Compensating Pose Uncertainties through Appropriate Gripper Finger Cutouts

Adam Wolniakowski 1 , Andrej Gams 2 , Lilita Kiforenko 3 , Aljaž Kramberger 2 , Dimitrios Chrysostomou 4 , Ole Madsen 4 , Konstantsin Miatliuk 1 , Henrik Gordon Petersen 3 , Frederik Hagelskjær 3 , Anders Glent Buch 3 , Aleš Ude 4  und Norbert Krüger 3
  • 1 Faculty of Mechanical Engineering, Bialystok University of Technology, 15-351, Białystok, Poland
  • 2 Department for Automation, Biocybernetics and Robotics, Jožef Stefan Institute, , 1000, Ljubljana, Slovenia
  • 3 The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, DK-5230, Odense, Denmark
  • 4 Robotics and Automation Group, Aalborg University, DK-9220, Aalborg East, Denmark


The gripper finger design is a recurring problem in many robotic grasping platforms used in industry. The task of switching the gripper configuration to accommodate for a new batch of objects typically requires engineering expertise, and is a lengthy and costly iterative trial-and-error process. One of the open challenges is the need for the gripper to compensate for uncertainties inherent to the workcell, e.g. due to errors in calibration, inaccurate pose estimation from the vision system, or object deformation. In this paper, we present an analysis of gripper uncertainty compensating capabilities in a sample industrial object grasping scenario for a finger that was designed using an automated simulation-based geometry optimization method (, ). We test the developed gripper with a set of grasps subjected to structured perturbation in a simulation environment and in the real-world setting. We provide a comparison of the data obtained by using both of these approaches. We argue that the strong correspondence observed in results validates the use of dynamic simulation for the gripper finger design and optimization.

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