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Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing

Langue : Anglais

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Couverture de l’ouvrage Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing

Proactive Human?Robot Collaboration Toward Human-Centric Smart Manufacturing is driven by an appreciation of manufacturing scenarios where human and robotic agents can understand each other’s actions and conduct mutual-cognitive, predictable, and self-organizing teamwork. Modern factories’ smart manufacturing transformation and the evolution of relationships between humans and robots in manufacturing tasks set the scene for a discussion on the technical fundamentals of state-of-the-art proactive human?robot collaboration; these are further elaborated into the three main steps (i.e., mutual-cognitive and empathic coworking; predictable spatio-temporal collaboration; self-organizing multiagent teamwork) to achieve an advanced form of symbiotic HRC with high-level, dynamic-reasoning teamwork skills. The authors then present a deployment roadmap and several case studies, providing step-by-step guidance for real-world application of these ground-breaking methods which crucially contribute to the maturing of human-centric, sustainable, and resilient production systems. The volume proves to be an invaluable resource that supports understanding and learning for users ranging from upper undergraduate/graduate students and academic researchers to engineering professionals in a variety of industry contexts.

1. Introduction 2. Evolvement of human-robot relationships 3. Fundamentals of Proactive human-robot collaboration 4. Mutual-cognitive and empathic co-work 5. Predictable spatio-temporal collaboration 6. Self-organising multi-agent teamwork 7. Deployment roadmap of Proactive human-robot collaboration 8. Operation modes of industrial Proactive human-robot collaboration 9. Case studies of Proactive human-robot collaboration in manufacturing 10. Conclusions and future perspectives

Shufei Li is currently a Postdoctoral Fellow in the Department of Industrial and Systems Engineering at The Hong Kong Polytechnic University. His research interests are focused on smart manufacturing and intelligent robotics, including human–robot collaboration, embodied AI, and augmented reality. Dr. Li is a member of IEEE and serves as a reviewer for many high-impact, international journals in the manufacturing and industrial engineering field. He has published over ten SCIE-indexed journal articles, won an International Best Conference Paper Award, and multiple domestic Innovation and Entrepreneurship awards.
Pai Zheng is currently an Assistant Professor and Wong Tit Shing Endowed Young Scholar in Smart Robotics in the Department of Industrial and Systems Engineering at The Hong Kong Polytechnic University. His research interests include smart product-service systems, human–robot collaboration, and industrial AI. Dr. Zheng is a senior member of IEEE and CMES, a member of ASME and HKIE, and a research affiliate of CIRP. He serves as the Associate Editor of the Journal of Intelligent Manufacturing and the Journal of Cleaner Production, and is an editorial board member of the Journal of Manufacturing Systems and Advanced Engineering Informatics.
Lihui Wang is a Chair Professor at KTH Royal Institute of Technology, Sweden. His research interests are focused on cyber-physical systems, human–robot collaborations, and adaptive manufacturing systems. He is the Editor-in?Chief of the International Journal of Manufacturing Research, the Journal of Manufacturing Systems, and Robotics and Computer-Integrated Manufacturing. Prof. Wang is a Fellow of the Canadian Academy of Engineering, CIRP, SME, and ASME. He was the President of the North American Manufacturing Research Institution of SME and the Chairman of the Swedish Production Academy.
  • Offers pioneering information on an industry 5.0 topic that has attracted much research interest in recent years
  • Takes advantage of a structured and comprehensive approach to seamlessly combine theory, latest technological developments, and their practical applications
  • Includes actionable methods, while conceptualizing future implications for smart manufacturing