  We present an adaptive grasping method that finds stable grasps on novel
objects. The main contributions of this paper is in the computation of the
probability of success of grasps in the vicinity of an already applied grasp.
Our method performs grasp adaptions by simulating tactile data for grasps in
the vicinity of the current grasp. The simulated data is used to evaluate
hypothetical grasps and thereby guide us toward better grasps. We demonstrate
the applicability of our method by constructing a system that can plan, apply
and adapt grasps on novel objects. Experiments are conducted on objects from
the YCB object set and the success rate of our method is 88%. Our experiments
show that the application of our grasp adaption method improves grasp stability
significantly.
