Grasp Planning with Soft Hands using Bounding Box Object Decomposition

In this paper, we present a method to plan grasps for soft hands. Considering that soft hands can easily conform to the shape an the object, with preference to certain types of basic geometries and dimensions, we decompose the object into one type of these geometries, particularly into Minimal Volume Bounding Boxes (MVBBs), which are proved to be efficiently graspable by the hand we use. A set of hand poses are then generated using geometric information extracted from such MVBBs. All hand postures are used in a dynamic simulator of the PISA/IIT Soft Hand and put on a test to evaluate if a proposed hand posture leads to a successful grasp. We show, through a set of numerical simulations, that the probability of success of the hand poses generated with the proposed algorithm is very good and represents an evident improvement with respect to our previous results published in [1].