Assistive Upper-Limb Control using a Novel Measure of Human Muscular Manipulability based on Force Envelopes

Abstract

This paper presents a novel approach to measuring upper limb muscular manipulability considering human biomechanics. We address the limitations of classical manipulability measures in robotics when applied to the human body. Our method introduces the concept of a force envelope to estimate the capability of the human arm to exert forces in different directions, considering the contributions of the muscles. To achieve this, we employed a biomechanical model based on Hill’s muscle model, calibrated using both geometric (segmental lengths) and strength-based (muscle activation) approaches to adapt to individual users. Furthermore, we designed a control algorithm that enables a robotic device to assist the user in unfavorable directions, guided by the manipulability measure. By providing a more isotropic response, the robotic device compensates for low manipulability in certain regions of the workspace. We conducted experiments using a haptic robot in admittance mode along the sagittal plane, where a viscous environment acted as a load to hinder human movement throughout the workspace. Our results demonstrate the effectiveness of the proposed method in reducing human effort by assisting in less manipulable directions while leaving high manipulability directions unassisted. Additionally, we successfully verified the superiority in performance of our novel approach against existing methods.