Topology based model predictive control planner for quadrotor flight in complex environments
Yihang Lin, Huaicheng Yan, Kai Rao, Yunkai Lv, Lingling Lv, Guang‐Jing Song · International Journal of Systems Science · 2025
Unmanned aerial vehicle (UAV) path planning in complex environments presents several challenges, including finding globally optimal paths, ensuring path smoothness, and guaranteeing path feasibility and robustness in varying environments. To address these issues, a topology-based model predictive control (MPC) planner for autonomous flight is proposed. The multiple potential paths with different topological characteristics first generated by analysing the topology of the environment, which providing diverse path options for quadrotors. These generated sets of paths are subsequently optimised by MPC local controller to ensure that the paths can meet the dynamic constraints of the UAV while improving path smoothness and executability. Simulation results show that this method can effectively provide a more robust, safe, and fast path selection for the quadrotor, improve the flight performance of the quadrotor in complex environments, and provide a more efficient solution for UAV navigation tasks.