Path Planning and Communication Protocol Design in Multi-UAV Coverage Missions

This paper investigates path planning algorithms and network protocols for multi-UAV collaborative coverage tasks, with the goal of enhancing coordination efficiency in complex missions. While existing research predominantly focuses on single-UAV path planning within known environments, this study addresses the challenge of multi-UAV coverage path planning in unknown environments. A novel algorithm, PL-MUSTC, based on the principles of parallel lines and spanning tree algorithms, is proposed to mitigate issues of redundant coverage along obstacle edges and target area boundaries, thereby significantly reducing task completion time. Additionally, to address communication constraints among UAVs, the MUCTAP application-layer protocol is designed. This protocol ensures that UAVs can effectively accomplish tasks even under limited communication conditions and includes strategies for handling node failures. Simulation results validate the applicability of the PL-MUSTC algorithm and the robustness of the MUCTAP protocol, demonstrating that this approach can effectively enhance task efficiency and coverage in unknown environments.