Marker-Based Safety Functionality for Human–Robot Collaboration Tasks by Means of Eye-Tracking Glasses DOI Creative Commons
Elisa Masi, Nhu Toan Nguyen, Eugenio Monari

и другие.

Machines, Год журнала: 2025, Номер 13(2), С. 122 - 122

Опубликована: Фев. 6, 2025

Human–robot collaboration (HRC) remains an increasingly growing trend in the robotics research field. Despite widespread usage of collaborative robots on market, several safety issues still need to be addressed develop industry-ready applications exploiting full potential technology. This paper focuses hand-guiding applications, proposing approach based a wearable device reduce risk related operator fatigue or distraction. The methodology aims at ensuring operator’s attention during hand guidance robot end effector order avoid injuries. goal is achieved by detecting region interest (ROI) and checking that gaze kept within this area means pair eye-tracking glasses (Pupil Labs Neon, Berlin, Germany). detection ROI obtained primarily tracking camera glasses, acquiring position predefined ArUco markers, thus obtaining corresponding contour area. In case misdetection one more their estimated through optical flow methodology. performance proposed system initially assessed with motorized test bench simulating rotation head repeatable way then HRC scenario used as study. tests show can effectively identify planar context application real time.

Язык: Английский

Marker-Based Safety Functionality for Human–Robot Collaboration Tasks by Means of Eye-Tracking Glasses DOI Creative Commons
Elisa Masi, Nhu Toan Nguyen, Eugenio Monari

и другие.

Machines, Год журнала: 2025, Номер 13(2), С. 122 - 122

Опубликована: Фев. 6, 2025

Human–robot collaboration (HRC) remains an increasingly growing trend in the robotics research field. Despite widespread usage of collaborative robots on market, several safety issues still need to be addressed develop industry-ready applications exploiting full potential technology. This paper focuses hand-guiding applications, proposing approach based a wearable device reduce risk related operator fatigue or distraction. The methodology aims at ensuring operator’s attention during hand guidance robot end effector order avoid injuries. goal is achieved by detecting region interest (ROI) and checking that gaze kept within this area means pair eye-tracking glasses (Pupil Labs Neon, Berlin, Germany). detection ROI obtained primarily tracking camera glasses, acquiring position predefined ArUco markers, thus obtaining corresponding contour area. In case misdetection one more their estimated through optical flow methodology. performance proposed system initially assessed with motorized test bench simulating rotation head repeatable way then HRC scenario used as study. tests show can effectively identify planar context application real time.

Язык: Английский

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