Acquiring robust, force-based assembly skills from human demonstration

Robots have been used successfully in structured settings, where the environment is controlled; this research is inspired by the vision of robots moving beyond structured, controlled settings. The work focuses on the problem of teaching robots forcebased assembly skills from human demonstration. To avoid position dependencies, force-based discrete states (contact formations) are used to describe qualitatively how contact is being made with the environment. Sensorimotor skills are modeled using a hybrid control model, which provides a mechanism for combining continuous low-level force control with higher-level discrete event control. A change in qualitative, discrete state constitutes an event and triggers a new control command to the robot, which moves the assembly toward a new contact formation. In this way, the skill execution is not dependent on absolute position but rather responds to changes in the force-based qualitative state. Experimental results are presented which validate the approach and show how skill acquisition can be accomplished even with an imperfect demonstration.