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Safe human–robot collaboration for industrial settings: a survey.

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Title: Safe human–robot collaboration for industrial settings: a survey.
Authors: Li, Weidong1 (AUTHOR) weidongli@usst.edu.cn, Hu, Yudie2,3 (AUTHOR), Zhou, Yong2 (AUTHOR), Pham, Duc Truong3 (AUTHOR)
Source: Journal of Intelligent Manufacturing. Jun2024, Vol. 35 Issue 5, p2235-2261. 27p.
Subjects: Industrial surveys, Industrial robots, Industrial safety, Industrialism, Safety standards
Abstract: Human–robot collaboration (HRC) plays a pivotal role in today's industry by supporting increasingly customised product development. Via HRC, the strengths of humans and robots can be combined to facilitate collaborative jobs within common workplaces to achieve specific industrial goals. Given the significance of safety assurance in HRC, in this survey paper, an update on standards and implementation approaches presented in the latest literature is given to reflect the state-of-the-art of this prominent research topic. First, an overview of safety standards for industrial robots, collaborative robots, and HRC is provided. Then, a survey of various approaches to HRC safety is conducted from two main perspectives, i.e., pre-collision and post-collision, which are further detailed in the aspects of sensing, prediction, learning, planning/replanning, and compliance control. Major characteristics, pros, cons, and applicability of the approaches are analysed. Finally, challenging issues and prospects for the future development of HRC safety are highlighted to provide recommendations for relevant stakeholders to consider when designing HRC-enabled industrial systems. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Intelligent Manufacturing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Human–robot collaboration (HRC) plays a pivotal role in today's industry by supporting increasingly customised product development. Via HRC, the strengths of humans and robots can be combined to facilitate collaborative jobs within common workplaces to achieve specific industrial goals. Given the significance of safety assurance in HRC, in this survey paper, an update on standards and implementation approaches presented in the latest literature is given to reflect the state-of-the-art of this prominent research topic. First, an overview of safety standards for industrial robots, collaborative robots, and HRC is provided. Then, a survey of various approaches to HRC safety is conducted from two main perspectives, i.e., pre-collision and post-collision, which are further detailed in the aspects of sensing, prediction, learning, planning/replanning, and compliance control. Major characteristics, pros, cons, and applicability of the approaches are analysed. Finally, challenging issues and prospects for the future development of HRC safety are highlighted to provide recommendations for relevant stakeholders to consider when designing HRC-enabled industrial systems. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Intelligent Manufacturing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10845-023-02159-4
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        Text: English
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            – D: 01
              M: 06
              Text: Jun2024
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              Y: 2024
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