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Are You Ready To Collaborate? -- Gaze Detection for Natural Human-Robot Interaction in Industrial Scenarios

Contributo in Atti di convegno
Data di Pubblicazione:
2023
Abstract:
Collaborative robots (cobots) are widely used in industrial applications, yet extensive research is still needed to enhance human-robot collaborations and operator experience. A potential approach to improve the collaboration experience involves adapting cobot behavior based on natural cues from the operator. Inspired by the literature on human-human interactions, we conducted a wizardof- oz study to examine whether a gaze towards the cobot can serve as a trigger for initiating joint activities in collaborative sessions. In this study, 37 participants engaged in an assembly task while their gaze behavior was analyzed. We employ a gaze-based attention recognition model to identify when the participants look at the cobot. Our results indicate that in most cases (83.74%), the joint activity is preceded by a gaze towards the cobot. Furthermore, during the entire assembly cycle, the participants tend to look at the cobot mostly around the time of the joint activity. Given the above results, a fully integrated system triggering joint action only when the gaze is directed towards the cobot was piloted with 10 volunteers, of which one characterized by high-functioning Autism Spectrum Disorder. Even though they had never interacted with the robot and did not know about the gaze-based triggering system, most of them successfully collaborated with the cobot and reported a smooth and natural interaction experience. To the best of our knowledge, this is the first study to analyze the natural gaze behavior of participants
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
human-robot interaction; industry 5.0; gaze estimation; natural behavior; human-centered computing
Elenco autori:
Mondellini, Marta; LAVIT NICORA, Matteo; Tauro, Giovanni; Malosio, Matteo
Autori di Ateneo:
MALOSIO MATTEO
MONDELLINI MARTA
TAURO GIOVANNI
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/436562
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