  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.
