Planar Grasping Characterization Based on Curvature-Symmetry Fusion

摘要

A new strategy is presented to simplify the real-time determination of grasping points in unknown objects from 2D images. We work with a parallel-jaw gripper and assume point contact with friction, taking into account stability conditions. This strategy is supported by a new tool that permits to establish a supervisor mechanism with the aim to seek grasping points from geometric reasoning on the contours extracted from 2D images captured by the system in execution time. This approach is named “curvature-symmetry fusion” (CSF) and its objective is to integrate curvature and symmetry knowledge in a single data structure to provide the necessary information to predict the 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 the total time for the execution is about 2 or 3 seconds in our inexpensive prototype, making real applications feasible.