長時間の自己身体イメージ獲得と筋骨格構造の制御への応用
Long-time Self-body Image Acquisition and its Application to the Control of Musculoskeletal Structures
腱駆動型筋骨格ヒューマノイドが長時間にわたり自己身体イメージを学習・維持するシステムを提案し、位置・トルク・可変剛性制御への応用可能性を示した。
著者: Kento Kawaharazuka, Kei Tsuzuki, Shogo Makino, Moritaka Onitsuka, Yuki Asano, Kei Okada, Koji Kawasaki, Masayuki Inaba
分類: cs.RO
原文アブストラクト
The tendon-driven musculoskeletal humanoid has many benefits that human beings have, but the modeling of its complex muscle and bone structures is difficult and conventional model-based controls cannot realize intended movements. Therefore, a learning control mechanism that acquires nonlinear relationships between joint angles, muscle tensions, and muscle lengths from the actual robot is necessary. In this study, we propose a system which runs the learning control mechanism for a long time to keep the self-body image of the musculoskeletal humanoid correct at all times. Also, we show that the musculoskeletal humanoid can conduct position control, torque control, and variable stiffness control using this self-body image. We conduct a long-time self-body image acquisition experiment lasting 3 hours, evaluate variable stiffness control using the self-body image, etc., and discuss the superiority and practicality of the self-body image acquisition of musculoskeletal structures, comprehensively.
