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.
翻译:以高效飞行战略避免在未知情况下出现混合障碍是无人驾驶飞行器应用的关键挑战。在本文件中,我们采用了一种技术来区分动态障碍和静态障碍,而静态障碍只有点云输入。然后,提出了一种计算高效的避免障碍运动规划方法,该方法符合改进的相对速度方法。该方法能够避免静态障碍和在同一框架内的动态障碍。对于静态和动态障碍,碰撞检查和运动限制是不同的,它们被有效地纳入一个框架。此外,我们提出了几种技术来改进算法的性能,并处理不同子模块之间的时间差距。拟议方法是实时运行,并在模拟和硬件测试中广泛验证。我们平均单步计算时间不到20米。