Floating visual grasp of unknown objects

Abstract

A new method for fast visual grasp of unknown objects using a camera mounted on a robot in an eye-in-hand configuration is presented. The method is composed of a fast iterative object surface reconstruction algorithm and of a local grasp planner, evolving in a synchronized parallel way. The reconstruction algorithm makes use of images taken by a camera carried by the robot. A reconstruction sphere, virtually placed around the object, is iteratively compressed towards the object visual hull, dragging out the fingers attached to it. Between two steps of the reconstruction process, the planner moves the fingers, floating on the current reconstructed surface, according to suitable quality measures. The fingers keep moving until a local minimum is achieved, then a new object surface estimation provided by the reconstruction process is considered. Quality measures considering both hand and grasp proprieties are adopted. Simulations are presented to show the performance of the proposed algorithm.