Trajectory Planning for Unmanned Aerial Vehicle Formation With Attitude Coupling Based on Distributed Model Predictive Control

This paper proposes a distributed model predictive control (DMPC) framework for unmanned aerial vehicle (UAV) formation trajectory planning. Unlike conventional methods relying on simplified point-mass models, this approach explicitly integrates attitude dynamics to enhance tracking precision. The strategy ensures formation integrity and collision avoidance with unknown obstacles in real time. A decoupled geometric control scheme is further employed to regulate the attitude loop independently, significantly improving the planning success rate. The stability of the closed-loop system is established via Lyapunov analysis. Finally, real-time flight experiments validate the effectiveness and robustness of the proposed framework in complex environments.