Precision timing in human-robot interaction

Yamazaki, Akiko; Yamazaki, Kazuo; Kuno, Yoshinori; Burdelski, Matthew; Kawashima, Michie; Kuzuoka, Hideaki

doi:10.1145/1357054.1357077

Cited by 109 publications

(18 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In humans, the study of synchronization skills has fundamental applications in the early diagnosis of social disorders as autism (Delaherche et al, 2013). Regarding synchrony and temporization, Yamazaki et al (2008) analyzed human–human interaction to highlight some transition relevant places (TRPs) corresponding to the moments when a speaker's turn is about to end. Emphasized keywords, unfamiliar and deictic words are other examples of focus points.…”

Section: Discussionmentioning

confidence: 99%

Robot initiative in a team learning task increases the rhythm of interaction but not the perceived engagement

et al. 2014

View full text Add to dashboard Cite

We hypothesize that the initiative of a robot during a collaborative task with a human can influence the pace of interaction, the human response to attention cues, and the perceived engagement. We propose an object learning experiment where the human interacts in a natural way with the humanoid iCub. Through a two-phases scenario, the human teaches the robot about the properties of some objects. We compare the effect of the initiator of the task in the teaching phase (human or robot) on the rhythm of the interaction in the verification phase. We measure the reaction time of the human gaze when responding to attention utterances of the robot. Our experiments show that when the robot is the initiator of the learning task, the pace of interaction is higher and the reaction to attention cues faster. Subjective evaluations suggest that the initiating role of the robot, however, does not affect the perceived engagement. Moreover, subjective and third-person evaluations of the interaction task suggest that the attentive mechanism we implemented in the humanoid robot iCub is able to arouse engagement and make the robot's behavior readable.

show abstract

Section: Discussionmentioning

confidence: 99%

Robot initiative in a team learning task increases the rhythm of interaction but not the perceived engagement

et al. 2014

View full text Add to dashboard Cite

show abstract

“…From previous studies we know that the perception of eye contact with Nao as a looker, is very similar compared to a human looker [43]. Also, several studies have shown that looking back at the participant is interpreted as a turn-taking cue for various agents [44][45][46] including the Nao robot [34,47,48]. In Fig.…”

Section: Gaze: the Head Movementmentioning

confidence: 92%

On the Imitation of Goal Directed Movements of a Humanoid Robot

Bao

Cuijpers

2017

Int J of Soc Robotics

View full text Add to dashboard Cite

Interacting with a social robot should give people a better understanding of the robot's actions and intentions. In terms of human-human interaction (HHI), people can interpret actions of others in an effortless way. However, it is still unclear whether people can do the same with humanoid robots. Imitation (of the robot's actions) provides us with an intuitive means for solving this puzzle, because it is closely related to interpreting another's actions. In the study of human imitation, the theory of goal-directed imitation holds that the imitator tends to imitate the action goals whenever the action goals are salient, otherwise people tend to imitate the action means. We investigated this theory for human robot interaction by manipulating the presence and absence of the goal object when people imitate the robot's pointing gestures. The results showed that the presence of a goal object reduces people's goal errors. Moreover, we found that most people tend to match their action means rather than the goals of the robot's action. To ensure that participants considered the robot as a social agent, we designed a natural interaction task where the turn-taking cue was included: we let the robot look at the human after completing the pointing gesture at varying latencies. As expected, we found that the earlier the robot gazes at people, the shorter the reaction time of people was to start to imitate. Our results show that people are responsive to a robot's social gaze cues, and that they are responsive to the action goals of robots, although not as much as in HHI.

show abstract

“…Yamazaki et al . examined how human participants respond nonverbally to a robot when the robot's head turns and gaze are coordinated to its vocal utterances at transition‐relevant instances . Moreover, Yamazaki et al .…”

Section: Related Workmentioning

confidence: 99%

Social interaction with visitors: mobile guide robots capable of offering a museum tour

Yousuf

Kobayashi

Kuno

et al. 2019

IEEJ Transactions Elec Engng

Self Cite

View full text Add to dashboard Cite

The purpose of this study is to develop a mobile museum guide (MG) robot capable of creating and controlling spatial formations with visitors in different situations. Although much research has already been conducted in the area of nonverbal communication between guide robots and humans, the creation and controlling of spatial formations with multiple visitors is a fundamental function for MG robots that remains unexplored. Drawing upon psychological and sociological studies on the spatial relationships between humans, it is evident that to be effective MG robots should also possess the capability to create and control spatial formations in various situations. A MG robot needs to establish a spatial formation to initiate interaction with the visitors; a spatial formation is a prerequisite before the robot can begin explaining an exhibit. Moreover, the guide robot must be able to identify interested bystanders and invite them into an ongoing explanation session, necessitating a reconfiguring of the spatial formation. Finally, the robot must be able to do this while continuing to explain multiple exhibits in a cohesive fashion. To devise a system capable of meeting these needs, we began by observing and videotaping scenes of actual museum galleries. Based on analyzing these data, we found that MG creates spatial formation with the visitors in a systematic way. We then developed a mobile robot system able to create and control spatial formations while guiding multiple visitors. A particle filter framework is employed to track the visitors' positions and body orientations and the orientations of their heads. We then evaluated the guide robot system in a series of experiments that focused on different situations where a guide robot creates a spatial formation with visitors. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

show abstract

Precision timing in human-robot interaction

Cited by 109 publications

References 23 publications

Robot initiative in a team learning task increases the rhythm of interaction but not the perceived engagement

Robot initiative in a team learning task increases the rhythm of interaction but not the perceived engagement

On the Imitation of Goal Directed Movements of a Humanoid Robot

Social interaction with visitors: mobile guide robots capable of offering a museum tour

Contact Info

Product

Resources

About