🤖 AI Summary
This study addresses the lack of a systematic characterization of intrinsic muscle properties and a unified control framework for musculoskeletal humanoid robots. Leveraging the Kengoro and Musashi platforms, it is the first to categorize muscle structural characteristics into five key types: redundancy, independence, anisotropy, variable moment arms, and nonlinear elasticity. Building upon this taxonomy, the authors develop an integrated motor control system that combines body schema learning, reflexive control, muscle grouping, and adaptive mechanisms. The work not only elucidates the advantages and challenges inherent in musculoskeletal systems for motor control but also establishes a theoretical foundation and practical pathway for the design of highly biomimetic robots.
📝 Abstract
Various musculoskeletal humanoids have been developed so far, and numerous studies on control mechanisms have been conducted to leverage the advantages of their biomimetic bodies. However, there has not been sufficient and unified discussion on the diverse properties inherent in these musculoskeletal structures, nor on how to manage and utilize them. Therefore, this study categorizes and analyzes the characteristics of muscles, as well as their management and utilization methods, based on the various research conducted on the musculoskeletal humanoids we have developed, Kengoro and Musashi. We classify the features of the musculoskeletal structure into five properties: redundancy, independency, anisotropy, variable moment arm, and nonlinear elasticity. We then organize the diverse advantages and disadvantages of musculoskeletal humanoids that arise from the combination of these properties. In particular, we discuss body schema learning and reflex control, along with muscle grouping and body schema adaptation. Also, we describe the implementation of movements through an integrated system and discuss future challenges and prospects.