基于规则的无人机集群区域协同搜索算法
The Regional Collaboration Search Algorithm of UAV Swarm Based on Rules
摘要: 区域搜索是无人机集群非常重要的一个应用方向，而科学合理的控制算法是提高集群执行任务效率的最有效途径。现有的规划控制算法存在非自主、规模小、计算复杂等不足之处，本文针对大规模无人机集群对不确定区域执行搜索任务，基于Boids动力学模型提出了一种基于规则的区域协同搜索算法，该算法具有自主性好、鲁棒、计算简单以及在理论上能以概率1实现搜索区域全覆盖等优点，并且通过仿真验证了该算法的有效性。
Abstract: Regional search is a very important application direction for UAV swarms, and adopting scientific and reasonable control algorithm is the most effective way to improve the efficiency of swarms executing tasks. The existing planning control algorithms are involuntary, small-scale, and computationally complex. This paper proposes a rule-based regional collaboration search algorithm, based on the kinetic model—Boids, for large-scale UAV swarms to perform search tasks on uncertain regions. The search algorithm has the advantages of good autonomy, robustness, simple calculation and theoretical full coverage of the search area with probability 1. The effectiveness of the algorithm is verified by simulation.
文章引用：张江东. 基于规则的无人机集群区域协同搜索算法[J]. 计算机科学与应用, 2019, 9(11): 2028-2036. https://doi.org/10.12677/CSA.2019.911228

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