2024
DOI: 10.1177/02783649231224053
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Rapid locomotion via reinforcement learning

Gabriel B. Margolis,
Ge Yang,
Kartik Paigwar
et al.

Abstract: Agile maneuvers such as sprinting and high-speed turning in the wild are challenging for legged robots. We present an end-to-end learned controller that achieves record agility for the MIT Mini Cheetah, sustaining speeds up to 3.9 m/s. This system runs and turns fast on natural terrains like grass, ice, and gravel and responds robustly to disturbances. Our controller is a neural network trained in simulation via reinforcement learning and transferred to the real world. The two key components are (i) an adaptiv… Show more

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Cited by 9 publications
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