Home /Research /Visuotactile Feedback Parallel Gripper for Robotic Adaptive Grasping
MANIPULATION

Visuotactile Feedback Parallel Gripper for Robotic Adaptive Grasping

Boyue Zhang, Shaowei Cui, Chaofan Zhang, Jingyi Hu, Shuo Wang

Year
2022
Citations
2

Abstract

In robot grasp and dexterous manipulation tasks, tactile sensing is important for the control adjustment of the manipulator. In this paper, we present a novel low-cost parallel gripper with high-resolution tactile sensing, named the GelStereo Gripper. Furthermore, an adaptive grasp strategy is proposed to endow the gripper with tactile-feedback grasp stability-maintaining ability. We install the gripper on our robot platform and conduct various grasp experiments by utilizing proposed control methods. Experimental results verify the reliability of the GelStereo gripper and also prove the effectiveness of the proposed strategy for experimental objects with different features.

Keywords

GRASPGrippersComputer scienceTactile sensorRobotReliability (semiconductor)Artificial intelligenceRobot manipulatorControl engineeringStability (learning theory)

Related papers

Browse all MANIPULATION papers