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For accomplishing a variety of missions in challenging environments, thecapability of navigating with full autonomy while avoiding unexpected obstaclesis the most crucial requirement for UAVs in real applications. In this paper,we proposed such a computationally efficient obstacle avoidance trajectoryplanner that can be used in cluttered unknown environments. Because of thenarrow view field of single depth camera on a UAV, the information of obstaclesaround is quite limited thus the shortest entire path is difficult to achieve.Therefore we focus on the time cost of the trajectory planner and safety ratherthan other factors. This planner is mainly composed of a point cloud processor,a waypoint publisher with Heuristic Angular Search(HAS) method and a motionplanner with minimum acceleration optimization. Furthermore, we propose severaltechniques to enhance safety by making the possibility of finding a feasibletrajectory as big as possible. The proposed approach is implemented to runonboard in real-time and is tested extensively in simulation and the averagecontrol output calculating time of iteration steps is less than 18 ms.

Computationally Efficient Obstacle Avoidance Trajectory Planner for UAVs Based on Heuristic Angular Search Method