Resource scheduling and distributing method for multiple autonomous guided vehicles

Abstract

The invention relates to an autonomous guided vehicle control system, and provides a resource scheduling and distributing method for multiple autonomous guided vehicles in order to solve the problem that an existing AGV task resource distributing strategy and scheduling method are poor in applicability, and the resource scheduling and distributing method comprises the following steps that the number and the model of needed vehicle resources are determined according to task execution types; detecting to-be-allocated vehicle resources, judging whether the to-be-allocated vehicle resources meet task execution conditions or not, and if yes, sorting the vehicle resources and starting to execute tasks; if not, setting an online waiting time length, and judging whether a to-be-returned vehicle resource which is executing the task exists in the system within the waiting time length or not; if not, task execution is ended; if yes, whether the task continues to be executed or not is judged, and if yes, the to-be-returned vehicle resources on which the task is executed are integrated and released, and the vehicle resource detection step is returned; and if not, task execution is ended, so that resource scheduling allocation of the plurality of autonomous guided vehicles is completed.

Description

Technical Field

[0001] The invention relates to an autonomous guided vehicle control system, and in particular to a resource scheduling and allocation method for multiple autonomous guided vehicles. Background Art

[0002] Automated Guided Vehicle (AGV) is an automated transportation equipment that integrates mechanics, electrical, control, and sensing. It is widely used in many industries and fields such as automobiles, manufacturing, logistics, military industry, and warehousing. AGV plays an important role in changing the warehousing and production operation mode of enterprises and improving efficiency. It has strong path flexibility, high space utilization, safety and reliability, and is increasingly widely used. The AGV scheduling system is the "intelligent brain" of the AGV. By formulating dynamic priority calculation rules, clarifying the dynamic priority update method and principles under the dynamic scheduling strategy, and solving the resource allocation and effective utilization problems in scheduling operations, the core content of AGV scheduling system research is to solve the resource allocation and effective utilization problems in scheduling operations.

[0003] At present, the main research directions for vehicle resource allocation in AGV scheduling systems are resource allocation methods based on optimization algorithms such as genetic algorithms, particle swarm algorithms, and ant colony algorithms, and resource allocation methods based on artificial intelligence technologies such as rule reasoning and fuzzy logic.

[0004] As the scale of the system expands and the complexity increases, how to effectively allocate vehicle resources becomes an important issue. At present, the research on AGV task resource allocation through various technologies and methods is based on the allocation of single-vehicle and single-type vehicle resources, selecting a vehicle from a set of multiple AGVs to complete the task; and for diversified business scenarios, when multiple and various AGVs need to be selected to work together, the above-mentioned task resource allocation method for AGV can no longer provide a reasonable and effective scheduling strategy. Therefore, it is necessary to design a resource allocation strategy suitable for the collaborative work of multiple and various AGVs, optimize the overall scheduling resource configuration, select appropriate vehicle resources to collaboratively complete the task, and thus ensure the rationality of resource allocation. Summary of the invention

[0005] The purpose of the present invention is to solve the problems that the existing AGV task resource allocation method cannot provide a resource allocation strategy and optimal scheduling method suitable for the collaborative work of multiple and various AGVs, and cannot ensure the rationality of resource allocation, and propose a resource scheduling and allocation method for multiple autonomous guided vehicles.

[0006] To achieve the above objectives, the technical solution proposed by the present invention is:

[0007] A resource scheduling and allocation method for multiple autonomous guided vehicles, which is special in that it includes the following steps:

[0008] S1. Determine the number and model of vehicle resources required according to the type of task execution;

[0009] S2, detecting the vehicle resources to be allocated according to the tasks to be performed, and determining whether the vehicle resources to be allocated meet the task execution conditions. If so, sorting the vehicle resources that meet the task execution conditions and starting to execute the tasks until the task execution is completed; if not, executing step S3;

[0010] S3, set the online waiting time, and determine whether there are vehicle resources in the system that are executing the task and are waiting to return within the waiting time; if not, cancel the task and end the task execution; if so, execute step S4;

[0011] S4. Determine whether to continue executing the task. If so, integrate and release the vehicle resources that are waiting to be returned and are currently executing the task, and return to step S2; if not, cancel the task and end the task execution, thereby completing the resource scheduling and allocation of multiple autonomous guided vehicles.

[0012] Furthermore, in step S1, vehicle resources of different models are marked according to model categories, and vehicle resources of the same model are stored in the same linked list to form a plurality of linked lists of different vehicle models.

[0013] Furthermore, step S2 is specifically as follows:

[0014] S2.1. Detect the vehicle resources in multiple linked lists of different vehicle models respectively to determine whether the vehicle resources are available, and update the available vehicle resources in each linked list in real time according to the detection results, and generate the available device set corresponding to each linked list according to the power level of the available vehicle resources;

[0015] S2.2, according to the task to be performed, determine whether the vehicle resources in the multiple available equipment sets meet the task execution conditions, put the vehicle resources that meet the task execution conditions into the vehicle selection set, and start to execute the task until the task is completed, and at the same time update the vehicle resources in the vehicle selection set and each linked list;

[0016] S2.3. If the vehicle resources in the multiple available equipment sets do not meet the task execution conditions, execute step S3.

[0017] Furthermore, in step S2.1, the conditions for determining whether the vehicle resource is available are as follows:

[0018] a. Determine whether the vehicle is online. If so, proceed to step b; if not, replace the next vehicle and start the determination again;

[0019] b. Determine whether the vehicle is in remote automatic mode. If so, execute step c; if not, replace the next vehicle and return to step a;

[0020] c. Determine whether the vehicle is in an idle state. If so, execute step d; if not, replace the next vehicle and return to step a;

[0021] d. Determine whether the remaining power of the vehicle is greater than 10%. If so, execute step e; if not, replace the next vehicle and return to step a;

[0022] e. Determine whether the vehicle has no fault error. If so, execute step f; if not, replace the next vehicle and return to step a;

[0023] f. Determine whether the vehicle is in the parking space. If so, execute step g; if not, replace the next vehicle and return to step a;

[0024] g. Determine whether the vehicle is at the working point. If so, execute step h; if not, replace the next vehicle and return to step a;

[0025] h. Determine whether the vehicle's adjustment mechanism is in the zero position. If so, put the vehicle into the available equipment set; if not, replace the next vehicle and return to step a.

[0026] Furthermore, step S2.2 is specifically as follows:

[0027] According to the task to be performed, the vehicle resources that meet the task execution conditions are placed in the vehicle selection set, and at the same time, it is determined whether the number and model of equipment required to perform the task have met the requirements. If the requirements are met, stop placing vehicle resources in the vehicle selection set; if not, select the next vehicle and return to step a until the number and model of equipment required to perform the task have met the requirements;

[0028] Then, the vehicle resources in the vehicle selection set are sorted according to the vehicle power levels. When executing a task, the vehicles are selected in the sorted order until the task is completed. The selected vehicles are removed from the vehicle selection set and re-entered into the corresponding linked list to achieve real-time update of the vehicle resources in each linked list.

[0029] Furthermore, in step S2.1, the available vehicle resources are sorted by the bubble sort algorithm.

[0030] Furthermore, in step S2.2, the vehicle selection set and each linked list are updated through a merging algorithm to achieve resource allocation and scheduling.

[0031] Furthermore, in step S4, the integration and release of the vehicle resources to be returned and currently executing tasks are specifically as follows:

[0032] The vehicle resource information that is currently executing the task to be returned is put into its corresponding linked list, and then the process returns to step S2 to detect the vehicle resources according to the task to be executed.

[0033] The present invention also proposes a readable storage medium, which is special in that: the readable storage medium stores programs or instructions, and when the programs or instructions are executed by a processor, the steps of the resource scheduling and allocation method for multiple autonomous guided vehicles as described in any one of claims 1-8 are implemented.

[0034] Beneficial effects of the present invention:

[0035] [1] The resource scheduling and allocation method for multiple autonomous guided vehicles of the present invention has simple operation steps and is easy to implement. It effectively allocates vehicle resources of different models according to task requirements and updates the usage status of vehicle resources in real time, so that the vehicle resources for each task execution are the latest vehicle information, ensuring the accurate execution of the task; the overall scheduling and allocation strategy of multiple vehicle resources is optimized by the bubble sort algorithm and the merge algorithm, ensuring the rationality and effectiveness of the allocation.

[0036] [2] The present invention improves the overall operating efficiency of the autonomous guided vehicle and the utilization rate of the equipment through a reasonable resource allocation method, ensures the efficient completion of the task, and also improves the accuracy of the task execution of the autonomous guided vehicle; by reducing the ineffective movement of the autonomous guided vehicle, it effectively reduces energy consumption, improves energy utilization, saves time and resource costs, and improves the overall operation effectiveness of the autonomous guided vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flow chart of a resource scheduling and allocation method for multiple autonomous guided vehicles of the present invention;

[0038] Figure 2 This is a flow chart for determining whether vehicle resources are available in step S2 of an embodiment of the present invention. DETAILED DESCRIPTION

[0039] like Figure 1 As shown, a resource scheduling and allocation method for multiple autonomous guided vehicles includes the following steps:

[0040] S1. Determine the number and model of vehicle resources required according to the type of task execution;

[0041] The vehicle resources of different models are marked according to the model category, and the vehicle resources of the same model are stored in the same linked list to form multiple linked lists of different vehicle models;

[0042] S2, detecting the vehicle resources to be allocated according to the tasks to be performed, and determining whether the vehicle resources to be allocated meet the task execution conditions. If so, sorting the vehicle resources that meet the task execution conditions and starting to execute the tasks until the task execution is completed; if not, executing step S3;

[0043] Step S2 is specifically as follows:

[0044] S2.1. Detect the vehicle resources in multiple linked lists of different vehicle models respectively to determine whether the vehicle resources are available, and update the available vehicle resources in each linked list in real time according to the detection results, sort the power levels of the available vehicle resources by bubble sorting algorithm, and generate the available device set corresponding to each linked list;

[0045] like Figure 2 As shown, the conditions for judging whether vehicle resources are available are as follows:

[0046] a. Determine whether the vehicle is online. If so, proceed to step b; if not, replace the next vehicle and start the determination again;

[0047] b. Determine whether the vehicle is in remote automatic mode. If so, execute step c; if not, replace the next vehicle and return to step a;

[0048] c. Determine whether the vehicle is in an idle state. If so, execute step d; if not, replace the next vehicle and return to step a;

[0049] d. Determine whether the remaining power of the vehicle is greater than 10%. If so, execute step e; if not, replace the next vehicle and return to step a;

[0050] e. Determine whether the vehicle has no fault error. If so, execute step f; if not, replace the next vehicle and return to step a;

[0051] f. Determine whether the vehicle is in the parking space. If so, execute step g; if not, replace the next vehicle and return to step a;

[0052] g. Determine whether the vehicle is at the working point. If so, execute step h; if not, replace the next vehicle and return to step a;

[0053] h. Determine whether the vehicle's adjustment mechanism is in the zero position. If so, put the vehicle into the available equipment set; if not, replace the next vehicle and return to step a.

[0054] S2.2. According to the tasks to be performed, determine whether the vehicle resources in multiple available equipment sets meet the task execution conditions, put the vehicle resources that meet the task execution conditions into the vehicle selection set, and start executing the task until the task is completed. At the same time, the vehicle selection set and each linked list are updated through the merging algorithm.

[0055] According to the task to be performed, the vehicle resources that meet the task execution conditions are placed in the vehicle selection set, and at the same time, it is determined whether the number and model of equipment required to perform the task have met the requirements. If the requirements are met, stop placing vehicle resources in the vehicle selection set; if not, select the next vehicle and return to step a until the number and model of equipment required to perform the task have met the requirements;

[0056] Then, the vehicle resources in the vehicle selection set are sorted according to the vehicle power levels. When executing a task, the vehicles are selected in the sorted order until the task is completed. The selected vehicles are removed from the vehicle selection set and re-entered into the corresponding linked list to achieve real-time update of the vehicle resources in each linked list.

[0057] S2.3. If the vehicle resources in the multiple available equipment sets do not meet the task execution conditions, execute step S3.

[0058] S3, set the online waiting time, and determine whether there are vehicle resources in the system that are executing the task and are waiting to return within the waiting time; if not, cancel the task and end the task execution; if so, execute step S4;

[0059] S4. Determine whether to continue executing the task. If so, integrate and release the vehicle resources that are waiting to be returned and are currently executing the task, and return to step S2; if not, cancel the task and end the task execution, thereby completing the resource scheduling and allocation of multiple autonomous guided vehicles.

[0060] In this embodiment, the task of storing goods is carried out for the shelves and shelves at two different positions in the warehouse. The tasks are assigned by two types of AGVs, namely, Z-type AGV and D-type AGV. The Z-type AGV can only place Z products, and the D-type AGV can only place D products. The task execution types are divided into three types: A, B, and C. The execution of tasks A and B requires one Z-type AGV and one D-type AGV respectively. The execution of task C requires one D-type AGV and two Z-type AGVs. In the collaborative task process, multiple AGVs work together to complete the same task.

[0061] After the task is issued, the scheduling system determines the number and model of vehicle resources required according to the task execution type. First, the vehicle resources are detected according to the task to be executed, and the existing vehicle resources are judged whether they meet the conditions for executing the task. The vehicle resources that meet the conditions for task execution are sorted. After the vehicle resources are successfully allocated, the vehicle must be locked and the task is started until the task is completed. If the vehicle resources in the system cannot meet the requirements of this task temporarily, the online waiting time is set, and the system enters the waiting state. After other tasks are completed, the corresponding vehicle resources are released and resources are allocated again; if the waiting time exceeds the waiting time set by the system, the task cannot be executed and the system automatically ends the task; if the waiting time does not exceed the predetermined time, the user can choose to continue waiting for the release of resources or cancel the task. If you choose to cancel the task, it will directly enter the cancellation state, otherwise it will continue to enter the task resource allocation link. When resources are released, the task will continue until the task is completed and the entire task execution process ends.

[0062] In this business scenario, all collaborative tasks have the same priority. The running speed of AGVs is the same when fully loaded and unloaded. Once the AGV is locked, it will not accept other tasks until the resources are released. The first task to arrive will occupy the AGV first. Other tasks can occupy the resources only after the AGV releases the resources. The scheduling system receives the tasks to be executed and reasonably allocates them to multiple AGVs to complete the tasks at the lowest cost. The system allocates tasks in a resource-preemptive manner.

[0063] First, two linked lists are designed to store the corresponding AGV models respectively, and then the resources of each device are detected. After the resource detection is successful, the models that meet the conditions are dynamically added to the corresponding model linked list in real time. After the addition is completed, the linked list is traversed according to the power level, and then a new linked list is output. Each time a vehicle is selected, the first element is selected from each new linked list. After the corresponding model vehicle is selected, it is placed in the final vehicle selection set according to the vehicle type required for the task, and then the vehicle selection set is returned. The selected AGV changes from an available state to an unavailable state and is locked from executing new tasks until the assigned task is completed and the resources are released. Only then can the state be set to available.

[0064] Solving the problem of available equipment is to select multiple AGVs from the AGV vehicles that meet the conditions to complete the collaborative task. Each task is completed according to a fixed point route. The task execution path of vehicles for the same task is fixed. After the task is issued, the vehicle is selected and allocated. Each device performs resource detection in the following 8 situations to determine whether the vehicle is in an available state. When any condition is not met, the AGV device is directly excluded and the resource detection of the next vehicle is carried out. When the conditions are met, it is added to the set of available devices. At the same time, it is determined whether the number and type of equipment required for the task meet the requirements. If so, the detection is stopped. If not, the next device resource judgment is entered.

[0065] The device resource detection conditions are as follows:

[0066] a. Determine whether the vehicle is online. If so, proceed to step b; if not, replace the next vehicle and start the determination again;

[0067] b. Determine whether the vehicle is in remote automatic mode. If so, execute step c; if not, replace the next vehicle and return to step a;

[0068] c. Determine whether the vehicle is in an idle state. If so, execute step d; if not, replace the next vehicle and return to step a;

[0069] d. Determine whether the remaining power of the vehicle is greater than 10%. If so, execute step e; if not, replace the next vehicle and return to step a;

[0070] e. Determine whether the vehicle has no fault error. If so, execute step f; if not, replace the next vehicle and return to step a;

[0071] f. Determine whether the vehicle is in the parking space. If so, execute step g; if not, replace the next vehicle and return to step a;

[0072] g. Determine whether the vehicle is at the working point. If so, execute step h; if not, replace the next vehicle and return to step a;

[0073] h. Determine whether the vehicle's adjustment mechanism is in the zero position. If so, put the vehicle into the available equipment set; if not, replace the next vehicle and return to step a.

[0074] Add the Z-type AGV to the Z-type AGV linked list, and the D-type AGV to the D-type AGV linked list, and sort them according to the power level. When executing a task, select a vehicle from the sorted linked list, and the selected vehicle will be deleted from the linked list. Each time a task is executed, the resource determination method will be called to remove resources that do not meet the conditions, regenerate the linked list, sort it, and then select the vehicle from the newly generated dynamic linked list. This ensures that the resources selected each time are the latest, and the selected resources are added to the resource selection linked list. After the resources are released, they are deleted from the selected linked list.

[0075] For example, there are n Z-type AGVs and m D-type AGVs. The set of Z-type AGVs is defined as the linked list AGVZ, the set of D-type AGVs is defined as the linked list AGVD, and the selected vehicle set linked list is defined as AGVS. The resource allocation steps are as follows:

[0076] 1) First, perform resource judgment, remove the equipment that does not meet the conditions, and add all Z-type and D-type AGVs that meet the conditions to their respective set lists. PZN is the Z-type vehicle number, which is a character type; TZN is the power of the vehicle, which is an integer type; AGVZ = {{P Z1 ,T Z1},{P Z2 ,T Z2},{P Z3 ,T Z3}……

[0077] {P ZN ,T ZN}}, D-type AGV set, AGVD = {{P D1 ,T D1},{P D2 ,T D2},{P D3 ,T D3}...{PDM,TDM}}, AGVS is defined as the NULL set;

[0078] 2) Using the bubble sort algorithm, the AGV vehicles are sorted in order according to their power levels, and a new set sequence is generated for the AGVs that meet the conditions in descending order of power levels. The Z-type AGV set AGVZ = {{P ZN ,T ZN},{P Z(N-1) ,T Z(N-1)},{P Z(N-2) ,T Z(N-2)}……{P Z1 ,T Z1}}, D-type AGV car set AGVD = { = { {P DM ,T DM},{PD(M-1) ,T D(M-2)},{P D(M-3) ,T D(M-3)}……{P D1 ,T D1}};

[0079] 3) Select vehicles according to the task type, always starting from the first element in the linked list, select vehicles from the AGVZ and AGVS sets, and add the selected vehicles to AGVS in the order of AGV types required for the task. The vehicle set for the locked task is AGVS = {{P ZN ,D ZN},{P DM ,T DM}};

[0080] 4) After the selection is completed, the selected AGV vehicle is deleted from the corresponding type AGV linked list. The linked list after deletion is AGVZ = {{P Z(N-1 ),T Z(N-1)},{P Z(N-2 ),T Z(N-2)}……{P Z1 ,T Z1}}, AGVD = {{P D(M-1 ),T D(M-1)},{P D(M-2) ,T D(M-2)}……{P D1 ,T D1}};

[0081] 5) After the first round of selection, if another vehicle needs to be selected, re-judgment of resources is performed, sorting of power, and re-selection from the vehicle set. After selection, the corresponding vehicle is added to the vehicle set of the locked task. The selection is terminated when it is no longer needed.

[0082] 6) Return the locked mission vehicle set AGVS.

[0083] 7) Assign tasks to the vehicles in the collection one by one.

[0084] Among them, bubble sort is an algorithm for sorting arrays or sequences from large to small or from small to large. By comparing and exchanging the positions of adjacent elements, each traversal can obtain the maximum or minimum value of the remaining elements and put them into the correct position in the ordered sequence.

[0085] The merge algorithm merges ordered subsequences to obtain a completely ordered sequence, that is, first make each subsequence ordered, and then make the subsequence segments ordered. Assuming that the initial sequence contains N records, it can be regarded as N ordered subsequences, each with a length of 1. Then they are merged in pairs to obtain half of the N ordered subsequences of length 2 or 1, and then merged in pairs, and repeated until an ordered sequence of length n is obtained.

[0086] The present invention adopts a merge sort algorithm to ensure the efficiency of task execution, with high reliability, and can quickly select multiple AGV vehicles of various varieties that meet the needs of task execution, and send tasks for collaborative work to complete the resource scheduling and allocation of multiple autonomous guided vehicles.

Claims

1. A resource scheduling and allocation method for multiple autonomous guided vehicles, characterized in that: The following steps are involved: S1. Determine the number and model of vehicle resources required according to the type of task execution; S2. Detect the vehicle resources to be allocated according to the tasks to be performed, and determine whether the vehicle resources to be allocated meet the task execution conditions. If so, sort the vehicle resources that meet the task execution conditions and start executing the tasks until the task execution is completed; if not, execute step S3; S3, setting the online waiting time, and determining whether there are vehicle resources in the system that are currently executing tasks and are waiting to be returned within the waiting time; if not, the task is canceled and the task execution ends; If yes, execute step S4; S4. Determine whether to continue executing the task. If so, integrate and release the vehicle resources that are waiting to be returned and are currently executing the task, and return to step S2; if not, cancel the task and end the task execution, thereby completing the resource scheduling and allocation of multiple autonomous guided vehicles.

2. The resource scheduling and allocation method for multiple autonomous guided vehicles according to claim 1, characterized in that: In step S1, vehicle resources of different models are marked according to model categories, and vehicle resources of the same model are stored in the same linked list to form a plurality of linked lists of different vehicle models.

3. The resource scheduling and allocation method for multiple autonomous guided vehicles according to claim 2 is characterized in that: Step S2 is specifically as follows: S2.

1. Detect the vehicle resources in multiple linked lists of different vehicle models respectively to determine whether the vehicle resources are available, and update the available vehicle resources in each linked list in real time according to the detection results, and generate the available device set corresponding to each linked list according to the power level of the available vehicle resources; S2.2, according to the task to be performed, determine whether the vehicle resources in the multiple available equipment sets meet the task execution conditions, put the vehicle resources that meet the task execution conditions into the vehicle selection set, and start to execute the task until the task execution is completed, and at the same time update the vehicle resources in the vehicle selection set and each linked list; S2.

3. If the vehicle resources in the multiple available equipment sets do not meet the task execution conditions, execute step S3.

4. A resource scheduling and allocation method for multiple autonomous guided vehicles according to claim 3, characterized in that: In step S2.1, the conditions for determining whether the vehicle resources are available are as follows: a. Determine whether the vehicle is online. If so, proceed to step b; if not, replace the next vehicle and start the determination again; b. Determine whether the vehicle is in remote automatic mode. If so, execute step c; if not, replace the next vehicle and return to step a; c. Determine whether the vehicle is in an idle state. If so, execute step d; if not, replace the next vehicle and return to step a; d. Determine whether the remaining power of the vehicle is greater than 10%. If so, execute step e; if not, replace the next vehicle and return to step a; e. Determine whether the vehicle has no fault error. If so, execute step f; if not, replace the next vehicle and return to step a; f. Determine whether the vehicle is in the parking space. If so, execute step g; if not, replace the next vehicle and return to step a; g. Determine whether the vehicle is at the working point. If so, execute step h; if not, replace the next vehicle and return to step a; h. Determine whether the vehicle's adjustment mechanism is in the zero position. If so, put the vehicle into the available equipment set; if not, replace the next vehicle and return to step a.

5. The resource scheduling and allocation method for multiple autonomous guided vehicles according to claim 4 is characterized in that: Step S2.2 is specifically as follows: According to the task to be performed, the vehicle resources that meet the task execution conditions are placed in the vehicle selection set, and at the same time, it is determined whether the number and model of equipment required to perform the task have met the requirements. If the requirements are met, stop placing vehicle resources in the vehicle selection set; if not, select the next vehicle and return to step a until the number and model of equipment required to perform the task have met the requirements; Then, the vehicle resources in the vehicle selection set are sorted according to the vehicle power levels. When executing a task, the vehicles are selected in the sorted order until the task is completed. The selected vehicles are removed from the vehicle selection set and re-entered into the corresponding linked list to achieve real-time update of the vehicle resources in each linked list.

6. The resource scheduling and allocation method for multiple autonomous guided vehicles according to claim 5 is characterized in that: In step S2.1, the available vehicle resources are sorted by the power level using a bubble sort algorithm.

7. A resource scheduling and allocation method for multiple autonomous guided vehicles according to claim 6, characterized in that: In step S2.2, the vehicle selection set and each linked list are updated through a merging algorithm to achieve resource allocation and scheduling.

8. The resource scheduling and allocation method for multiple autonomous guided vehicles according to claim 7 is characterized in that: In step S4, the integration and release of the vehicle resources to be returned and currently executing tasks are specifically as follows: The vehicle resource information that is currently executing the task to be returned is put into its corresponding linked list, and then the process returns to step S2 to detect the vehicle resources according to the task to be executed.

9. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of a resource scheduling and allocation method for multiple autonomous guided vehicles as described in any one of claims 1-8 are implemented.

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