EquiMus: Energy-Equivalent Dynamic Modeling and Simulation of Musculoskeletal Robots Driven by Linear Elastic Actuators

Fuente: arXiv
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Autores principales: Zhu, Yinglei, Dong, Xuguang, Wang, Qiyao, Shao, Qi, Xie, Fugui, Liu, Xinjun, Zhao, Huichan
Formato: Preprint
Publicado: 2025
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author Zhu, Yinglei
Dong, Xuguang
Wang, Qiyao
Shao, Qi
Xie, Fugui
Liu, Xinjun
Zhao, Huichan
author_facet Zhu, Yinglei
Dong, Xuguang
Wang, Qiyao
Shao, Qi
Xie, Fugui
Liu, Xinjun
Zhao, Huichan
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2511_07887
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle EquiMus: Energy-Equivalent Dynamic Modeling and Simulation of Musculoskeletal Robots Driven by Linear Elastic Actuators
Zhu, Yinglei
Dong, Xuguang
Wang, Qiyao
Shao, Qi
Xie, Fugui
Liu, Xinjun
Zhao, Huichan
Robotics
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.
title EquiMus: Energy-Equivalent Dynamic Modeling and Simulation of Musculoskeletal Robots Driven by Linear Elastic Actuators
topic Robotics
url https://arxiv.org/abs/2511.07887