Human to robot whole-body motion transfer

Conference Article


IEEE-RAS International Conference on Humanoid Robots (HUMANOIDS)





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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.


cooperative systems, humanoid robots, learning (artificial intelligence), manipulators.

Author keywords

easy teaching, motion transfer

Scientific reference

M. Arduengo, A. Arduengo, A. Colomé, J. Lobo and C. Torras. Human to robot whole-body motion transfer, 2020 IEEE-RAS International Conference on Humanoid Robots, 2021, Munich, Germany (Virtual), pp. 299-305.