2020/10/19 by Ruiqi Ni, Teseo Schneider, Ni, Ruiqi +7 · 1 citation
Computer Science · Engineering · #Control and Dynamics of Mobile Robots #FOS: Computer and information sciences #Robotic Path Planning Algorithms #Robotics (cs.RO) #Robotics and Sensor-Based Localization
paper · pdf · doi:10.48550/arxiv.2010.09904
openalex publication_date 2020/10/19 · openalex created_date 2020/10/29 · openalex updated_date 2026/07/28
Generating locally optimal UAV-trajectories is challenging due to the non-convex constraints of collision avoidance and actuation limits. We present the first local, optimization-based UAV-trajectory generator that simultaneously guarantees the validity and asymptotic optimality for known environments. Validity: Given a feasible initial guess, our algorithm guarantees the satisfaction of all constraints throughout the process of optimization. Asymptotic Optimality: We use an asymptotic exact piecewise approximation of the trajectory with an automatically adjustable resolution of its discretization. The trajectory converges under refinement to the first-order stationary point of the exact non-convex programming problem. Our method has additional practical advantages including joint optimality in terms of trajectory and time-allocation, and robustness to challenging environments as demonstrated in our experiments.