A model-based scooping grasp for the autonomous picking of unknown objects with a two-fingered gripper

Grasping objects used in daily activities is not an easy task for a robot: the diversity of shapes and volumes of objects renders specific grasping methods inefficient. In this paper, we propose a novel model-based scooping grasp for the picking of thin objects lying on a flat surface, which are typically elusive to common grippers and grasping strategies. A robotic work cell composed of a serial arm, a commercially available gripper and a 3D camera overlooking the workspace is used to demonstrate and test the algorithm. Since a commercial gripper is used, the robot is capable of grasping a large variety of objects, in addition to the targeted thin objects. An experiment based on a test set of 80 objects results in an overall grasp success rate of 84%, which demonstrates the potential of the novel scooping grasp to extend the capabilities of existing grippers.