Stochastic Heuristic Algorithms for Multi-UAV Cooperative Path Planning

被引：0

作者：

Zhao, Chang ^{[1
]}

Liu, Yungang ^{[1
]}

Yu, Linzhen ^{[1
]}

Li, Wenjuan ^{[1
]}

机构：

[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China

来源：

2021 PROCEEDINGS OF THE 40TH CHINESE CONTROL CONFERENCE (CCC) | 2021年

关键词：

Multiple UAVs; Path Planning; Stochastic Heuristic Algorithms; Algorithm Improvement; PIGEON-INSPIRED OPTIMIZATION; COLLISION-AVOIDANCE; SEARCH; SYSTEMS; COLONY; MODEL; PSO;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Multi-UAV collaborative path planning (MUCPP) is a complex multi-objective optimization problem. Compared with the traditional path planning algorithms, stochastic heuristic algorithm (SHA) can solve this kind of problem more efficiently. In this paper, we first introduce several widely used UAV path planning algorithms. Then, recent works on MUCPP based on SHA are reviewed, where the feature, improvement and application, merits and demerits of those proposed algorithms are discussed. Finally, the challenges of path planning for multiple UAVs are put forward and the future development trend is prospected from the aspects of theoretical and applied research.

引用

页码：7677 / 7682

页数：6

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