A Rectified RRT* with Efficient Obstacles Avoidance Method for UAV in 3D Environment
Omar Mechali, Limei Xu, Mingzhu Wei, Ilyas Benkhaddra, Fan Guo, Abdelkader Senouci · 2019
Our paper presents a static obstacles avoidance and path planning method for Unmanned Aerial Vehicle (UAV) in outdoor three-dimension (3D) environment. We propose a rectified rapidly exploring random tree (RRT*) algorithm where a method is proposed for smoothing and rectifying the final path generated by RRT* in order to reduce the energy consumption during the flight. We also introduce an obstacle avoidance method which allows an efficient free-path collision generation in a complex 3D operating state space. This method ensures that the environment modeling is very close to the reality which allows a high accuracy obstacle avoidance with a secure distance between the UAV and the obstacles edges. Our algorithm was validated through the experiments including the Hardware-in-the-loop simulation (HIL) and real outdoor flights.