Research on UAV Path Planning Strategy Integrating Bionic Intelligence and Collaborative Perception

With the rapid development and large-scale application of UAV technology, the intelligent demand for path planning and management has become increasingly prominent. Inspired by bionic intelligence mechanisms and Collaborative Perception technologies, this paper integrates the artificial potential field theory (a typical bionic intelligence method) with the visual monitoring capability of ADS-B technology to propose a bionic intelligence and Collaborative Perception-integrated UAV path planning strategy. This strategy simulates the attraction-repulsion effects of natural force fields and combines real-time airspace data perception from ADS-B to achieve dynamic optimization and cooperative management of UAV paths. In comparative experiments, the one-time success rate of the proposed algorithm is slightly lower than that of traditional algorithms under varying numbers of obstacles, but it significantly outperforms the MUGA, tmuga, and D15 algorithms in terms of obstacle avoidance efficiency and planning time. Multi-UAV swarm simulation experiments further demonstrate that the strategy can effectively plan cooperative paths in complex obstacle environments, verifying the feasibility and superiority of integrating bionic intelligence with Collaborative Perception.