Dynamic obstacle avoidance for uavs using a fast trajectory planning approach

Real-time path planning is crucial to the dexterity of UAVs when traversing through environments with unknown obstacles. In this paper, we proposed such a real-time planning algorithm that can be used in cluttered environments. The real-time computation is achieved by using dimensionality reduction as well as the rolling optimization. We test the algorithm both in the Gazebo simulation and in two real experiments. The results show that our algorithm can maintain a relatively high speed flight while avoiding obstacles successfully.

Recommended citation: Chen, Han, and Peng Lu. "Real-time identification and avoidance of simultaneous static and dynamic obstacles on point cloud for UAVs navigation." Robotics and Autonomous Systems 154 (2022): 104124. https://www.researchgate.net/profile/Peng-Lu-49/publication/338644159_Dynamic_Obstacle_Avoidance_for_UAVs_Using_a_Fast_Trajectory_Planning_Approach/links/5e212c62299bf1e1fab804af/Dynamic-Obstacle-Avoidance-for-UAVs-Using-a-Fast-Trajectory-Planning-Approach.pdf