In this paper, the problem of automating the pre-grasps generation for novel 3d objects has been discussed. The objects represented as cloud of 3D points are split into parts and organized in a tree structure, where parts are approximated by simple box primitives. Applying grasping only on the individual object parts may miss a good grasp which involves a combination of parts. The problem has been addressed by traversing the decomposition tree and checking each node of the tree for possible pre-grasps against a set of conditions. Further, a face mask has been introduced to encode the free and blocked faces of the box primitives. Pre-grasps are generated only for the free faces. Finally, the proposed method implemented on a set twenty-four household objects and toys, where a grasp planner based on object slicing method has been used to compute the contact-level grasp plan.
@article{arxiv.1908.00221,
title = {Automatic pre-grasps generation for unknown 3D objects},
author = {IA Sainul and Sankha Deb and AK Deb},
journal= {arXiv preprint arXiv:1908.00221},
year = {2019}
}