Design of an Eye-in-Hand Smart Gripper for Visual and Mechanical Adaptation in Grasping

Abstract

With the advancement of robotic technologies, more and more tasks in industrial and commercial applications rely on the use of robots to assist or even replace humans. To fulfill the needs of grasping and handling different objects, the development of a universal grasping device acting as an end-effector to a robotic manipulator has been one of the main robotic research and development focuses. Therefore, this study was aimed at the development of a general robotic gripper with three fingers for adaptive actuation and an eye-in-hand vision system. With the adaptive actuation feature, each finger of the robotic gripper contained multiple degrees of freedom that allowed the finger to change its shape to wrap around an object’s geometry adaptively for stable grasping. With the eye-in-hand configuration in the adaptive gripper, it offered advantages including occlusion avoidance, intuitive teleoperation, imaging from different angles, and simple calibration. This study proposed and integrated a plug-and-play gripper module, controller module, and visual calculation module all in the model smart gripper, of which the gripper was further validated by calibrated experiments. The proposed gripper featured mechanical adaptation and visual servoing adaptivity to achieve 100% gripping success rate when gripping a moving target of any shape that was carried by conveyor belt with moving speed less than 70 mm/s. By integrating mechanical and visual adaptivity, the proposed gripper enabled the inclusion of intelligence in robotic applications and can further be used in smart manufacturing and intelligent robotic applications.