模仿鸽群与鱼群，实现多无人机避障编队飞行
Novel Pigeon-inspired 3D Obstacle Detection and Avoidance Maneuver for Multi-UAV Systems
- 结合鸽群与鱼群行为，设计分层式避障控制策略
- 3D空间中成功实现动态障碍物下的稳定编队飞行
- 适合城市环境下多无人机协同任务应用
多无人系统在城市环境中面临静态与动态障碍物的挑战。受鲤鱼和鸽群集体行为启发，本文提出一种受自然启发的无碰撞编队控制方法，支持多无人机系统在复杂环境中的避障机动。研究采用半分布式控制架构：基于概率性Lloyd算法的集中式引导算法负责最优位置分配，分布式控制则用于机间碰撞与障碍物规避。进一步将该框架扩展至三维空间，提出了全新的3D机动定义。在2D与3D场景下的多无人机系统测试表明，该方法在存在静止与移动障碍物的动态环境中具有显著有效性。
原文摘要 · Abstract (English)
Recent advances in multi-agent systems manipulation have demonstrated a rising demand for the implementation of multi-UAV systems in urban areas, which are always subjected to the presence of static and dynamic obstacles. Inspired by the collective behavior of tilapia fish and pigeons, the focus of the presented research is on the introduction of a nature-inspired collision-free formation control for a multi-UAV system, considering the obstacle avoidance maneuvers. The developed framework in this study utilizes a semi-distributed control approach, in which, based on a probabilistic Lloyd's algorithm, a centralized guidance algorithm works for optimal positioning of the UAVs, while a distributed control approach has been used for the intervehicle collision and obstacle avoidance. Further, the presented framework has been extended to the 3D space with a novel definition of 3D maneuvers. Finally, the presented framework has been applied to multi-UAV systems in 2D and 3D scenarios, and the obtained results demonstrated the validity of the presented method in dynamic environments with stationary and moving obstacles.
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