Whole-Body Geometric Retargeting for Humanoid Robots

TL;DR

This paper introduces a scalable, intuitive framework for teleoperating various humanoid robots through inverse kinematics-based motion retargeting, validated with multiple robot models and controllers.

Contribution

A novel, scalable motion retargeting approach enabling natural teleoperation of different humanoid robots with minimal system modifications.

Findings

Successful whole-body retargeting across multiple robot models

Effective teleoperation validated with state-of-the-art controllers

Enhanced scalability and natural interaction in humanoid robot control

Abstract

Humanoid robot teleoperation allows humans to integrate their cognitive capabilities with the apparatus to perform tasks that need high strength, manoeuvrability and dexterity. This paper presents a framework for teleoperation of humanoid robots using a novel approach for motion retargeting through inverse kinematics over the robot model. The proposed method enhances scalability for retargeting, i.e., it allows teleoperating different robots by different human users with minimal changes to the proposed system. Our framework enables an intuitive and natural interaction between the human operator and the humanoid robot at the configuration space level. We validate our approach by demonstrating whole-body retargeting with multiple robot models. Furthermore, we present experimental validation through teleoperation experiments using two state-of-the-art whole-body controllers for humanoid robots.