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In this paper we address the problem of path planning in an unknownenvironment with an aerial robot. The main goal is to safely follow the plannedtrajectory by avoiding obstacles. The proposed approach is suitable for aerialvehicles equipped with 3D sensors, such as LiDARs. It performs obstacleavoidance in real time and on an on-board computer. We present a novelalgorithm based on the conventional Artifcial Potential Field (APF) thatcorrects the planned trajectory to avoid obstacles. To this end, our modifedalgorithm uses a rotation-based component to avoid local minima. The smoothtrajectory following, achieved with the MPC tracker, allows us to quicklychange and re-plan the UAV trajectory. Comparative experiments in simulationhave shown that our approach solves local minima problems in trajectoryplanning and generates more effcient paths to avoid potential collisions withstatic obstacles compared to the original APF method.

Path Planning with Potential Field-Based Obstacle Avoidance in a 3D Environment by an Unmanned Aerial Vehicle