Design of an Intelligent Robotic End Effector Based on Topology Optimization in the Concept of Industry 4.0

Abstract

AbstractOver the past decades, automation industry has seen a major shift from traditional, hard-tooled lines to reconfigurable and reprogrammable robotic cells. Robots have added increasing value to the industry with special focus on robotic arms which enable many repetitive tasks to be carried out with high repeatability, reliability, flexibility, and speed. Grasping, carrying and placement of objects are the basic capabilities of robotic arms. However, with the integration of new technologies the capabilities, of robotic arms can be extended. As such, grippers being an essential component of robots play an important role in many handling tasks since they serve as end-of-arm tools. The aim of this paper is to propose a new end effector design, which is integrated with a sensing system, for improving the adaptivity and flexibility of a robotic cell in comparison with the State-of-the-Market end effector solutions. The proposed design is used to extend this research work and to develop an intelligent end effector based on the implementation of a Machine Vision algorithm, for the recognition of the part, the gripper, and 3D scanning the produced part. The recognition of the part is essential in order for the robot to grasp the object appropriately and facilitate the machining process. The 3D scanning of the part geometry will be utilized for CAD comparison versus the original drawings. Finally, based on the Finite Element Analysis (FEA) and the topology optimization, a reduction of the material used for the 3D printing of the gripper has been reduced by 19.57%.KeywordsFinite element analysisTopology optimizationRobotic end effectorSimulation