Cooperative Robot Manipulators Dynamical Modeling and Control: An Overview

Dynamics Pub Date : 2023-12-11 DOI:10.3390/dynamics3040045
Amin Ghorbanpour
{"title":"Cooperative Robot Manipulators Dynamical Modeling and Control: An Overview","authors":"Amin Ghorbanpour","doi":"10.3390/dynamics3040045","DOIUrl":null,"url":null,"abstract":"Robot manipulators possess the capability to autonomously execute complex sequences of actions. Their proficiency in handling challenging and hazardous tasks has led to their widespread adoption across diverse sectors, including industry, business, household appliances, rehabilitation, and many more. However, certain tasks prove to be challenging for individual robots, primarily due to constraints in their structure and limited degrees of freedom. Cooperative robot manipulators (CRMs) emerge as a compelling solution when dealing with large, heavy, or flexible payloads. The utilization of CRMs offers a host of benefits, including enhanced manipulation performance achieved through the synergy of sensing and actuation capabilities or by tapping into increased redundancy. Numerous techniques have been devised for the control and dynamical modeling of CRMs. Nevertheless, the field continues to present technical challenges and scientific inquiries. To inspire and facilitate further research and development in this realm, this review aims to consolidate the current body of knowledge pertaining to CRMs kinematics, dynamics modeling, and various control methodologies used for payload manipulation via CRMs.","PeriodicalId":507568,"journal":{"name":"Dynamics","volume":"16 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dynamics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/dynamics3040045","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Robot manipulators possess the capability to autonomously execute complex sequences of actions. Their proficiency in handling challenging and hazardous tasks has led to their widespread adoption across diverse sectors, including industry, business, household appliances, rehabilitation, and many more. However, certain tasks prove to be challenging for individual robots, primarily due to constraints in their structure and limited degrees of freedom. Cooperative robot manipulators (CRMs) emerge as a compelling solution when dealing with large, heavy, or flexible payloads. The utilization of CRMs offers a host of benefits, including enhanced manipulation performance achieved through the synergy of sensing and actuation capabilities or by tapping into increased redundancy. Numerous techniques have been devised for the control and dynamical modeling of CRMs. Nevertheless, the field continues to present technical challenges and scientific inquiries. To inspire and facilitate further research and development in this realm, this review aims to consolidate the current body of knowledge pertaining to CRMs kinematics, dynamics modeling, and various control methodologies used for payload manipulation via CRMs.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
合作机器人机械手动态建模与控制:概述
机器人机械手具有自主执行复杂动作序列的能力。它们能够熟练地处理具有挑战性和危险性的任务,因此被广泛应用于工业、商业、家用电器、康复等各个领域。然而,某些任务对单个机器人来说具有挑战性,这主要是由于它们的结构限制和自由度有限。在处理大型、重型或灵活的有效载荷时,协作机器人机械手(CRM)成为一种引人注目的解决方案。使用协同机器人机械手有很多好处,包括通过传感和执行能力的协同作用或利用增加的冗余来提高操纵性能。目前已设计出许多用于有源元件控制和动态建模的技术。然而,这一领域仍面临着技术挑战和科学探索。为了启发和促进这一领域的进一步研究和开发,本综述旨在整合当前与有源元件运动学、动力学建模以及用于通过有源元件操纵有效载荷的各种控制方法有关的知识体系。
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 去求助
来源期刊
CiteScore
1.20
自引率
0.00%
发文量
0
期刊最新文献
A Fluid–Structure Interaction Analysis to Investigate the Influence of Magnetic Fields on Plaque Growth in Stenotic Bifurcated Arteries Vertical and Lateral Dynamics of 4L Freight Bogie Theoretical Model of Structural Phase Transitions in Al-Cu Solid Solutions under Dynamic Loading Using Machine Learning An Optimum Design for a Fast-Response Solenoid Valve: Application to a Limaçon Gas Expander Artificial Intelligence Modeling of the Heterogeneous Gas Quenching Process for Steel Batches Based on Numerical Simulations and Experiments
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1