Intuitive Human-Robot Interaction Through Active 3D Gaze Tracking

Atienza, Rowel; Zelinsky, Alexander

doi:10.1007/11008941_19

Cited by 20 publications

(10 citation statements)

References 13 publications

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“…In contrast, Kirchner et al [22] demonstrated how robot gaze can be effective in targeting an individual recipient out of a group of people for a robot initiated handover. Atienza and Zelinksy [1] augmented handover interactions with gaze, demonstrating a system that allowed a human to request an object for handover by looking at it.…”

Section: Gaze In Human-robot Interactionmentioning

confidence: 99%

Meet me where i'm gazing

Moon

Troniak

Gleeson

et al. 2014

Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction

158

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In this paper we provide empirical evidence that using humanlike gaze cues during human-robot handovers can improve the timing and perceived quality of the handover event. Handovers serve as the foundation of many human-robot tasks. Fluent, legible handover interactions require appropriate nonverbal cues to signal handover intent, location and timing. Inspired by observations of human-human handovers, we implemented gaze behaviors on a PR2 humanoid robot. The robot handed over water bottles to a total of 102 naïve subjects while varying its gaze behaviour: no gaze, gaze designed to elicit shared attention at the handover location, and the shared attention gaze complemented with a turntaking cue. We compared subject perception of and reaction time to the robot-initiated handovers across the three gaze conditions. Results indicate that subjects reach for the offered object significantly earlier when a robot provides a shared attention gaze cue during a handover. We also observed a statistical trend of subjects preferring handovers with turn-taking gaze cues over the other conditions. Our work demonstrates that gaze can play a key role in improving user experience of human-robot handovers, and help make handovers fast and fluent.

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Section: Gaze In Human-robot Interactionmentioning

confidence: 99%

Meet me where i'm gazing

Moon

Troniak

Gleeson

et al. 2014

Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction

158

View full text Add to dashboard Cite

show abstract

“…In the system developed by Atienza and Zelinsky [9] the active vision detects when a person is staring at an object and searches the gaze line to find the object of unknown shape and size to be manipulated by a robot arm.…”

Section: Related Literaturementioning

confidence: 99%

Path generation in virtual reality environment based on gaze analysis

2011

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In this paper the gaze point and gaze line were used for generation of the path of a mobile robot in an immersive virtual environment. The gaze point is considered the intersection of the lines of sight of the two eyes. The experiments were conducted in computer generated virtual reality environment using polarized glasses. The virtual scene was projected in front of the user on a 3D stereoscopic visualization screen. The user was immersed in the environment through polarized glasses and a head-mounted eye tracking device was placed on the head of the user. The floor of the environment was tilted to reproduce the real floor position relative to the user's head when they are seated in a wheelchair. In the first part is presented the evaluation of the accuracy of the estimated gaze point, followed by the results of the experiments on path generation in virtual reality environment based on gaze analysis.

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“…Other fields would benefit from the intuitive and powerful source of data provided by eye tracking, notably in the fields of robotic control [Jan and Bukhari 2009;Atienza and Zelinsky 2003;Lupu and Ungureanu 2013]and assistive technologies [Frisoli et al 2012;Atienza and Zelinsky 2005]. However, these cannot generally be implemented using a fixed gazing target plane given that their target is often in an uncontrolled environment.…”

Section: Introductionmentioning

confidence: 99%

Assessment of accuracy for target detection in 3D-space using eye tracking and computer vision

Leroux

Achiche

Raison

2017

Preprint

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Over the last decade, eye tracking systems have been developed and used in many fields, mostly to identify targets on a screen, i.e. a plane. For novel applications such as the control of robotic devices by the user vision, there is a great interest in developing methods base on eye tracking to identify target points in free three dimensional environments. The objective of this paper is to characterise the accuracy the eye tracking and computer vision combination that was designed recently to overcome many limitations of eye tracking in 3D space. We propose a characterization protocol to assess the behavior of the accuracy of the system over the workspace of a robotic manipulator assistant. Applying this protocol to 33 subjects, we estimated the behavior of the error of the system relatively to the target position on a cylindrical workspace and to the acquisition time. Over our workspace, targets are located on average at 0.84 m and our method shows an accuracy 12.65 times better than the calculation of the 3D point of gaze. With the current accuracy, many potential applications become possible, such as visually controlled robotic assistants in the field of rehabilitation and adaptation engineering.

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Intuitive Human-Robot Interaction Through Active 3D Gaze Tracking

Cited by 20 publications

References 13 publications

Meet me where i'm gazing

Meet me where i'm gazing

Path generation in virtual reality environment based on gaze analysis

Assessment of accuracy for target detection in 3D-space using eye tracking and computer vision

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