Unmanned vehicle multi-point dynamic aggregation structure heuristic task planning method

Through the heuristic task planning method of multi-point dynamic set structure of unmanned vehicles, the integer planning framework and alliance redundancy are used to solve the problem of large computing resources and long time in the multi-point dynamic aggregation optimization problem, and efficient task allocation and Path planning meets real-time needs.

CN119292261AActive Publication Date: 2025-01-10TONGJI UNIV
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Patent Information

Application Number
CN202411240687.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-09-05
Publication Date
2025-01-10
Estimated Expiration
2044-09-05

AI Technical Summary

Technical Problem

The existing technology consumes a lot of computing resources, is time-consuming and easy to fall into local optimal solutions when solving multi-point dynamic aggregation optimization problem, and is difficult to effectively apply in large-scale problems.

Method used

The heuristic task planning method of unmanned vehicles is adopted to construct a multi-point dynamic set structure, and through value sorting and joint execution income calculation, combined with an integer planning framework and appropriate alliance redundancy, task allocation and path planning are optimized.

Benefits of technology

It significantly reduces computing complexity, improves real-time and task execution efficiency, and can generate high-quality solutions in a short time, ensuring that tasks are completed within a specific time window.

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Abstract

The invention relates to an unmanned vehicle multi-point dynamic aggregation construction heuristic task planning method, which comprises the following steps: discriminating a task with the highest value, determining an unmanned vehicle which is most adaptive to the task to join a team list, aiming at each task, calculating the income of all unmanned vehicles, selecting the unmanned vehicles which rank at the top k, and establishing a task alliance with certain redundancy. And repeatedly executing until all the established tasks are effectively configured, calculating potential benefits of the unmanned vehicles which are not allocated or have completed the established alliance tasks to participate in the remaining tasks, and assigning the unmanned vehicles to the task with the highest benefits. Compared with the prior art, the method has the advantages that the task execution efficiency and effect are improved, resources of unmanned vehicles in a team are fully utilized, a high-quality solution is generated within a short time, and the real-time requirement is met.
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Citation Information

Patent Citations

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