A method that enables a robot system to learn how to grasp an object is presented. The method combines an automatic grasp discovery process with a visual recognition technique. When an object is seen the first time, the system experiments with it, seeking a way of grasping and lifting the object by trial and error, using visual information and input from the robot gripper. A discovered grasp configuration is saved along with the object's shape. When the same object is presented again in a different position and orientation, and the system recognizes its shape, the grasp information is retrieved and transformed to match the position and orientation of the object, so it can be picked in the first trial. The approach makes fewer assumptions, and requires less prior information about objects, than nonlearning grasp-determination methods. The presented method was implemented in a system with a robot and a servo-controlled two-finger gripper. Several examples of its operation are reported. >
['Garfield B. Dunn', 'Jakub Segen']
Automatic discovery of robotic grasp configurations