反力制御と歩容制御の分離による動的適応型脚式ロコモーション方策
Dynamic Adaptive Legged Locomotion Policy via Decoupling Reaction Force Control and Gait Control
強化学習による脚式ロコモーションにおいて、支持脚制御と遊脚制御を分離する枠組みを提案し、未知環境へのオンライン適応とsim-to-realギャップの低減を実現した。
詳しい要約
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2. 先行研究と比べてどこがすごい？
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6. 次に読むべき論文は？
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著者: Renjie Wang, Shangke Lyu, Donglin Wang
分類: cs.RO
原文アブストラクト
While Reinforcement Learning (RL) has achieved remarkable progress in legged locomotion control, it often suffers from performance degradation in out-of-distribution (OOD) conditions and discrepancies between the simulation and the real environments. Instead of mainly relying on domain randomization (DR) to best cover the real environments and thereby close the sim-to-real gap and enhance robustness, this work proposes an emerging decoupled framework that acquires fast online adaptation ability and mitigates the sim-to-real problems in unfamiliar environments by isolating stance-leg control and swing-leg control. Various simulation and real-world experiments demonstrate its effectiveness against horizontal force disturbances, uneven terrains, heavy and biased payloads, and sim-to-real gap.
