EquiMus: 線形弾性アクチュエータ駆動筋骨格ロボットのエネルギー等価動的モデリングとシミュレーション
EquiMus: Energy-Equivalent Dynamic Modeling and Simulation of Musculoskeletal Robots Driven by Linear Elastic Actuators
剛体骨格と柔軟アクチュエータを組み合わせた筋骨格ロボットの動的モデリングを、エネルギー等価性に基づいて行い、MuJoCo上でシミュレーションするフレームワークを提案し、脚ロボットで有効性を検証した。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
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著者: Yinglei Zhu, Xuguang Dong, Qiyao Wang, Qi Shao, Fugui Xie, Xinjun Liu, Huichan Zhao
分類: cs.RO
原文アブストラクト
Dynamic modeling and control are critical for unleashing soft robots' potential, yet remain challenging due to their complex constitutive behaviors and real-world operating conditions. Bio-inspired musculoskeletal robots, which integrate rigid skeletons with soft actuators, combine high load-bearing capacity with inherent flexibility. Although actuation dynamics have been studied through experimental methods and surrogate models, accurate and effective modeling and simulation remain a significant challenge, especially for large-scale hybrid rigid--soft robots with continuously distributed mass, kinematic loops, and diverse motion modes. To address these challenges, we propose EquiMus, an energy-equivalent dynamic modeling framework and MuJoCo-based simulation for musculoskeletal rigid--soft hybrid robots with linear elastic actuators. The equivalence and effectiveness of the proposed approach are validated and examined through both simulations and real-world experiments on a bionic robotic leg. EquiMus further demonstrates its utility for downstream tasks, including controller design and learning-based control strategies.
