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Avoiding hybrid obstacles in unknown scenarios with an efficient flightstrategy is a key challenge for unmanned aerial vehicle applications. In thispaper, we introduce a technique to distinguish dynamic obstacles from staticones with only point cloud input. Then, a computationally efficient obstacleavoidance motion planning approach is proposed and it is in line with animproved relative velocity method. The approach is able to avoid both staticobstacles and dynamic ones in the same framework. For static and dynamicobstacles, the collision check and motion constraints are different, and theyare integrated into one framework efficiently. In addition, we present severaltechniques to improve the algorithm performance and deal with the time gapbetween different submodules. The proposed approach is implemented to runonboard in real-time and validated extensively in simulation and hardwaretests. Our average single step calculating time is less than 20 ms.

Identification and Avoidance of Static and Dynamic Obstacles on Point Cloud for UAVs Navigation