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Safe Sensing for Industrial Human-Robot Collaboration

  • ID: 4768551
  • Book
  • December 2019
  • Region: Global
  • 340 Pages
  • Elsevier Science and Technology
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Safe Sensing for Industrial Human-robot Collaboration discusses the trend for future technology development in this field. Its driving force is the vision that many industrial scenarios will include both human workers with specific expertise and robotic production assistants with their characteristic strengths, combining forces to empower a production facility with superior productivity and flexibility. This book presents professionals with the real requirements for safe sensing in industrial mixed human-robot environments, along with the current availability of safe sensing technologies/products. With its real cases regarding industrial human-robot collaboration, this book will be a great resource for both graduate students and researchers.

  • Provides the guidance and instruction to understand the real requirements and state-of-the art technology as the foundation/basis for industrial human-robot collaboration
  • Focuses on safety sensing and the perception required to ensure that the robot has awareness of the human operator in the robot workspace and can behave in a safe manner
  • Contains the state-of-the-art of safe sensing technology, covering scientific research, prototypes and existing products
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1. Introduction / Background

Part A: Safe sensing requirements for industrial human-robot collaborative 2. Industrial human-robot collaboration: describing what is it defined in the international standards including four collaborative operation types a. General requirements b. Safe-Rated Monitoring Stop c. Hand Guiding d. Speed & Separation Monitoring e. Power and Force Limiting 3. Safe sensing requirements for different collaborative operation types a. Safe sensing for Safe-Rated Monitoring Stop b. Safe sensing for Hand Guiding c. Safe sensing for Speed & Separation Monitoring d. Safe sensing for Power and Force Limiting 4. Use-cases / real industrial collaborative applications

Part B: State-of-the-art safe sensing technology, covering scientific research, prototypes and existing products 5. Force-torque and tactile sensing 6. Capacitive sensing, focusing on proximity sensing 7. Optical sensing, using visible or infrared light for measurement 8. Vision-based sensing, all camera-based solution, especially 3D vision, also including infrared vision 9. Radio wave based sensing, including radar and Wi-Fi 10. Acoustic sensing, including ultrasound

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Ding, Hao
Hao Ding received his B.Sc. degree in automation from the Beijing Institute of Technology, Beijing, China, in 2003, the M.Sc. degree in automation and robotics from Technische Universität Dortmund, Dortmund, Germany, in 2006, and the Ph.D. degree in control and robotics from Universität Kassel, Kassel, Germany, in 2013. From 2007 to 2009, he was a Research Assistant at the Chair of Automatic Control Engineering, Technische Universität München, Germany. Since 2011, he has been with ABB Corporate Research Germany, where he is currently a Principal Scientist and a Project Lead. His research interest include human-robot/machine collaboration, machinery safety, robotic assembly, and factory automation. He is the author of about 50 papers in international/national journals and conferences, and book chapters. He is an independent expert on robotics for evaluation of proposals for the European Commission. Dr. Ding is the recipient of the EU HYCON WP2 Solar Benchmark Exercise Award in 2006 for his work on supervisory control of a solar air-conditioning system. With his work on optimizing motion of robotic manipulators in interaction with human and on optimized task distribution in mixed environments, he received the Best Paper Award at ICIRA in 2011 and the Best Application Paper Award at IEEE CASE in 2014, respectively. In 2011, he was awarded by the Chinese Government as an Outstanding Self-Financed Student Abroad.
Zanchettin, Andrea M.
Andrea Zanchettin was born in Cremona (Italy) in 1983 and received his MSc in Computer Science Engineering in 2008, and his PhD in Information Technology in 2012, both from Politecnico di Milano. During Spring 2010, he spent a research stay at the Department of Automatic Control (Reglerteknik) at Lund University. From January 2012 until February 2014, he has been a temporary research assistant at the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB). From March 2014 to September 2016, he has been a fixed-term assistant professor at DEIB, where he is now a tenure-track assistant professor. In September 2014, Andrea Zanchettin has been the recipient of the Young Author Best Paper Award, sponsored by the Italian Chapter of the IEEE Robotics and Automation Society (I-RAS). Andrea Zanchettin has been member of the IEEE Robotics and Automation Society since 2009, and in 2017 he has been elected as Deputy Chair of I-RAS. Andrea Zanchettin has been co-author of around 50 papers on automatic
control and intelligent human-robot interaction.
Hedelind, Mikael
Mikael Hedelind received his M.Sc. in Computer Science from Mälardalen University, Sweden, in 2004. He received a licentiate engineering degree from the same university in 2006 on the topic of applied industrial robotics. Mikael has worked within industry for over 10 years, working as project leader of industrial R&D projects and coordinator of EU-funded collaboration projects. EU projects include FP7 large-scale integrating project ROSETTA and the H2020 research action SARAFun. Research interests included industrial robot applications, human-robot collaboration, and flexible manufacturing. Mikael currently works as a programme manager at Vinnova, the Swedish governmental agency for innovation systems, department of Industrial Technologies and Innovation Management. Mikael also works as an external expert and evaluator for the European Commission and has been a member of IEEE for ten years.
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