適応的エネルギー正則化による四足歩行の自律的歩容遷移と省エネルギー化
Adaptive Energy Regularization for Autonomous Gait Transition and Energy-Efficient Quadruped Locomotion
エネルギー消費を最小化する適応的な報酬設計により、四足ロボットが速度に応じて歩容を自律的に切り替え、省エネで安定した移動を実現する手法を提案した。
著者: Boyuan Liang, Lingfeng Sun, Xinghao Zhu, Bike Zhang, Ziyin Xiong, Yixiao Wang, Chenran Li, Koushil Sreenath, Masayoshi Tomizuka
分類: cs.RO
原文アブストラクト
In reinforcement learning for legged robot locomotion, crafting effective reward strategies is crucial. Pre-defined gait patterns and complex reward systems are widely used to stabilize policy training. Drawing from the natural locomotion behaviors of humans and animals, which adapt their gaits to minimize energy consumption, we propose a simplified, energy-centric reward strategy to foster the development of energy-efficient locomotion across various speeds in quadruped robots. By implementing an adaptive energy reward function and adjusting the weights based on velocity, we demonstrate that our approach enables ANYmal-C and Unitree Go1 robots to autonomously select appropriate gaits, such as four-beat walking at lower speeds and trotting at higher speeds, resulting in improved energy efficiency and stable velocity tracking compared to previous methods using complex reward designs and prior gait knowledge. The effectiveness of our policy is validated through simulations in the IsaacGym simulation environment and on real robots, demonstrating its potential to facilitate stable and adaptive locomotion.
