Abstract:
Contact with the outside world is challenging for robots due to its inherently discontinuous nature β when a foot or hand is touching a surface the forces are completely different than if it is just above the surface. However, most of our computational and analytic tools for planning, learning, and control assume continuous (if not smooth or even linear) systems. Simple models of contact make assumptions (like plasticity and coulomb friction) that are known to not only be wrong physically but also inconsistent. In this talk I will present techniques for overcoming these challenges in order to adapt smooth methods to systems that have changing contact conditions. In particular I will focus on three topics: First, I will present the βSalted Kalman Filterβ for state estimation over hybrid systems. Second, I will present an analysis approach that unifies and extends different strategies for stabilizing and controlling systems through contact. Finally, I will talk about when these hybrid models of contact break down, especially when driving on sand.