Motion Modification Method of Musculoskeletal Humanoids by Human Teaching Using Muscle-Based Compensation Control

TL;DR

This paper presents a muscle-based compensation control method to modify musculoskeletal humanoid movements by applying external forces, effectively handling model and recognition errors for improved motion accuracy.

Contribution

It introduces a novel control approach that compensates for model inaccuracies in musculoskeletal humanoids using external forces and muscle-based feedback.

Findings

Effective motion modification demonstrated on Musashi humanoid.

Improved control robustness against model and recognition errors.

Validation confirms the method's practical applicability.

Abstract

While musculoskeletal humanoids have the advantages of various biomimetic structures, it is difficult to accurately control the body, which is challenging to model. Although various learning-based control methods have been developed so far, they cannot completely absorb model errors, and recognition errors are also bound to occur. In this paper, we describe a method to modify the movement of the musculoskeletal humanoid by applying external force during the movement, taking advantage of its flexible body. Considering the fact that the joint angles cannot be measured, and that the external force greatly affects the nonlinear elastic element and not the actuator, the modified motion is reproduced by the proposed muscle-based compensation control. This method is applied to a musculoskeletal humanoid, Musashi, and its effectiveness is confirmed.