Fast and reliable obstacle avoidance is an important task for mobile robots. In this work, we propose an efficient reactive system that provides high-quality obstacle avoidance while running at hundreds of hertz with minimal resource usage. Our approach combines wavemap, a hierarchical volumetric map representation, with a novel hierarchical and parallelizable obstacle avoidance algorithm formulated through Riemannian Motion Policies (RMP). Leveraging multi-resolution obstacle avoidance policies, the proposed navigation system facilitates precise, low-latency (36ms), and extremely efficient obstacle avoidance with a very large perceptive radius (30m). We perform extensive statistical evaluations on indoor and outdoor maps, verifying that the proposed system compares favorably to fixed-resolution RMP variants and CHOMP. Finally, the RMP formulation allows the seamless fusion of obstacle avoidance with additional objectives, such as goal-seeking, to obtain a fully-fledged navigation system that is versatile and robust. We deploy the system on a Micro Aerial Vehicle and show how it navigates through an indoor obstacle course. Our complete implementation, called waverider, is made available as open source.

翻译：快速可靠的避障是移动机器人的重要任务。本研究提出一种高效反应式系统，能够在数百赫兹频率下运行并以最小资源消耗提供高质量避障。该方法将分层体素地图表示wavemap与通过黎曼运动策略（RMP）构建的新型分层并行化避障算法相结合。借助多分辨率避障策略，所提出的导航系统能够实现精确、低延迟（36毫秒）且极高效率的大感知半径（30米）避障。我们在室内外地图上进行了广泛的统计评估，验证了该系统相较于固定分辨率RMP变体及CHOMP方法的优越性。最后，RMP框架允许将避障与其他目标（如目标追踪）无缝融合，从而获得功能完备且鲁棒的导航系统。我们将该系统部署于微型飞行器，展示了其在室内障碍场地中的导航能力。我们的完整实现（称为waverider）已作为开源项目发布。