基于改进最小边际代价算法的多 USV 多 AUV 任务分配
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作者单位:

深圳大学

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中图分类号:

00-00

基金项目:

国家自然科学基金项目(62373255)


Task Assignment for Multiple USVs and AUVs Based on Improved Minimum Marginal Cost Algorithm
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Affiliation:

Shenzhen University

Fund Project:

The National Natural Science Foundation of China (62373255)

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    摘要:

    随着自主水下机器人(Autonomous Underwater Vehicle, AUV)和无人水面艇(Unmanned Surface Vessel, USV)在民用和军事领域的应用不断扩展, USV 与 AUV 协同完成相关任务的作业模式受到了广泛关注. 本文针 对多 USV 和多 AUV 协同访问多目标点的任务分配问题进行了研究, 旨在最小化多 USV 和 AUV 系统访问所有 目标点的总旅行距离. 首先, 建立了考虑通信约束和 AUV 最大航程约束的多 USV 多 AUV 协同多点访问任务分 配问题的数学模型, 并对问题的NP-Hardness性质进行了分析. 其次, 本文提出一个两阶段任务分配算法: 1) 先利 用最小边际代价算法构建各 USV访问完所有水面目标点的路径, 再采用最近插入策略分配水下目标点; 2) 通过 多个邻域搜索算子对初始解进行优化, 得到可行最终解. 相对于已有流行的自组织映射算法, 仿真实验表明所提 出任务分配算法能在较短计算时间内得到质量较优的任务分配方案.

    Abstract:

    With the rapid development of Autonomous Underwater Vehicles (AUVs) and Unmanned Surface Vessels (USVs) in both civil and military domains, the collaboration between USVs and AUVs for performing certain tasks has attracted widespread attention. This paper focuses on the task assignment problem for multiple USVs and AUVs to visit multiple target locations, aiming to minimize the total travel distance for multiple USVs and AUVs to visit all target locations. Firstly, a mathematical model for the studied task assignment problem is established, considering the AUVs’ communication constraints and the maximum travel distance, and the NP-hardness of the problem is analyzed. Secondly, a two-stage task assignment algorithm is proposed: 1) The initial routes of the USVs to visit all the surface target locations are first constructed using the Minimum Marginal-cost Algorithm, and the nearest insertion strategy is adopted to assign underwater target locations? 2) The initial assignment solution is improved through several neighborhood search operators. Simulation results show that the proposed algorithm can obtain a better assignment solution within a shorter running time than the existing popular self-organizing map algorithm.

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  • 收稿日期:2024-04-30
  • 最后修改日期:2024-09-21
  • 录用日期:2024-08-24
  • 在线发布日期: 2024-09-09
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