AGV task allocation and management method based on block chain

Abstract

The invention discloses an AGV task allocation and management method based on a block chain. The method comprises the following steps: (1) constructing a hardware layer; (2) configuring a software layer; (3) the warehouse management server node generates an AGV task containing task information based on the high SKU order demand, encrypts the task information and uploads the task information to the block chain network node, and the block chain network node writes the task information into a task state account book; (4) the AGV node collects state data of the AGV node in real time and uploads the state data to the block chain network node; the improved PoS consensus module calculates a right weight value of each AGV node, submits a competition proposal, and determines an optimal AGV node; (5) the intelligent contract execution module presets an intelligent contract rule and judges whether the SKU attribute in the task information relates to a sensitive SKU field; (6) the optimal AGV node receives an instruction, plans a path in combination with a real-time storage map and executes a task; and (7) the multi-agent collaboration module triggers data filtering, then starts a data sharing mechanism, synchronizes information to different nodes and allocates corresponding permissions.

Description

Technical Field

[0001] The present invention relates to the fields of warehousing logistics and blockchain technology, and in particular to an AGV task allocation and management method based on blockchain. Background Art

[0002] Traditional AGV task allocation solutions currently available on the market mostly utilize centralized control systems. A master computer is responsible for assigning tasks, planning routes, and resolving conflicts for all AGVs. Lower computers then execute tasks according to the master-planned routes using classic path planning algorithms (such as A-star and Dijkstra). This architecture places a heavy burden on the master computer for computation and coordination, placing extremely high demands on its computing performance. A failure in the master computer can lead to traffic congestion and system crashes for the entire system. Furthermore, while classic path planning algorithms like A-star and Dijkstra perform well for single-AGV path planning, when multiple AGVs are operating simultaneously, conflicts and deadlocks can occur if each AGV's picking path is planned solely according to a single-vehicle path planning algorithm without considering the interactions between multiple AGVs.

[0003] In high-SKU warehousing scenarios, the sheer number of tasks and AGVs magnifies the drawbacks of centralized architectures, leading to low scheduling efficiency and slow dynamic response. Furthermore, given the frequent changes in shelf locations, path planning algorithms that don't consider inter-AGV interactions cannot meet dynamic response requirements. Furthermore, traditional solutions lack trust among participating entities, making efficient multi-agent collaboration difficult in high-SKU warehousing, which involves multiple parties collaborating. Information opacity and low trust among stakeholders can hinder overall warehouse operational efficiency.

[0004] Therefore, traditional AGV task allocation solutions have problems such as reliance on centralized architecture, low efficiency of traditional algorithms, and insufficient application of blockchain. These problems lead to low scheduling efficiency, slow dynamic response, poor data consistency, low resource utilization, and difficulty in multi-agent collaboration in high-SKU warehousing, making it difficult to meet the intelligent warehousing needs of massive SKUs. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an AGV task allocation and management method based on blockchain. This AGV task allocation and management method based on blockchain can improve scheduling efficiency, dynamic response, data consistency and resource utilization in high SKU warehousing, coordinate multiple subjects, and meet the intelligent warehousing needs of massive SKUs.

[0006] In order to solve the above technical problems, the technical solutions adopted by the present invention are as follows: A blockchain-based AGV task allocation and management method, characterized by comprising the following steps: (1) Hardware layer construction: The hardware layer includes blockchain network nodes, AGV nodes, warehouse management server nodes, cargo owner authority nodes and 5G communication modules; (2) Software layer configuration: The software layer includes an improved PoS consensus module, an AGV status real-time collection and transmission module, a smart contract execution module, a multi-agent collaboration module, a SKU dimension permission control module, and a multi-agent data interaction and permission management module; The AGV status real-time collection and transmission module and the improved PoS consensus module are all set in the AGV node; the smart contract execution module, multi-agent collaboration module, SKU dimension permission control module, and multi-agent data interaction and permission management module are all set in the blockchain network node; (3) Based on the high SKU order demand, the warehouse management server node generates an AGV task containing task information, encrypts the task information and uploads it to the blockchain network node, which then writes it into the task status ledger; (4) The AGV node collects its own status data in real time through the AGV status real-time collection and transmission module, and uses the 5G communication module to upload the status data of the AGV node to the blockchain network node; Improve the PoS consensus module to calculate the equity weight of each AGV node based on task information and status data, submit competing proposals, and determine the optimal AGV node through a weighted voting mechanism; (5) The smart contract execution module presets the smart contract rules and determines whether the SKU attributes in the task information involve sensitive SKU fields: (5-1) If the SKU attribute involves sensitive SKU fields, the smart contract execution module sends a task instruction to the optimal AGV node and proceeds to step (6), and at the same time sends a permission control request to the multi-agent collaboration module and proceeds to step (7); (5-2) If the SKU attribute does not involve sensitive SKU fields, the smart contract execution module sends a task instruction to the optimal AGV node and proceeds to step (6); (6) The smart contract execution module automatically assigns tasks and updates the task status ledger; the optimal AGV node receives the instruction, plans the path based on the real-time warehouse map, executes the task, and reports the progress to the blockchain network node; after the task is completed, it is verified by the smart contract and stored on the chain, and then returns to step (5); (7) The multi-agent collaboration module triggers the SKU dimension permission control module to filter data, and then starts the data sharing mechanism through the multi-agent data interaction and permission management module to synchronize information to the warehouse management server node and the cargo owner permission node and assign corresponding permissions.

[0007] In the above step (1), the blockchain network node serves as the basis for data interaction and storage; the AGV node is used to collect its own status data and participate in task competition; the warehouse management server node is used to generate task information and upload it to the chain; and the cargo owner authority node is used to achieve secure access to data.

[0008] In the above step (2), the PoS consensus module is improved, and the equity weight of each AGV node is calculated based on the status data and task information uploaded by the AGV node and a competition proposal is submitted; the smart contract execution module presets smart contract rules and automatically executes task allocation operations, authority control operations and data notarization operations; the AGV status real-time collection and transmission module continuously provides dynamic data support for improving the PoS consensus module and task execution; the multi-agent collaboration module receives the authority control request of the smart contract execution module and implements field-level data filtering through the SKU dimension authority control module; the SKU dimension authority control module dynamically authorizes according to the preset smart contract rules and sends security data to the multi-agent data interaction and authority management module; the multi-agent data interaction and authority management module ensures the trusted sharing of data between nodes, and assigns corresponding permissions to different subjects according to the preset smart contract rules, realizes the collaborative operation of each part, and completes the efficient management of AGV tasks in high SKU scenarios.

[0009] In the above steps (1)-(4), the blockchain distributed architecture is applied to the AGV task allocation of high SKU warehousing. The decentralized task allocation is achieved through the improved PoS consensus mechanism that integrates AGV status and SKU attributes. The system has strong fault tolerance and can fairly and efficiently select the optimal AGV node among multiple AGVs, creating a new idea for AGV scheduling in high SKU warehousing.

[0010] The instantaneous uploading of task information in step (3) and the high-frequency uploading of task progress in step (6) constitute an innovative two-layer real-time data uploading method. This method encrypts and protects data during transmission and storage, ensuring the real-time and integrity of the data. This not only ensures the timeliness of task release, but also enables real-time monitoring of the AGV execution process. This design ensures a trusted closed loop between dynamic data and task execution, significantly improving the efficiency and response speed of dynamic task processing.

[0011] In step (5), when sensitive SKU fields are involved, issuing task instructions to the optimal AGV node and sending permission control requests to the multi-agent collaboration module are executed in parallel. The sensitive SKU fields mentioned above are generally "temperature control required", "drug information", and "sensitive data".

[0012] In the above step (6), the smart contract execution module automatically assigns tasks and generates task instructions to the optimal AGV node, and simultaneously updates the task status ledger of the blockchain network node. In the above step (6), a dynamic task optimization algorithm and path planning strategy adapted to the high SKU characteristics are proposed to achieve adaptive management of warehouse layout adjustment and SKU attribute changes, highly adapt to the dynamic changes of high SKU scenarios, and achieve high resource utilization.

[0013] In step (7) above, a fine-grained permission control system based on the SKU dimension is constructed based on smart contracts. Differentiated data access rights are assigned to different entities through smart contract rules, effectively solving the privacy protection problem in multi-agent collaboration and ensuring the trusted sharing and privacy security of multi-agent data. Typically, the authorization of specific fields can be "opening the drug expiration date to the shipper" or "hiding the path details from the warehouse management server node".

[0014] In the preferred embodiment, in step (3), the task information includes the task quantity and SKU attributes; wherein the SKU attributes include priority; in step (4), the AGV node collects its own status data including current position, target position, power, and load in real time.

[0015] In a further preferred embodiment, in step (4), the equity weight value is calculated using a preset equity weight calculation formula, and the weighted voting mechanism allocates voting weights based on the equity weight value of each AGV node, and the AGV node with the highest number of votes is determined as the optimal AGV node. The improved PoS consensus module calculates the equity weight value of each AGV node according to the task information and status data using the preset equity weight calculation formula, and uses the calculated equity weight value as a proposal to compete for the task, and submits the competing proposal to the smart contract execution module.

[0016] In a further preferred solution, the equity weight calculation formula is: Equity weight W = α × E + β × (1 / D) + γ × (1 / L) + δ × P, where: E: battery percentage (0≤E≤1); D: distance between AGV and target location; L: current task number + 1; P: SKU priority coefficient; α, β, γ, δ: adjustable weight parameters.

[0017] Typically, α is the power weight parameter, β is the distance weight parameter, γ is the task number weight parameter, and δ is the SKU priority weight parameter.

[0018] In the preferred embodiment, in step (6), the optimal AGV node uses a genetic algorithm to plan the optimal path and uses a high-frequency progress reporting mechanism to upload the task progress to the blockchain network node. The optimal AGV node receives the task instruction, combines the real-time warehouse map stored by the blockchain network node, uses the genetic algorithm to plan the optimal path and execute the task, and uses a high-frequency progress reporting mechanism to upload the task progress to the blockchain network node.

[0019] In a further preferred solution, in step (6), the real-time status data of the optimal AGV node drives the smart contract execution module to execute the task; after the task is completed, the AGV node submits the task result, and after verification by the smart contract execution module, the task completion information is uploaded to the chain for evidence, and the execution jumps back to step (5).

[0020] In a further preferred embodiment, in step (6), the high-frequency progress reporting mechanism is to upload the task progress to the blockchain network node every 400ms-600ms.

[0021] In a further preferred solution, in step (6), the high-frequency progress reporting mechanism is to upload the task progress to the blockchain network node every 500ms.

[0022] In the preferred solution, in step (7), the multi-agent collaboration module receives the permission control request from the smart contract execution module, triggering the SKU dimension permission control module to perform data filtering; after data filtering, the multi-agent data interaction and permission management module is triggered to start the multi-agent data sharing mechanism, synchronize the task trajectory and status to the warehouse management server node and the cargo owner permission node, assign corresponding permissions to the warehouse management server node and the cargo owner permission node, and according to the preset rules of the smart contract, only authorized specific fields are opened to the cargo owner permission node.

[0023] Compared with the prior art, the present invention has the following advantages: The present invention builds a decentralized, adaptive, and trustworthy management system for AGV task allocation in high SKU scenarios through the deep integration of blockchain distributed architecture, improved PoS consensus mechanism, real-time data on-chain technology, smart contract collaboration, and dynamic task optimization algorithm. It realizes distributed and efficient decision-making in high SKU scenarios, ensures real-time data processing of task allocation, balances multi-agent data privacy and collaborative sharing, improves the system's adaptability to dynamic SKU changes, and enhances fault tolerance in abnormal scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a diagram showing the connection relationship between each node and each module in a specific embodiment 1 of the present invention; Figure 2 Schematic diagram of the steps of the AGV task allocation and management method in the specific embodiment 1 of the present invention; Figure 3 This is a processing flow chart of the smart contract execution module in specific embodiment 1 of the present invention; Figure 4 This is a flowchart of a method for real-time uploading of double-layer data to a chain in accordance with a specific embodiment 1 of the present invention; Figure 5 This is a flowchart of calculating the equity weight of each AGV node in specific embodiment 2 of the present invention. DETAILED DESCRIPTION

[0025] The following is a further description of the preferred embodiments of the present invention in conjunction with the accompanying drawings.

[0026] Example 1, as Figure 1-4 The blockchain-based AGV task allocation and management method of this embodiment includes the following steps: (1) Hardware layer construction: The hardware layer includes blockchain network nodes, AGV nodes, warehouse management server nodes, cargo owner authority nodes and 5G communication modules; (2) Software layer configuration: The software layer includes an improved PoS consensus module, an AGV status real-time collection and transmission module, a smart contract execution module, a multi-agent collaboration module, a SKU dimension permission control module, and a multi-agent data interaction and permission management module; The AGV status real-time collection and transmission module and the improved PoS consensus module are all set in the AGV node; the smart contract execution module, multi-agent collaboration module, SKU dimension permission control module, and multi-agent data interaction and permission management module are all set in the blockchain network node; (3) Based on the high SKU order demand, the warehouse management server node generates an AGV task containing task information, encrypts the task information and uploads it to the blockchain network node, which then writes it into the task status ledger; (4) The AGV node collects its own status data in real time through the AGV status real-time collection and transmission module, and uses the 5G communication module to upload the status data of the AGV node to the blockchain network node; Improve the PoS consensus module to calculate the equity weight of each AGV node based on task information and status data, submit competing proposals, and determine the optimal AGV node through a weighted voting mechanism; (5) The smart contract execution module presets the smart contract rules and determines whether the SKU attributes in the task information involve sensitive SKU fields: (5-1) If the SKU attribute involves sensitive SKU fields, the smart contract execution module sends a task instruction to the optimal AGV node and proceeds to step (6), and at the same time sends a permission control request to the multi-agent collaboration module and proceeds to step (7); (5-2) If the SKU attribute does not involve sensitive SKU fields, the smart contract execution module sends a task instruction to the optimal AGV node and proceeds to step (6); (6) The smart contract execution module automatically assigns tasks and updates the task status ledger; the optimal AGV node receives the instruction, plans the path based on the real-time warehouse map, executes the task, and reports the progress to the blockchain network node; after the task is completed, it is verified by the smart contract and stored on the chain, and then returns to step (5); (7) The multi-agent collaboration module triggers the SKU dimension permission control module to filter data, and then starts the data sharing mechanism through the multi-agent data interaction and permission management module to synchronize information to the warehouse management server node and the cargo owner permission node and assign corresponding permissions.

[0027] In step (3), the task information includes the task quantity and SKU attributes; wherein the SKU attributes include priority; in step (4), the AGV node collects its own status data including current position, target position, power, and load in real time.

[0028] In step (4), the equity weight value is calculated using a preset equity weight calculation formula. The weighted voting mechanism allocates voting weights based on the equity weight value of each AGV node, and the AGV node with the highest number of votes is determined as the optimal AGV node. The improved PoS consensus module calculates the equity weight value of each AGV node based on the task information and status data according to the preset equity weight calculation formula, and uses the calculated equity weight value as a proposal to compete for the task, and submits the competition proposal to the smart contract execution module.

[0029] In step (6), the optimal AGV node uses a genetic algorithm to plan the optimal path and uses a high-frequency progress reporting mechanism to upload the task progress to the blockchain network node. The optimal AGV node receives the task instruction, combines the real-time warehouse map stored by the blockchain network node, uses the genetic algorithm to plan the optimal path and execute the task, and uses a high-frequency progress reporting mechanism to upload the task progress to the blockchain network node.

[0030] In step (6), the real-time status data of the optimal AGV node drives the smart contract execution module to execute the task; after the task is completed, the AGV node submits the task result, and after verification by the smart contract execution module, the task completion information is stored on the chain and jumps back to step (5).

[0031] In step (6), the high-frequency progress reporting mechanism is to upload the task progress to the blockchain network node every 500ms.

[0032] In this embodiment Figure 3The core logic of how the smart contract execution module handles task allocation, status verification, and data access permission control based on preset smart contract rules and specific SKUIDs is demonstrated.

[0033] In this embodiment Figure 4 The two-layer real-time data chain-up process is intuitively presented, including task information generation and chain-up, periodic reporting of AGV status, and high-frequency (500ms) progress chain-up during task execution.

[0034] The following specifically uses the pharmaceutical warehousing scenario (high SKU, high timeliness requirements) as an example to implement this blockchain-based AGV task allocation and management method, which includes the following steps: (1) Hardware layer construction and (2) Software layer configuration

[0035] A. Blockchain network node construction: a. Use Hyperledger Fabric 2.3 to build blockchain network nodes, including three types of nodes: -AGV node (including 5G communication module); -Warehouse management server node (running task generation and map management services); - Shipowner authority node (a private node for pharmaceutical companies, used for SKU data authorization); b. Network channel settings: Create task-channel (task assignment) and data-channel (real-time data sharing) to achieve data isolation; B. Use the following core contract code (chain code) to deploy smart contracts: Func AssignTask(ctx ContractContext,taskID string) error { / / Verify task validity (SKU attributes) task:=GetTaskFromLedger(ctx,taskID) / / Call the improved PoS consensus module to calculate the equity weight of the AGV node validAGVs:=CalculateAGVWeight(task.SKU.Priority,task.TargetLocation) / / Select the best AGV node through weighted voting mechanism (the one with the highest weight wins the bid) selectedAGV:=SelectAGVByVote(validAGVs) / / The smart contract execution module generates task instructions and updates the task status ledger UpdateTaskLedger(ctx,taskID,"ASSIGNED",selectedAGV) return nil }

[0036] Step (3) Task generation and chaining (warehouse management server node execution) -When a pharmaceutical order arrives, the warehouse management server node parses the SKU attributes (such as the expiration date of the drug and temperature control requirements) and generates a task structure: { "TaskID":"T20250620001", "SKU_Properties":{"ID":"MED_001","Priority":"High","ExpiryDate":"2025-12-31"}, "TargetLocation":"Aisle3-Shelf5", "Deadline":"2025-06-20T14:30:00Z" } Use AES-256 to encrypt task data and call the blockchain SDK through the gRPC interface to write it into the task-channel ledger.

[0037] Step (4) AGV status reporting and competition proposal (AGV node execution) -AGV periodically (every 1 second) collects and encrypts status data and uploads it to the data-channel: { "AGV_ID":"AGV007", "Battery": 85, / / Unit: % "Location":[23.5,45.2], / / 2D coordinates "CurrentLoad":3 / / Current number of tasks } By improving the PoS consensus module, the equity weight of each AGV node is calculated according to the equity weight calculation formula W=α×E+β×(1 / D)+γ×(1 / L)+δ×P.

[0038] Consensus (automatically executed by blockchain network nodes) - Improve the PoS consensus module to collect AGV competition proposals in the task-channel, calculate the weights and sort them according to the above formula; Step (5) Task allocation (automatic execution by blockchain network nodes) -The smart contract AssignTask is automatically triggered and sends instructions to the optimal AGV node (such as AGV007). The task status ledger is updated as follows: TaskID:T20250620001→Status:ASSIGNED→Executor:AGV007 Step (6) Task execution and progress are frequently uploaded to the blockchain (AGV execution) -After receiving the command, AGV007 calls the genetic algorithm path planning module (with built-in dynamic obstacle avoidance): - Input: real-time warehouse map (obtain the latest version from the blockchain network node), mission target location (23.7, 45.3) -Output: optimal path (e.g. Path: [Aisle1→Aisle3→Shelf5]) -500ms progress on-chain (encrypted and written to data-channel): { "TaskID":"T20250620001", "Timestamp":"2025-06-20T14:00:00.500Z", "Progress":{"Location":[23.7,45.3],"Completion":15%} } Step (7) Task verification and multi-agent data sharing (automatic execution of smart contracts) -AGV007 uploads the final result (including the hash value of the SKU pickup photo) after completing the task; -After the smart contract verification is passed: -Mark the task status as COMPLETED in the ledger; -Trigger SKU dimension data sharing rules: -Open to the owner's permission node: sensitive data such as drug expiration date and pickup time; -Open to warehouse management server nodes: path trajectory, execution time and other operational data.

[0039] -SKU dimension permission control logic: -If SKU_Properties contains the "TempControl" field, only the owner's permission node can access the temperature data; -Path trajectory data is encrypted to the owner's authority node.

[0040] From the above data, we can see that AGV_ID = AGV007, current position = (23.5, 45.2), target position = (23.7, 45.3), power = 85%, and load = 3 tasks.

[0041] By improving the PoS consensus module, the equity weight of each AGV node is calculated according to the equity weight calculation formula W=α×E+β×(1 / D)+γ×(1 / L)+δ×P, where the SKU priority coefficients are assumed to be: high=1.5, medium=1.0, low=0.8; α=0.3, β=0.6, γ=0.1, δ=0.1, and the one with the highest weight gets the task.

[0042] D= m, distance coefficient 1 / D=4.46; Electricity weight: E=0.85; Load factor: 1 / L=1 / (1+3)=0.25; SKU attribute: Priority = High → Priority coefficient: P = 1.5.

[0043] AGV007 weight: W=0.3*0.85+0.6*4.46+0.1*0.25+0.1*1.5=3.106.

[0044] Example 2, as Figure 5 As shown below, it explains how to integrate AGV status (position, power, load) with task-related SKU attributes (such as priority and distance) to calculate equity weights and select the optimal AGV execution node through weighted voting.

[0045] Proposal 1: Given AGV_ID = 001, current position = (10, 20), target position = (50, 60), battery level = 80%, and load = 2 tasks; D= m, distance coefficient 1 / D=0.0177; Electricity weight: E=0.8; Load factor: 1 / L=1 / (1+2)=0.33; SKU attribute: Priority = High → Priority coefficient: P = 1.5.

[0046] Proposal 2: Given AGV_ID = 002, current position = (45, 55), target position = (50, 60), battery level = 60%, and load = 1 task number; D= m, distance coefficient 1 / D=0.1414; Electricity weight: E=0.6; Load factor: 1 / L=1 / (1+1)=0.5; SKU attribute: Priority = Medium → Priority coefficient: P = 1.0.

[0047] By improving the PoS consensus module, the equity weight of each AGV node is calculated according to the equity weight calculation formula W=α×E+β×(1 / D)+γ×(1 / L)+δ×P, where the SKU priority coefficient is: high=1.5, medium=1.0, low=0.8; α=0.4, β=0.3, γ=0.2, δ=0.1, and the one with the highest weight gets the task.

[0048] AGV001 weight: W1=0.4*0.8+0.3*0.12+0.2*0.33+0.1*1.5=0.542; AGV002 weight: W2=0.4*0.6+0.3*0.14+0.2*0.5+0.1*1.0=0.482; Optimal AGV = MAX(W1, W2, …) → AGV001.

[0049] Output: Selected AGV node ID and task execution instructions.

[0050] { "winner_AGV":"001", "start_position":"(10,20)", "target_position":"(50,60)", "SKU_priority":"high" } In addition, it should be noted that the names of the various parts of the specific embodiments described in this specification may be different. Any equivalent or simple changes made based on the structure, features, and principles described in the patent concept of the present invention are included in the scope of protection of the patent of this invention. Those skilled in the art of the technical field to which the present invention relates may make various modifications, supplements, or replace the specific embodiments described in the description with similar methods. As long as they do not deviate from the structure of the present invention or exceed the scope defined by the claims, they shall fall within the scope of protection of the present invention.

Claims

1. A blockchain-based AGV task allocation and management method, characterized by The steps include: (1) Hardware layer construction: The hardware layer includes blockchain network nodes, AGV nodes, warehouse management server nodes, cargo owner authority nodes and 5G communication modules; (2) Software layer configuration: The software layer includes an improved PoS consensus module, an AGV status real-time collection and transmission module, a smart contract execution module, a multi-agent collaboration module, a SKU dimension permission control module, and a multi-agent data interaction and permission management module; The AGV status real-time collection and transmission module and the improved PoS consensus module are both set in the AGV node; The smart contract execution module, multi-agent collaboration module, SKU dimension permission control module, and multi-agent data interaction and permission management module are all set in the blockchain network node; (3) Based on the high SKU order demand, the warehouse management server node generates an AGV task containing task information, encrypts the task information and uploads it to the blockchain network node, which then writes it into the task status ledger; (4) The AGV node collects its own status data in real time through the AGV status real-time collection and transmission module, and uses the 5G communication module to upload the status data of the AGV node to the blockchain network node; Improve the PoS consensus module to calculate the equity weight of each AGV node based on task information and status data, submit competing proposals, and determine the optimal AGV node through a weighted voting mechanism; (5) The smart contract execution module presets the smart contract rules and determines whether the SKU attributes in the task information involve sensitive SKU fields: (5-1) If the SKU attribute involves sensitive SKU fields, the smart contract execution module sends a task instruction to the optimal AGV node and proceeds to step (6), and at the same time sends a permission control request to the multi-agent collaboration module and proceeds to step (7); (5-2) If the SKU attribute does not involve sensitive SKU fields, the smart contract execution module sends a task instruction to the optimal AGV node and proceeds to step (6); (6) The smart contract execution module automatically assigns tasks and updates the task status ledger; the optimal AGV node receives the instruction, plans the path based on the real-time warehouse map, executes the task, and reports the progress to the blockchain network node; after the task is completed, it is verified by the smart contract and stored on the chain, and then returns to step (5); (7) The multi-agent collaboration module triggers the SKU dimension permission control module to filter data, and then starts the data sharing mechanism through the multi-agent data interaction and permission management module to synchronize information to the warehouse management server node and the cargo owner permission node and assign corresponding permissions.

2. The blockchain-based AGV task allocation and management method according to claim 1, characterized in that: In step (3), the task information includes the task quantity and SKU attributes; wherein the SKU attributes include priority; in step (4), the AGV node collects its own status data including current position, target position, power, and load in real time.

3. The blockchain-based AGV task allocation and management method according to claim 2, characterized in that: In the step (4), the equity weight value is calculated by a preset equity weight calculation formula, and the weighted voting mechanism allocates voting weights according to the equity weight values ​​of each AGV node, and the AGV node with the highest number of votes is determined as the optimal AGV node.

4. The blockchain-based AGV task allocation and management method according to claim 3, characterized in that: The equity weight calculation formula is: Equity weight W = α × E + β × (1 / D) + γ × (1 / L) + δ × P, where: E: battery percentage (0≤E≤1); D: distance between AGV and target location; L: current task number + 1; P: SKU priority coefficient; α, β, γ, δ: adjustable weight parameters.

5. The blockchain-based AGV task allocation and management method according to claim 1, characterized in that: In step (6), the optimal AGV node uses a genetic algorithm to plan the optimal path and uses a high-frequency progress reporting mechanism to upload the task progress to the blockchain network node.

6. The blockchain-based AGV task allocation and management method according to claim 5, characterized in that: In step (6), the real-time status data of the optimal AGV node drives the smart contract execution module to execute the task; after the task is completed, the AGV node submits the task result, and after verification by the smart contract execution module, the task completion information is stored on the chain and the execution returns to step (5).

7. The blockchain-based AGV task allocation and management method according to claim 5, characterized in that: In step (6), the high-frequency progress reporting mechanism is to upload the task progress to the blockchain network node every 400ms-600ms.

8. The blockchain-based AGV task allocation and management method according to claim 7, characterized in that: In step (6), the high-frequency progress reporting mechanism is to upload the task progress to the blockchain network node every 500ms.

9. The blockchain-based AGV task allocation and management method according to claim 1, characterized in that: In step (7), the multi-agent collaboration module receives the permission control request from the smart contract execution module, triggering the SKU dimension permission control module to perform data filtering; after data filtering, the multi-agent data interaction and permission management module is triggered to start the multi-agent data sharing mechanism, synchronize the task trajectory and status to the warehouse management server node and the cargo owner permission node, assign corresponding permissions to the warehouse management server node and the cargo owner permission node, and according to the preset rules of the smart contract, only authorized specific fields are opened to the cargo owner permission node.

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