Active Multi-Contact Continuous Tactile Exploration with Gaussian Process Differential Entropy

摘要

In the present work, we propose an active tactile exploration framework to obtain a surface model of an unknown object utilizing multiple contacts simultaneously. To incorporate these multiple contacts, the exploration strategy is based on the differential entropy of the underlying Gaussian process implicit surface model, which formalizes the exploration with multiple contacts within an information theoretic context and additionally allows for nonmyopic multi-step planning. In contrast to many previous approaches, the robot continuously slides along the surface with its end-effectors to gather the tactile stimuli, instead of touching it at discrete locations. This is realized by closely integrating the surface model into the compliant controller framework. Furthermore, we extend our recently proposed sliding based tactile exploration approach to handle non-convex objects. In the experiments, it is shown that multiple contacts simultaneously leads to a more efficient exploration of complex, non-convex objects, not only in terms of time, but also with respect to the total moved distance of all end-effectors. Finally, we demonstrate our methodology with a real PR2 robot that explores an object with both of its arms.