© MCube Lab
This research focuses on closing the loop in robotic manipulation, moving towards robots that can better perceive their environment and react to unforeseen situations. Humans effectively process and react to information from visual and tactile sensing, however robots often remain programmed in an open-loop fashion, and struggle to correct their motion based on detected errors.
We begin our work by developing full-state feedback controllers for dynamical systems involving frictional contact interactions. Hybridness and underactuation are key characteristics of these systems that complicate the design of feedback controllers. We design and experimentally validate the controllers on a planar manipulation system where the purpose is to control the motion of a sliding object on a flat surface using a point robotic pusher. The pusher-slider is a simple dynamical system that retains many of the challenges that are typical of robotic manipulation tasks.
We extend this work to partially observable systems, by developing closed-loop tactile controllers for dexterous manipulation with dual-arm robotic palms. We introduce tactile dexterity, an approach to dexterous manipulation that plans for robot/object interactions that render interpretable tactile information for control. Key to this formulation is the decomposition of manipulation plans into sequences of manipulation primitives with simple mechanics and efficient planners.
© MCube Lab