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arXiv · 2005.04323

ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skills

Zhaoming Xie·Hung Yu Ling·Nam Hee Kim·Michiel van de Panne
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Abstract

Humans are highly adept at walking in environments with foot placement constraints, including stepping-stone scenarios where the footstep locations are fully constrained. Finding good solutions to stepping-stone locomotion is a longstanding and fundamental challenge for animation and robotics. We present fully learned solutions to this difficult problem using reinforcement learning. We demonstrate the importance of a curriculum for efficient learning and evaluate four possible curriculum choices compared to a non-curriculum baseline. Results are presented for a simulated human character, a realistic bipedal robot simulation and a monster character, in each case producing robust, plausible motions for challenging stepping stone sequences and terrains.

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Zhaoming Xie, Hung Yu Ling, Nam Hee Kim, Michiel van de Panne. 2020-08-30. ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skills. https://arxiv.org/abs/2005.04323

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