Bio-Inspired Self-Organized Fission–Fusion Control Algorithm for UAV Swarm

Swarm control has become a challenging topic for the current unmanned aerial vehicle (UAV) swarm due to its conflicting individual behaviors and high external interference. However, in contrast static obstacles, limited attention been paid fission–fusion behavior of against dynamic obstacles. In this paper, inspired by interaction mechanism motion starlings, we propose Bio-inspired Self-organized Fission–fusion Control (BiSoFC) algorithm UAV swarm, where number UAVs sub-swarm is controllable. It solves problem under obstacle interference with tracking function. Firstly, establish kinematic equations controllers introduce framework achieve movement lower communication load. Afterward, selection built upon topological structure. When faced different tasks, that can agents accomplish corresponding task more reasonable agents. Finally, design trapping function The simulation results show self-organize fission sub-swarms cope obstacles disturbance situations, successfully goal protecting parent from experimental prove feasibility effectiveness our proposed algorithm.