论文标题
在动态环境中的主动意义和避免用于飞行机器人的系统
An Active Sense and Avoid System for Flying Robots in Dynamic Environments
论文作者
论文摘要
本文研究了一种基于活跃的障碍范围的新型障碍范式，用于在动态环境中飞行机器人。我们没有融合多个传感器来扩大视野（FOV），而是引入了一种替代方法，该方法利用带有独立旋转DOF的立体声摄像头积极地感知障碍物。特别是，传感方向是通过多个目标来启发的，包括跟踪动态障碍，观察标题方向以及探索以前看不见的区域。通过感应结果，然后根据实时采样和状态空间中的不确定性碰撞检查计划飞行路径，该检查构成了主动意义并避免（ASAA）系统。模拟和现实世界中的实验表明，该系统可以很好地应对动态障碍和突然的目标方向变化。由于仅利用一个立体声摄像头，因此该系统提供了一种低成本和有效的方法来克服视觉导航中的FOV限制。
This paper investigates a novel active-sensing-based obstacle avoidance paradigm for flying robots in dynamic environments. Instead of fusing multiple sensors to enlarge the field of view (FOV), we introduce an alternative approach that utilizes a stereo camera with an independent rotational DOF to sense the obstacles actively. In particular, the sensing direction is planned heuristically by multiple objectives, including tracking dynamic obstacles, observing the heading direction, and exploring the previously unseen area. With the sensing result, a flight path is then planned based on real-time sampling and uncertainty-aware collision checking in the state space, which constitutes an active sense and avoid (ASAA) system. Experiments in both simulation and the real world demonstrate that this system can well cope with dynamic obstacles and abrupt goal direction changes. Since only one stereo camera is utilized, this system provides a low-cost and effective approach to overcome the FOV limitation in visual navigation.
