A Learning Rule-Based Robotics Hand Optimal Force Closure

E. Al-Gallaf
{"title":"A Learning Rule-Based Robotics Hand Optimal Force Closure","authors":"E. Al-Gallaf","doi":"10.1109/CICSyN.2010.57","DOIUrl":null,"url":null,"abstract":"This article presents an intelligent fuzzy rule-based approach for computing optimal set of joints torques, for manipulating a grasped object by a dexterous multi-fingered robotics hand. The intelligent approached followed here, is to let a learning fuzzy system to approximate a nonlinear force formulation for optimal contact forces. This has been achieved via following two major steps: The first was to formulate the optimal fingertips force distribution as a quadratic force optimization problem, hence to generate a large set of data. The second step was to involve a learning fuzzy system (Neuro- Fuzzy System) to learn the nonlinear relations governing fingertips forces (ÂÎ12x1) to hand joint torques (ÂÎ12x1). Simulation results show that the proposed Neuro-Fuzzy network do achieve optimal grasping force in real time.","PeriodicalId":358023,"journal":{"name":"2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICSyN.2010.57","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

This article presents an intelligent fuzzy rule-based approach for computing optimal set of joints torques, for manipulating a grasped object by a dexterous multi-fingered robotics hand. The intelligent approached followed here, is to let a learning fuzzy system to approximate a nonlinear force formulation for optimal contact forces. This has been achieved via following two major steps: The first was to formulate the optimal fingertips force distribution as a quadratic force optimization problem, hence to generate a large set of data. The second step was to involve a learning fuzzy system (Neuro- Fuzzy System) to learn the nonlinear relations governing fingertips forces (ÂÎ12x1) to hand joint torques (ÂÎ12x1). Simulation results show that the proposed Neuro-Fuzzy network do achieve optimal grasping force in real time.
基于学习规则的机器人手部最优力闭合
本文提出了一种基于模糊规则的智能关节力矩计算方法,用于多指灵巧机器人手抓取物体。接下来的智能方法,是让一个学习模糊系统近似一个非线性力的最优接触力公式。这主要通过以下两个步骤来实现:第一步是将最优指尖力分布制定为二次力优化问题,从而产生大量数据。第二步是涉及一个学习模糊系统(神经模糊系统)来学习控制指尖力(ÂÎ12x1)和手关节扭矩(ÂÎ12x1)的非线性关系。仿真结果表明,所提出的神经模糊网络能够实时实现最优抓取力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信