An Bio-Inspired Improved Self-organized Fission-Fusion Control Algorithm for Heterogeneous UAV Swarm

Due to the motion conflicts and environmental interference among entities in heterogeneous unmanned aerial vehicle (UAV) swarms, controlling algorithm for heterogeneous UAV swarms has become a challenging issue in the field of UAVs. However, compared to homogeneous UAV swarms, less attention is given to the research on swarm fission-fusion algorithms for the heterogeneous type with dynamic obstacles. Inspired by the interaction mechanism of starlings and the self-organized swarm motion of heterogeneous UAV swarms, this paper proposes a bio-inspired improved self-organized fission-fusion control algorithm for heterogeneous UAV swarm. First, inspired by the staring interaction mechanism, this paper designs an improved topological interaction mechanism for the heterogeneous swarm. Second, we establish the UAV model and dynamic model of the heterogeneous swarm, consisting fixed-wing UAVs and quadcopters. Then, this paper designs a fission-fusion control algorithm for heterogeneous swarms, achieving self-organizing fission-fusion motion for heterogeneous UAV swarms to track dynamic obstacles. Finally, the effectiveness of the proposed algorithm is validated through simulation experiments.