Genetic Algorithms for Stable Robot Grasping

B. Hichri, Francesco Giovannini, Sławomir Kędziora
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引用次数: 2

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.
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机器人稳定抓取的遗传算法
本文的目标是针对一般的3D物体提出机械手手指的最佳定位,以确保工业拾取和放置过程中的稳定抓取。提出了基于遗传算法的最优定位策略。抓握结构是在保证物体稳定性的几个标准下确定的。一种准则是基于静态稳定裕度(SSM),考虑了物体质心在支撑多边形中的位置;另一种准则是基于力闭合抓握(FCG),考虑了机器人手指尖施加的接触力。针对不同类型的产品,给出了最优定位算法的结果。
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来源期刊
CiteScore
2.80
自引率
0.00%
发文量
25
期刊介绍: International Journal of Mechanical Engineering and Robotics Research. IJMERR is a scholarly peer-reviewed international scientific journal published bimonthly, focusing on theories, systems, methods, algorithms and applications in mechanical engineering and robotics. It provides a high profile, leading edge forum for academic researchers, industrial professionals, engineers, consultants, managers, educators and policy makers working in the field to contribute and disseminate innovative new work on Mechanical Engineering and Robotics Research.
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