Are You Ready To Collaborate? -- Gaze Detection for Natural Human-Robot Interaction in Industrial Scenarios
Conference Paper
Publication Date:
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
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
human-robot interaction; industry 5.0; gaze estimation; natural behavior; human-centered computing
List of contributors: