Effects of anticipatory action on human-robot teamwork efficiency, fluency, and perception of team
Proceedings of the ACM/IEEE international conference on Human-robot interaction
Human-robot interaction: a survey
Foundations and Trends in Human-Computer Interaction
Human-robot collaboration in precise positioning of a three-dimensional object
Automatica (Journal of IFAC)
Human-robot collaboration in cellular manufacturing: design and development
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Designing for Situation Awareness: An Approach to User-Centered Design, Second Edition
Designing for Situation Awareness: An Approach to User-Centered Design, Second Edition
Transitional or partnership human and robot collaboration for automotive assembly
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop
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United States Consortium for Automotive Research (USCAR) conducted a concept feasibility study in 2010--2011 to investigate critical requirements to implement fenceless (the long term goal) or minimally fenced (the short term goal) robotics work cells for automotive applications. One output of the study defines the levels of human and robot collaboration and addresses the levels of complexity that drive the probabilities of successful implementation. The development of these definitions was accomplished through interviews with technology providers, observation of current robot system installations, and discussions with automotive manufacturing engineers and robotic technical experts. In this paper, we attempt to categorize robotic systems for low, medium and high levels of human and robot collaboration with current state application examples in automotive body shop, automotive powertrain manufacturing and assembly, as well as in automotive general assembly. We propose potential human and robot collaboration applications in future state where sensors, when closely integrated with robotic systems with greater dynamic response and related new technology advancements, could enable a closer and more dynamic human and robot collaboration. Finally we highlight the assessment of the successful implementation probabilities for the low, medium, and high levels of human and robot collaborative applications.