Augmented reality system for operator support in human–robot collaborative assembly

Makris, Sotiris; Karagiannis, Panagiotis; Koukas, Spyridon; Matthaiakis, Aleksandros-Stereos

doi:10.1016/j.cirp.2016.04.038

Cited by 214 publications

(70 citation statements)

References 5 publications

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“…The digital twin can be coupled with additional computational intelligence to handle the diversity of autonomous human actions, or provide cognitive support-e.g., real-time scene assessment, revealing hidden aspects via visualisation or other humaninterpretable feedback-assisting humans in their participation in the production process [21] [22]. Fig.…”

Section: Services To Support Symbiotic Hrcmentioning

confidence: 99%

Human–robot collaborative assembly in cyber-physical production: Classification framework and implementation

et al. 2017

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The production industry is moving towards the next generation of assembly, which is conducted based on safe and reliable robots working in the same workplace alongside with humans. Focusing on assembly tasks, this paper presents a review of human-robot collaboration research and its classification works. Aside from defining key terms and relations, the paper also proposes means of describing human-robot collaboration that can be relied on during detailed elaboration of solutions. A human-robot collaborative assembly system is developed with a novel and comprehensive structure, and a case study is presented to validate the proposed framework.Assembly, man-machine system, human-robot collaboration

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Section: Services To Support Symbiotic Hrcmentioning

confidence: 99%

Human–robot collaborative assembly in cyber-physical production: Classification framework and implementation

et al. 2017

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“…By augmenting the physical environment with virtual objects, AR further enhances information perception and situational awareness, giving the users a live view of the manufacturing environment. AR has been applied in many areas in manufacturing, including assembly and human-robot interaction [3][4][5].…”

Section: Related Workmentioning

confidence: 99%

Haptic and visual augmented reality interface for programming welding robots

Yew

Ong

et al. 2017

Adv. Manuf.

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It is a challenging task for operators to program a remote robot for welding manipulation depending only on the visual information from the remote site. This paper proposes an intuitive user interface for programming welding robots remotely using augmented reality (AR) with haptic feedback. The proposed system uses a depth camera to reconstruct the surfaces of workpieces. A haptic input device is used to allow users to define welding paths along these surfaces. An AR user interface is developed to allow users to visualize and adjust the orientation of the welding torch. Compared with the traditional robotic welding path programming methods which rely on prior CAD models or contact between the robot end-effector and the workpiece, this proposed approach allows for fast and intuitive remote robotic welding path programming without prior knowledge of CAD models of the workpieces. The experimental results show that the proposed approach is a user-friendly interface and can assist users in obtaining an accurate welding path.

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“…In any case, being completely modular and portable, it would be very interesting for the future to consider the exploitation of our perception framework also out of social robotics context. For example, in case of humans and robots collaboration in production lines and other work related tasks [59][60][61]. In these applications, a continuous monitoring of the human psycho-physiological state by the robots can drastically decrease the risk of accidents and maximise productivity.…”

Section: Future Workmentioning

confidence: 99%

A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics

et al. 2017

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Abstract:In this work, we present an unobtrusive and non-invasive perception framework based on the synergy between two main acquisition systems: the Touch-Me Pad, consisting of two electronic patches for physiological signal extraction and processing; and the Scene Analyzer, a visual-auditory perception system specifically designed for the detection of social and emotional cues. It will be explained how the information extracted by this specific kind of framework is particularly suitable for social robotics applications and how the system has been conceived in order to be used in human-robot interaction scenarios.

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Augmented reality system for operator support in human–robot collaborative assembly

Cited by 214 publications

References 5 publications

Human–robot collaborative assembly in cyber-physical production: Classification framework and implementation

Human–robot collaborative assembly in cyber-physical production: Classification framework and implementation

Haptic and visual augmented reality interface for programming welding robots

A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics

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