Distributed Collaborative Search for Dynamically Moving Targets in Unknown Environments Utilizing Multiple UAVs
Xiaonan Liu, Sheng Li, Zhengrong Xiang · 2024
This paper addresses the challenge of unknown initial positions and motion directions of moving targets by proposing a model predictive control algorithm. The algorithm enhances the number of search targets and reduces estimation errors by constructing various perception maps. It integrates information sharing and fusion techniques with an automatic boundary regression strategy to refine the perception maps, thereby assisting drones in locating targets more efficiently. Simulation results demonstrate that the multiple unmanned aerial vehicles (UAVs) cooperative search strategy presented in this paper outperforms three other search strategies, showing strong adaptability for searching moving targets and verifying the rationality and effectiveness of the proposed approach.