{"title":"A corrective shared control architecture for human–robot collaborative polishing tasks","authors":"Hao Zhou , Xin Zhang , Jinguo Liu","doi":"10.1016/j.rcim.2024.102876","DOIUrl":null,"url":null,"abstract":"<div><p>Human–robot collaborative polishing can integrate the capabilities of humans and automation to deal with complex polishing tasks. Traditional impedance-control-based human–robot collaboration (HRC) requires operators to physically interact with robots for a good polishing performance, which brings unsafety to operators. To address this issue, a corrective shared control architecture using haptic feedback is proposed in this paper, where the direct force-reflection is used to guarantee the exact human-intention intervention. The proposed control architecture is designed with two layers: (i) the transparency layer in which the direct force-reflection and the human–robot collaborative polishing strategy are implemented; (ii) the passivity layer in which two energy tanks are designed and endowed with master and slave sides and a coupling energy scaling policy is employed to guarantee the passivity of the whole system. Under the proposed architecture, the constant force is adopted to polish normal areas of workpieces, and corrective force based on human intention is applied to deal with unexpected issues. Finally, two groups of experiments are conducted to evaluate the proposed architecture from two aspects: polishing effect and user experience.</p></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"92 ","pages":"Article 102876"},"PeriodicalIF":9.1000,"publicationDate":"2024-09-18","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/S0736584524001637","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
Human–robot collaborative polishing can integrate the capabilities of humans and automation to deal with complex polishing tasks. Traditional impedance-control-based human–robot collaboration (HRC) requires operators to physically interact with robots for a good polishing performance, which brings unsafety to operators. To address this issue, a corrective shared control architecture using haptic feedback is proposed in this paper, where the direct force-reflection is used to guarantee the exact human-intention intervention. The proposed control architecture is designed with two layers: (i) the transparency layer in which the direct force-reflection and the human–robot collaborative polishing strategy are implemented; (ii) the passivity layer in which two energy tanks are designed and endowed with master and slave sides and a coupling energy scaling policy is employed to guarantee the passivity of the whole system. Under the proposed architecture, the constant force is adopted to polish normal areas of workpieces, and corrective force based on human intention is applied to deal with unexpected issues. Finally, two groups of experiments are conducted to evaluate the proposed architecture from two aspects: polishing effect and user experience.
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.