the corresponding number of AGVs according to the number of areas to be divided in the inventory. Query the activated AGV serial number from the preset warehouse database; Based on the partitioned area number and the activated AGV number, a zone allocation instruction is generated and executed, wherein the zone allocation instruction corresponds to the partitioned area number and the activated AGV number. Based on the inventory division area and the warehouse aisle data, an inventory travel path corresponding to the activated AGV sequence number is generated; Based on the inventory movement path, execute the steps of generating inventory instructions and performing them; Based on the activated AGV sequence number, the inventory control command is pushed to the corresponding AGV. Based on the inventory path diagram, generate and execute inventory instructions; Acquire data on changes in the monitoring environment, build a real-time environmental map, and update the global path and replan the local path in real time; In dynamic environments, fusion algorithms are used to avoid dynamic obstacles and unknown static obstacles, satisfying the requirements of global optimal path and dynamic obstacle avoidance in complex maps.

2. The scheduling and control method for warehouse AGVs according to claim 1, characterized in that, The steps of generating and executing disk access instructions specifically include: Real-time acquisition of actual warehouse item identification; Retrieve the warehouse item type corresponding to the actual warehouse item identifier from the preset warehouse database; Based on the actual warehouse item identifier, the cumulative quantity of warehouse items corresponding to the warehouse item type is generated. The type of warehouse item and the quantity of warehouse items corresponding to the type of warehouse item are pushed to the user's smart terminal.

3. The scheduling and control method for warehouse AGVs according to claim 2, characterized in that, Prior to the step of obtaining the actual warehouse item identification, the following is also included: Real-time acquisition of AGV's position; Based on the AGV's travel position, determine the actual shelf position with the smallest distance from the AGV's travel position; The actual shelf spacing is determined based on the AGV's travel position and the actual shelf position. Query the preset shelf spacing corresponding to the actual shelf spacing from the preset warehouse database; If the actual shelf spacing is less than the preset shelf spacing, then the step of obtaining the actual warehouse item identification is performed.

4. The scheduling and control method for warehouse AGVs according to claim 3, characterized in that, Following the step of obtaining the actual warehouse item identification, the following is also included: Based on the actual warehouse item identifier, obtain the location of the actual warehouse item corresponding to the actual warehouse item identifier; The actual item spacing is generated based on the actual warehouse item location and the AGV travel position; If the actual item spacing is greater than the preset shelf spacing, a label deletion instruction is generated and executed. The label deletion instruction is used to delete the label of the actual warehouse item.

5. A scheduling and control method for warehouse AGVs according to claim 3, characterized in that, After the step of determining the actual shelf position with the smallest distance from the AGV's travel position, the method further includes: Retrieve the pre-stored shelf item identifier corresponding to the actual shelf location from the preset warehouse database; If the actual warehouse item identification does not match the pre-stored shelf item identification, then the inconsistent item identification is determined; Based on the inconsistent item identifiers, an inventory check order is generated; The inventory work order is pushed to the user's smart terminal.

6. The scheduling and control method for warehouse AGVs according to claim 5, characterized in that, Following the step of determining the inconsistent item identifier, the method further includes: Retrieve the correct shelf label corresponding to the inconsistent item label from the preset warehouse database; If the corresponding correct shelf identifier exists, then the incorrect shelf identifier corresponding to the inconsistent item identifier is invoked; If the corresponding incorrect shelf identifier exists, an item misplacement instruction is generated and executed. The item misplacement instruction is used to update the record of the correct shelf identifier and the incorrect shelf identifier corresponding to the inconsistent item identifier to the inventory work order. If the corresponding incorrect shelf identifier does not exist, an item shortage instruction is generated and executed. The item shortage instruction is used to update the record of the correct shelf identifier corresponding to the inconsistent item identifier to the inventory work order.

7. A scheduling and control system for warehouse AGVs, characterized in that, include: The inventory request receiving module is used to receive inventory requests sent by users, the inventory requests carrying inventory information for controlling AGVs to conduct inventory checks on warehouse items; The walkway data query module is used to query warehouse walkway data from a preset warehouse database and retrieve Algorithm A. The path planning module is used to optimize the A algorithm based on the warehouse aisle data and use the optimized A algorithm for global path planning. The inventory path map generation module is used to perform local path adjustments and obstacle avoidance on the global path planning using a dynamic window method, and generate an inventory path map. The inventory check instruction generation module is used to generate and execute inventory check instructions based on the inventory check path diagram. The local path planning module is used to acquire monitoring environment change data, build a real-time environment map, update the global path in real time, and replan the local path. The obstacle avoidance module is used to avoid dynamic obstacles and unknown static obstacles in dynamic environments using a fusion algorithm, and to meet the requirements of global optimal path and dynamic obstacle avoidance in complex maps.

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