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.
@article{arxiv.1704.02603,
title = {Estimating Tactile Data for Adaptive Grasping of Novel Objects},
author = {Emil Hyttinen and Danica Kragic and Renaud Detry},
journal= {arXiv preprint arXiv:1704.02603},
year = {2017}
}
Comments
This paper has been withdrawn by the author due to an incomplete related work section