A Robot Teleoperation Framework for Human Motion Transfer

09/13/2019
by   Miguel Arduengo, et al.
0

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 robot whole-body teleoperation framework for human motion transfer. We propose a general solution to the correspondence problem: a mapping that defines an equivalence between the robot and observed human posture. For achieving real-time teleoperation and effective redundancy resolution, we make use of the whole-body paradigm with an adequate task hierarchy, and present a differential drive control algorithm to the wheeled robot base. To ensure safe physical human-robot interaction, we propose a 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 experiments using the TIAGo robot. Results show effective real-time imitation and dynamic behavior adaptation. This could be an easy way for a non-expert to teach a rough manipulation skill to an assistive robot.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset
Success!
Error Icon An error occurred

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×

Consider DeepAI Pro