An Improved Wrist Kinematic Model for Human-Robot Interaction

TL;DR

This paper introduces an improved wrist kinematic model that captures dynamic axes and enhances accuracy for human-robot interaction, addressing limitations of traditional models with a novel, real-time estimable approach.

Contribution

The work presents a new wrist kinematic model incorporating dynamic axes and nonlinear regression for real-time estimation, improving accuracy and applicability in robotic systems.

Findings

Dynamic axes exist in carpal rotation.

The model achieves accurate real-time estimation.

Enhanced applicability for human-robot interaction.

Abstract

Human kinematics is of fundamental importance for rehabilitation and assistive robotic systems that physically interact with human. The wrist plays an essential role for dexterous human-robot interaction, but its conventional kinematic model is oversimplified with intrinsic inaccuracies and its biomechanical model is too complicated for robotic applications. In this work, we establish an improved kinematic model of the wrist. In vivo kinematic behavior of the wrist was investigated through noninvasive marker-less optical tracking. Data analysis demonstrated the existence of measurable dynamic axes in carpal rotation, justifying inevitable misalignment between the wrist and robotic representation if using the conventional wrist model. A novel wrist kinematic model was then proposed with rigid body transformation in fusion with a varying prismatic term indicating the dynamic axes location. Accurate and real-time estimation of this term has been achieved through coupled wrist angles with nonlinear regression. The proposed model is not only accurate but also conveniently applicable for translating anatomical behaviors into robotic implementation and functional assessment for precise and dexterous human-robot interaction.