  Avoiding hybrid obstacles in unknown scenarios with an efficient flight
strategy is a key challenge for unmanned aerial vehicle applications. In this
paper, we introduce a technique to distinguish dynamic obstacles from static
ones with only point cloud input. Then, a computationally efficient obstacle
avoidance motion planning approach is proposed and it is in line with an
improved relative velocity method. The approach is able to avoid both static
obstacles and dynamic ones in the same framework. For static and dynamic
obstacles, the collision check and motion constraints are different, and they
are integrated into one framework efficiently. In addition, we present several
techniques to improve the algorithm performance and deal with the time gap
between different submodules. The proposed approach is implemented to run
onboard in real-time and validated extensively in simulation and hardware
tests. Our average single step calculating time is less than 20 ms.
