Planar grasping characterization based on curvature-symmetry fusion

A new strategy is presented to simplify the real-time determination of gras ping points in unknown objects from 2D images. We work with a parallel-jaw gripper and assume point contact with friction, taking into account stabili ty conditions. This strategy is supported by a new tool that permits to est ablish a supervisor mechanism with the aim to seek grasping points from geo metric reasoning on the contours extracted from 2D images captured by the s ystem in execution time. This approach is named "curvature-symmetry fusion" (CSF) and its objective is to integrate curvature and symmetry knowledge i n a single data structure to provide the necessary information to predict t he more suitable directions used by a supervisor mechanism described below. These algorithms have been implemented on a SCARA manipulator with one end point mounted camera. Visual feedback was used in the control system and t he total time for the execution is about 2 or 3 seconds in our inexpensive prototype, making real applications feasible.