ICUAS'17 Paper Abstract


Paper WeA2.3

Yu, Xiang (Concordia University), Zhou, Xiaobin (Hunan University), Zhang, Youmin (Concordia University)

Collision-Free Trajectory Generation for UAVs Using Markov Decision Process

Scheduled for presentation during the "Path Planning - I" (WeA2), Wednesday, June 14, 2017, 10:40−11:00, Salon AB

2017 International Conference on Unmanned Aircraft Systems, June 13-16, 2017, Miami Marriott Biscayne Bay, Miami, FL,

This information is tentative and subject to change. Compiled on April 12, 2021

Keywords Navigation, Path Planning, See-and-avoid Systems


A collision-free trajectory generation method capable of re-planning the trajectories of an unmanned aerial vehicle (UAV) can increase flight safety and decrease the possibility of mission failure. For this purpose, a Markov decision process (MDP) based algorithm combined with backtracking method, is presented to create a safe trajectory in the case of obstacles. Subsequently, a differential flatness method is adopted to smooth the profile of the rerouted trajectory for satisfying the UAV physical constraints. Simulation results demonstrate that the UAV with the proposed strategy can avoid obstacles and track moving targets in a hostile environment.



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