论文标题
基于启发式角度搜索方法，无人机的计算有效避免轨迹轨迹计划者
Computationally Efficient Obstacle Avoidance Trajectory Planner for UAVs Based on Heuristic Angular Search Method
论文作者
论文摘要
为了在具有挑战性的环境中完成各种任务，在避免意外障碍的同时导航的能力是对实际应用中无人机的最关键要求。在本文中，我们提出了可以在混乱的未知环境中使用的一种计算有效的避免轨迹轨迹计划者。由于无人机上的单个深度摄像头的视图狭窄，因此周围的障碍信息非常有限，因此很难实现整个路径。因此，我们专注于轨迹规划师和安全性的时间成本，而不是其他因素。该规划师主要由点云处理器组成，该点云处理器是具有启发式角搜索（HAS）方法的Waypoint Publisher和具有最低加速度优化的运动计划器。此外，我们提出了几种技术来通过发现尽可能大的可行轨迹来提高安全性。提出的方法是实现的，以实时运行，并在模拟中进行了广泛的测试，并且平均控制输出计算迭代步骤的时间小于18 ms。
For accomplishing a variety of missions in challenging environments, the capability of navigating with full autonomy while avoiding unexpected obstacles is the most crucial requirement for UAVs in real applications. In this paper, we proposed such a computationally efficient obstacle avoidance trajectory planner that can be used in cluttered unknown environments. Because of the narrow view field of single depth camera on a UAV, the information of obstacles around 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 rather than other factors. This planner is mainly composed of a point cloud processor, a waypoint publisher with Heuristic Angular Search(HAS) method and a motion planner with minimum acceleration optimization. Furthermore, we propose several techniques to enhance safety by making the possibility of finding a feasible trajectory as big as possible. The proposed approach is implemented to run onboard in real-time and is tested extensively in simulation and the average control output calculating time of iteration steps is less than 18 ms.
