A real-time collision avoidance method for redundant dual-arm robots in an open operational environment

IF 9.1 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Yi Wu , Xiaohui Jia , Tiejun Li , Jinyue Liu
{"title":"A real-time collision avoidance method for redundant dual-arm robots in an open operational environment","authors":"Yi Wu ,&nbsp;Xiaohui Jia ,&nbsp;Tiejun Li ,&nbsp;Jinyue Liu","doi":"10.1016/j.rcim.2024.102894","DOIUrl":null,"url":null,"abstract":"<div><div>Due to the structural resemblance of redundant dual-arm robots to human arms, they are widely employed to replace humans in open operational environments. Addressing safety concerns related to the autonomous operations of redundant dual-arm robots in open environments, this paper proposes a real-time collision avoidance method. Firstly, an avoidance direction adjustment algorithm is designed based on the avoidance function method, providing a collision avoidance formulation for the robot control point. Secondly, an obstacle classification algorithm is devised to categorize obstacles into robot body obstacles and end-effector obstacles, and the collision avoidance strategy of redundant dual-arm robots is designed. Subsequently, a collision avoidance penalty factor is introduced based on the proximity between the end-effector and the target point, ensuring the convergence of the joint velocity. Finally, a novel collision avoidance formulation for redundant manipulators is presented, further extended under dual-arm coordinated tasks. Numerical simulations and physical experiments demonstrate that the proposed method can achieve self-collision avoidance for redundant dual-arm robots and dynamic/static obstacle avoidance in dual-arm coordinated tasks, with smooth collision avoidance maneuvers. The research results provide safety guidelines for autonomous operations of redundant dual-arm robots in open operational environments.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102894"},"PeriodicalIF":9.1000,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Computer-integrated Manufacturing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736584524001819","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

Due to the structural resemblance of redundant dual-arm robots to human arms, they are widely employed to replace humans in open operational environments. Addressing safety concerns related to the autonomous operations of redundant dual-arm robots in open environments, this paper proposes a real-time collision avoidance method. Firstly, an avoidance direction adjustment algorithm is designed based on the avoidance function method, providing a collision avoidance formulation for the robot control point. Secondly, an obstacle classification algorithm is devised to categorize obstacles into robot body obstacles and end-effector obstacles, and the collision avoidance strategy of redundant dual-arm robots is designed. Subsequently, a collision avoidance penalty factor is introduced based on the proximity between the end-effector and the target point, ensuring the convergence of the joint velocity. Finally, a novel collision avoidance formulation for redundant manipulators is presented, further extended under dual-arm coordinated tasks. Numerical simulations and physical experiments demonstrate that the proposed method can achieve self-collision avoidance for redundant dual-arm robots and dynamic/static obstacle avoidance in dual-arm coordinated tasks, with smooth collision avoidance maneuvers. The research results provide safety guidelines for autonomous operations of redundant dual-arm robots in open operational environments.
开放操作环境中冗余双臂机器人的实时防撞方法
由于冗余双臂机器人在结构上与人类手臂相似,因此被广泛用于在开放的作业环境中替代人类。针对冗余双臂机器人在开放环境中自主运行的安全问题,本文提出了一种实时避撞方法。首先,基于避让函数法设计了一种避让方向调整算法,为机器人控制点提供了一种避撞公式。其次,设计了一种障碍物分类算法,将障碍物分为机器人本体障碍物和末端执行器障碍物,并设计了冗余双臂机器人的防撞策略。随后,根据末端执行器与目标点之间的距离引入了防撞惩罚因子,确保了关节速度的收敛性。最后,介绍了一种适用于冗余机械手的新型防撞公式,并在双臂协调任务下进一步扩展。数值模拟和物理实验证明,所提出的方法可以实现冗余双臂机器人的自碰撞规避和双臂协调任务中的动态/静态障碍物规避,并具有平滑的碰撞规避机动性。研究成果为冗余双臂机器人在开放操作环境中的自主操作提供了安全指南。
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
Robotics and Computer-integrated Manufacturing
Robotics and Computer-integrated Manufacturing 工程技术-工程:制造
CiteScore
24.10
自引率
13.50%
发文量
160
审稿时长
50 days
期刊介绍: The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.
×
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