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arXiv · 2405.13617

Waverider: Leveraging Hierarchical, Multi-Resolution Maps for Efficient and Reactive Obstacle Avoidance

Victor Reijgwart·Michael Pantic·Roland Siegwart·Lionel Ott
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Abstract

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.

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Victor Reijgwart, Michael Pantic, Roland Siegwart, Lionel Ott. 2024-05-22. Waverider: Leveraging Hierarchical, Multi-Resolution Maps for Efficient and Reactive Obstacle Avoidance. https://arxiv.org/abs/2405.13617

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