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IJMERR 2022 Vol.11(7): 507-512

Genetic Algorithms for Stable Robot Grasping

Bassem A. Hichri, Francesco B. Giovannini, and Slawomir C. Kedziora
Guala Closures Group – University of Luxembourg, Luxembourg

Abstract—The goal of this paper is to propose an optimal positioning of robotic hand fingers, for a generic 3D object, to ensure stable grasping for an industrial pick and place process. The proposed strategy for optimal positioning based on genetic algorithms is presented. The grasping configuration is determined under several criteria that ensure the object stability. One criterion is based on Static Stability Margin (SSM) that takes into consideration the position of object center of mass in the polygon of support and a second criterion based on the Force Closure Grasping (FCG) taking into consideration the contact forces applied by the robotic hand fingertips. The optimal positioning algorithm results are presented to validate our proposal for a different kind of products.

Index Terms—robotic grasping, genetic algorithms, pick and place, static stability, force closure grasping

Cite: Bassem A. Hichri, Francesco B. Giovannini, and Slawomir C. Kedziora, "Genetic Algorithms for Stable Robot Grasping," International Journal of Mechanical Engineering and Robotics Research, Vol. 11, No. 7, pp. 507-512, July 2022. DOI: 10.18178/ijmerr.11.7.507-512

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.