Optimization of a 3-RRR Delta Robot for a Desired Workspace with Real-Time Simulation in MATLAB

Eric McCormick, Yanjun Wang, H. Lang
{"title":"Optimization of a 3-RRR Delta Robot for a Desired Workspace with Real-Time Simulation in MATLAB","authors":"Eric McCormick, Yanjun Wang, H. Lang","doi":"10.1109/ICCSE.2019.8845388","DOIUrl":null,"url":null,"abstract":"This paper presents an introduction to 3-RRR Delta Robots, as well as, the workspace associated with this robot’s design configuration. In addition, the inverse kinematic solution of 3-RRR Delta Robots is provided in full detail. Two methods of workspace optimization, Genetic Algorithms (GA) and Maximum Surrounding Workspace (MSW), are explored in order to design a robot which minimizes the amount of unutilized workspace. The results of these two methods are compared to one another, and with a newly proposed method which combines these two approaches. The results produced by these methods demonstrate that this combination of GA and MSW produces the most optimal design for minimizing wasted workspace.","PeriodicalId":351346,"journal":{"name":"2019 14th International Conference on Computer Science & Education (ICCSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 14th International Conference on Computer Science & Education (ICCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2019.8845388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

This paper presents an introduction to 3-RRR Delta Robots, as well as, the workspace associated with this robot’s design configuration. In addition, the inverse kinematic solution of 3-RRR Delta Robots is provided in full detail. Two methods of workspace optimization, Genetic Algorithms (GA) and Maximum Surrounding Workspace (MSW), are explored in order to design a robot which minimizes the amount of unutilized workspace. The results of these two methods are compared to one another, and with a newly proposed method which combines these two approaches. The results produced by these methods demonstrate that this combination of GA and MSW produces the most optimal design for minimizing wasted workspace.
3-RRR Delta机器人理想工作空间的优化与MATLAB实时仿真
本文介绍了3-RRR Delta机器人,以及与该机器人设计构型相关的工作空间。此外,还详细地给出了3-RRR型Delta机器人的运动学逆解。研究了遗传算法(GA)和最大周围工作空间(MSW)两种工作空间优化方法,以设计出最大限度减少未利用工作空间的机器人。对这两种方法的结果进行了比较,并与一种将这两种方法结合起来的新方法进行了比较。这些方法产生的结果表明,遗传算法和都市生活垃圾的结合产生了最小化浪费工作空间的最优设计。
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:604180095
Book学术官方微信