Uncertainty aware grasping and tactile exploration

The perception of the surrounding world depends on noisy sensors which introduce uncertainty. When we develop algorithms for grasping with robotic hands it is not enough to assume the best estimate of the environment - if there is a measure of uncertainty we need to account for it. This paper presents a control law which augments a grasp controller with the ability to prefer known or unseen regions of an object; this leads to the introduction of two motion primitives: an explorative and exploitative grasp. We integrate this control law in a framework for iterative grasping and implement a tactile exploration scenario. The experimental results confirm that using the notion of uncertainty in the control loop yields better models and does it faster than an uninformed controller.