Human to Robot Whole-Body Motion Transfer
This work addresses the challenge of automating complex manipulation tasks in human-shared environments, providing a method for non-experts to transfer skills to assistive robots, though it appears incremental in its approach.
The authors tackled the problem of transferring human whole-body motion to a mobile robotic manipulator for safe physical interaction, achieving effective real-time imitation and dynamic behavior adaptation in experiments with the TIAGo robot.
Transferring human motion to a mobile robotic manipulator and ensuring safe physical human-robot interaction are crucial steps towards automating complex manipulation tasks in human-shared environments. In this work, we present a novel human to robot whole-body motion transfer framework. We propose a general solution to the correspondence problem, namely a mapping between the observed human posture and the robot one. For achieving real-time imitation and effective redundancy resolution, we use the whole-body control paradigm, proposing a specific task hierarchy, and present a differential drive control algorithm for the wheeled robot base. To ensure safe physical human-robot interaction, we propose a novel variable admittance controller that stably adapts the dynamics of the end-effector to switch between stiff and compliant behaviors. We validate our approach through several real-world experiments with the TIAGo robot. Results show effective real-time imitation and dynamic behavior adaptation. This constitutes an easy way for a non-expert to transfer a manipulation skill to an assistive robot.