Dexterous Gripper for In-Hand Manipulation with Embedded Object Localization Algorithm

Abstract

Since the last decade, thanks to the spreading of the concept of Industry 4.0 and Smart Factory, more and more companies have started to investigate the robotic field looking for reliable solutions aiming at improving the efficiency of assembly lines.Promising technologies are connected to the speeding up of production stages like fast algorithms for object localization, as well as dexterous grippers for manipulation and assembly. Nowadays, most of the solutions for pick and place tasks involve the use of robotic grippers for grasping objects, while robotic manipulators are responsible for their accurate placements. Focusing on the grippers, although their simple structure can be appreciated, it greatly reduces their in-hand manipulation abilities, making unfeasible the twists of grasped objects and their release in a desired pose. As consequence, the efficiency of the pick and place operation is reduced since several adjustments of the robotic arm are required to accomplish the task.In this paper, a novel dexterous gripper coupled with a vision system algorithm for object localization and pose estimation are presented, and their performances in manipulating different objects are discussed. The designed gripper has a symmetrical structure with two finger modules, each one consisting in a couple of linear actuators arranged mutually orthogonal, so the translations in two axis, namely y and z directions, are allowed. As terminal part of each finger there is a revolute joint to whom is attached a fingertip modelled according to the shape of the target objects and easily replaceable. The embedded vision system algorithm adopted estimates position and orientation of the objects on a flat surface, and it coordinates the gripper placement to grasp them. The case study of the handling of a Spanish fan is presented and discussed in details.