Robotic Grasping Using Proximity Sensors for Detecting both Target Object and Surrounding Environment

Abstract

Grasping thin objects on the table is difficult because a slight angular error of the robot hand causes grasping failure. Besides, unintended contact with surface of the table causes not only grasping failure but also malfunction of the robot hand. Therefore, In the grasping, posture adaptation between hand and environment is important for successful grasping. In this paper we present a grasping method for thin object using finger pad and nail proximity sensor which can detect both object and surrounding environment. Because the nail proximity sensor is consisted of photo reflector and TOF proximity sensor, angular and distance error between the hand and the surrounding environment can be detected and corrected during approach to the object. As an experimental result, we show that the proposed method has robustness for environment and can grasp thin object on the table even if angular error exists.