An unmanned aerial vehicle multi-task resource allocation and optimization method based on optimal efficiency-cost ratio

Abstract

The application provides a multi-task resource allocation and optimization method based on optimal efficiency-cost ratio for unmanned aerial vehicles, and relates to resource allocation and optimization technology in the field of unmanned aerial vehicles. The application is aimed at multi-task resource allocation under the condition of limited resources of unmanned aerial vehicles. Whether the resources of unmanned aerial vehicles meet the execution of all tasks is judged according to the resource consumption of the tasks and the resource consumption required by the unmanned aerial vehicles for executing the tasks. Different weight coefficients are given to different tasks under the condition that all tasks cannot be executed. After the priority execution task is determined, other tasks are allocated according to the remaining resources according to the optimal efficiency-cost ratio principle, so that the online allocation of multi-task of unmanned aerial vehicles is realized. The method is simple, and is helpful to improve the stability of the running state of unmanned aerial vehicles during the execution of multi-task.

Description

Technical Field

[0001] This invention relates to resource allocation and optimization technology in the field of unmanned aerial vehicle (UAV) applications, and in particular to a method for multi-task resource allocation and optimization of UAVs based on optimal cost-effectiveness ratio, which is applicable to resource optimization and allocation under the condition of UAV multi-task parallelism. Background Technology

[0002] As a highly maneuverable low-altitude aircraft, unmanned aerial vehicles (UAVs) are widely used in various fields, such as low-altitude mapping, pesticide spraying, power line maintenance, and reconnaissance in complex environments. However, UAVs are limited by payload capacity, which restricts the resources available for multiple payloads. In the process of multi-tasking in parallel, with limited resources, how to select the optimal resource allocation method based on task importance and the best resource allocation strategy to achieve optimal UAV resource management is one of the key issues that needs to be addressed in UAV resource optimization.

[0003] However, at present, there are few publicly available technologies for the allocation and optimization of multi-task resources for UAVs, both domestically and internationally, making it difficult to achieve effective allocation of multi-task resources for UAVs. Summary of the Invention

[0004] In view of this, the present invention proposes a method for resource allocation and optimization of UAV multi-task based on optimal cost-effectiveness ratio. This method determines whether UAV resources are sufficient for all task execution based on the resource consumption of each task and the resource consumption required for the UAV to execute the task. If not, different weight coefficients are assigned to different tasks. After determining the priority tasks, other tasks are allocated based on the remaining resources according to the optimal cost-effectiveness ratio principle, thus achieving online allocation of UAV multi-tasks.

[0005] The objective of this invention is achieved as follows:

[0006] A method for multi-task resource allocation and optimization of unmanned aerial vehicles (UAVs) based on optimal cost-effectiveness ratio includes the following steps:

[0007] Step 1, assuming the total amount of resources the drone can currently use to perform the task is... The number of tasks to be executed is , No. The resource consumption per unit of time for each task is Complete the first The execution time of each task is Then the first step is completed. The resource consumption of each task is ,implement The total resource consumption of each task is ;

[0008] Step 2, classify tasks according to their importance. Different tasks are assigned different task importance coefficients, that is... ,in For the first The importance coefficient of each task;

[0009] Step 3, according to Total resource consumption for each task Resource consumption of drones during mission execution To determine whether the current drone resources are sufficient. The execution of all tasks; among which , The unit resource consumption of drones in the current environment, For drones to perform The flight time required for each mission ;

[0010] Step 4, if + > If the current resources are insufficient to support it, then the resources are insufficient to support it. The execution of each task needs to be optimized based on its importance and resource consumption.

[0011] Step 5: Based on task importance, execution time, and resource consumption, set the cost-effectiveness ratio coefficient for different tasks. , among which, the The cost-effectiveness ratio of each task is , This is the cost-effectiveness weighting factor;

[0012] Step 6, Compare middle Based on the value of each cost-effectiveness ratio coefficient, select the task with the highest cost-effectiveness ratio and calculate the resources required to execute that task. ,in Indicates the index corresponding to the task with the highest efficiency-cost ratio. ;

[0013] Step 7, if Then choose The task corresponding to the subscript is the priority task to be executed. > Then, tasks with high cost-effectiveness ratios are selected in sequence until a task that meets the resource consumption requirements is found and prioritized for execution.

[0014] Step 8, after determining the priority tasks, order ,like If so, the drone will only perform the priority task; if This indicates that there are still resources available to add new tasks; proceed to step 9. This indicates the resource consumption of the task requiring the least resources.

[0015] Step 9: Select a task with a high cost-effectiveness ratio to execute concurrently with the current task, i.e., let... ,in, This indicates the addition of a new task; return to step 8 to continue the evaluation. and The relationship, until No new tasks will be added, and task allocation is complete.

[0016] The beneficial effects of this invention are as follows:

[0017] 1. This invention assigns different weight coefficients to different tasks. After determining the priority task to be executed, other tasks are allocated to be executed based on the principle of optimal cost-effectiveness and the remaining resources, thereby realizing the online allocation of multiple tasks for UAVs.

[0018] 2. This invention can select the optimal resource and task allocation method according to the relationship between resources and tasks, thereby improving the execution efficiency of UAV multi-task.

[0019] 3. This invention has a small computational load, which helps improve the operational stability of UAVs when performing multiple tasks, and has good promotional value. Attached Figure Description

[0020] Figure 1 This is a flowchart of a multi-task resource allocation optimization method for UAVs based on the optimal cost-effectiveness ratio. Detailed Implementation

[0021] The invention will now be further described with reference to the accompanying drawings.

[0022] An optimization method for multi-task resource allocation of unmanned aerial vehicles (UAVs) based on optimal cost-effectiveness ratio, such as... Figure 1 As shown, the specific steps include the following:

[0023] (1) Assume that the total amount of resources currently available for the UAV to perform tasks is The number of tasks to be executed is , No. The resource consumption per unit of time for each task is Complete the first The execution time of each task is Then the first step is completed. The resource consumption of each task is Then execute The total resource consumption of each task is ;

[0024] (2) Based on the importance of the task Different tasks are assigned different task importance coefficients, that is... ,in For the first The importance coefficient of each task;

[0025] (3) According to Resource consumption of each task Resource consumption of drones during mission execution Determine if the current drone's resources are sufficient. The complete execution of the task, including ,in The unit resource consumption of drones in the current environment, To execute The flight time required for each mission drone is: ;

[0026] (4) If If so, the drone can complete the current task without needing to optimize it; if + > If the current resources are insufficient to support it, then the resources are insufficient to support it. The execution of each task needs to be optimized based on its importance and resource consumption.

[0027] (5) Set the cost-effectiveness ratio coefficient for different tasks based on their importance, execution time, and resource consumption. ,in, , This is the cost-effectiveness weighting factor;

[0028] (6) Comparison Inside Based on the value of each cost-effectiveness ratio coefficient, select the task with the highest cost-effectiveness ratio and calculate the resources required to execute that task. ,in This indicates the index corresponding to the task with the highest cost-effectiveness ratio. ;

[0029] (7) If ,choose The task corresponding to the subscript is the priority task to be executed. > Then, select the tasks with the highest cost-effectiveness ratio in sequence, and recalculate the resources Q required for each task. X Until a resource consumption requirement is met. Prioritize tasks;

[0030] (8) After determining the priority tasks, order ,judge , This indicates the resource consumption of the task requiring the fewest resources; if so, the drone will only execute the priority task. This indicates that there are resources available to increase task execution;

[0031] (9) Select a task with a high cost-effectiveness ratio to execute concurrently with the current task, i.e., let ,in, Indicates the currently added task; return to step (8) to continue the judgment. and The relationship between them, until No new tasks will be added, and task allocation is complete.

[0032] In summary, this invention addresses the problem of multi-task resource allocation under resource-constrained conditions for unmanned aerial vehicles (UAVs). It determines whether UAV resources are sufficient for all tasks to be executed based on the resource consumption of each task and the resource consumption required for the UAV to perform those tasks. If not, different weight coefficients are assigned to different tasks. After determining the priority tasks, other tasks are allocated based on the optimal cost-effectiveness principle and the remaining resources, thus achieving online allocation of multiple tasks for the UAV. This method is simple to implement and helps improve the stability of the UAV's operational status during multi-task execution.

Claims

1. A method for multi-task resource allocation and optimization of unmanned aerial vehicles (UAVs) based on optimal cost-effectiveness ratio, characterized in that, Includes the following steps: Step 1, assuming the total amount of resources the drone can currently use to perform the task is... The number of tasks to be executed is , No. The resource consumption per unit of time for each task is Complete the first The execution time of each task is Then the first step is completed. The resource consumption of each task is ,implement The total resource consumption of each task is ; Step 2, classify tasks according to their importance. Different tasks are assigned different task importance coefficients, that is... ,in For the first The importance coefficient of each task; Step 3, according to Total resource consumption for each task Resource consumption of drones during mission execution To determine whether the current drone resources are sufficient. The execution of all tasks; among which , The unit resource consumption of drones in the current environment, For drones to perform The flight time required for each mission ; Step 4, if + > If the current resources are insufficient to support it, then the resources are insufficient to support it. The execution of each task needs to be optimized based on its importance and resource consumption. Step 5: Based on task importance, execution time, and resource consumption, set the cost-effectiveness ratio coefficient for different tasks. , among which, the The cost-effectiveness ratio of each task is , This is the cost-effectiveness weighting factor; Step 6, Compare middle Based on the value of each cost-effectiveness ratio coefficient, select the task with the highest cost-effectiveness ratio and calculate the resources required to execute that task. ,in Indicates the index corresponding to the task with the highest efficiency-cost ratio. ; Step 7, if Then choose The task corresponding to the subscript is the priority task to be executed. > Then, tasks with high cost-effectiveness ratios are selected in sequence until a task that meets the resource consumption requirements is found and prioritized for execution. Step 8, after determining the priority tasks, order ,like If so, the drone will only perform the priority task; if This indicates that there are still resources available to add new tasks; proceed to step 9. This indicates the resource consumption of the task requiring the least resources. Step 9: Select a task with a high cost-effectiveness ratio to execute concurrently with the current task, i.e., let... ,in, This indicates the addition of a new task; return to step 8 to continue the evaluation. and The relationship, until No new tasks will be added, and task allocation is complete.

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