Research on Robotic Grasping Object Hardness Perception Based on Tactile Sensing

Abstract

The perception of object hardness is of great significance for robots to perform fine manipulation task. Aiming at the problems of poor system robustness and easy damage to objects caused by complex sensing signals and large object compression in object hardness perception, a method of robotic grasping object hardness perception based on tactile sensing is proposed. Pressure sequences are obtained by the flexible tactile sensors when the two fingers gripper slightly squeezes the object. The pressure sequence signals are then polynomial processed to obtain nonlinear characteristics and then input into the Adaboost algorithm which is based on the decision tree to realize online grasped object hardness perception. The Adaboost algorithm is compared with other algorithms, and the hardness perception experiment for novel objects is carried out. Experimental results show that the proposed method can accurately identify the hardness of different grasped objects.