  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.
