Antagonist Inhibition Control in Redundant Tendon-driven Structures Based on Human Reciprocal Innervation for Wide Range Limb Motion of Musculoskeletal Humanoids
September 01, 2024 Β· Declared Dead Β· π IEEE Robotics and Automation Letters
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Authors
Kento Kawaharazuka, Masaya Kawamura, Shogo Makino, Yuki Asano, Kei Okada, Masayuki Inaba
arXiv ID
2409.00705
Category
cs.RO: Robotics
Citations
32
Venue
IEEE Robotics and Automation Letters
Last Checked
6 months ago
Abstract
The body structure of an anatomically correct tendon-driven musculoskeletal humanoid is complex, and the difference between its geometric model and the actual robot is very large because expressing the complex routes of tendon wires in a geometric model is very difficult. If we move a tendon-driven musculoskeletal humanoid by the tendon wire lengths of the geometric model, unintended muscle tension and slack will emerge. In some cases, this can lead to the wreckage of the actual robot. To solve this problem, we focused on reciprocal innervation in the human nervous system, and then implemented antagonist inhibition control (AIC) based on the reflex. This control makes it possible to avoid unnecessary internal muscle tension and slack of tendon wires caused by model error, and to perform wide range motion safely for a long time. To verify its effectiveness, we applied AIC to the upper limb of the tendon-driven musculoskeletal humanoid, Kengoro, and succeeded in dangling for 14 minutes and doing pull-ups.
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