位相ベースのマルチ歩容学習によるサンショウウオ型ロボット
Phase-Based Multi-Gait Learning for a Salamander-Like Robot
位相変数と位相カバレッジ報酬を用いて、参照動作なしにサンショウウオ型ロボットへ多様な歩容を獲得させる学習フレームワークを提案し、22種類の歩容を実現した。
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著者: Zhiang Liu, Yang Liu, Yongchun Fang, Xian Guo
分類: cs.RO
原文アブストラクト
Salamander-like robots are designed inspired by the skeletal structure of their biological counterparts. However, existing controllers cannot fully exploit these morphological features and largely rely on predefined patterns or joint trajectories, which prevents the generation of diverse and flexible gaits and limits their applicability in real-world scenarios. In this paper, we propose a phase-based learning framework that enables the robot to acquire a diverse repertoire of gaits without using reference motions. Each body part is controlled by a phase variable capable of forward and backward evolution, with a phase coverage reward to promote the exploration of the leg phase space. Additionally, morphological symmetry of the robot is incorporated via data augmentation, improving sample efficiency and enforcing both motion-level and task-level symmetry in learned behaviors. Extensive experiments show that the robot successfully acquires 22 representative gaits exhibiting both dynamic and symmetric movements, demonstrating the effectiveness of the proposed learning framework.
