Multi-target Cooperative Path Planning for Air-Sea Heterogeneous Unmanned System

Shaoxin Qin, Xingwang Yang, Wangcheng Zhang, Mingyang Sun, Xingyu Liu, Z. Zhen
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Abstract

This paper focuses on the cooperative path planning of multi-target heterogeneous unmanned systems in air-sea. In the face of multiple targets, Unmanned Aerial Vehicles (UAV) flies fast, but its range and load capacity are limited; Unmanned Surface Vehicles (USV) has strong load capacity and long endurance, but its navigation speed is slow. This paper studies the path planning problem of the air-sea heterogeneous unmanned system composed of UAVs and USVs for a large range and multiple targets, taking the time for the unmanned system to complete this task as the optimization objective. Firstly, distinguish targets with ReConDensity-Ratio based clustering algorithm, and find appropriate refueling points for UAVs and USVs in each classification. Secondly, the Double-deck Travel Modified Particle Swarm Optimization algorithm (DT-MPSO) is used to plan the path of targets and find the shortest route. Finally, the effectiveness of the proposed method is verified by simulation experiments.
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海空异构无人系统多目标协同路径规划
研究了海空多目标异构无人系统协同路径规划问题。面对多目标时,无人机飞行速度快,但航程和载荷能力有限;无人水面车辆(USV)承载能力强,续航力长,但其导航速度较慢。本文以无人系统完成该任务的时间为优化目标,研究了由无人机和无人艇组成的海空异构无人系统在大范围多目标下的路径规划问题。首先,采用基于recondenity - ratio的聚类算法对目标进行区分,并在每种分类中找到适合无人机和无人水面艇的加油点;其次,采用双层行程修正粒子群优化算法(DT-MPSO)规划目标路径,寻找最短路径;最后,通过仿真实验验证了所提方法的有效性。
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