I Can Help You

Yasumatsu, Yuuki; Sono, Taichi; Hasegawa, Kazuo; Imai, Michita

doi:10.1145/3029798.3038305

Cited by 9 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This would explain the low number of studies with children of this age. Recent reviews on the interactions between neuro-typical children and a robot (Jamet et al, 2018;Neumann, 2020;van Straten et al, 2020) indicate that only one study was conducted using NAO and a group of children from 2 to 8 years-old (Yasumatsu et al, 2017). The few other studies conducted on 2 years-old either used the tiny humanoid robot QRIO that is smaller than a 2 years-old child (Tanaka et al, 2007), the iRobiQ robot that looks more like a toy (Hsiao et al, 2015), or robots specifically designed to be enjoyed by young children like the stuffed dragon robot Dragonbot (Kory Westlund et al, 2017) and the RUBI-4 (Movellan et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

“…It was shown that children as young as two can be susceptible to the conversational violations of a robot (Ferrier et al, 2000). Recent studies (Yasumatsu et al, 2017;Martin et al, 2020a,b) also showed that the natural and spontaneous propensity of young children to try being useful extends to humanoid robots seeming to be in difficulty. It seems that 3 years-old children assign mental states to a robot (Di Dio et al, 2018Marchetti et al, 2018).…”

Section: The Robot-pupil Solutionmentioning

confidence: 99%

See 1 more Smart Citation

Pragmatics in the False-Belief Task: Let the Robot Ask the Question!

et al. 2020

View full text Add to dashboard Cite

The poor performances of typically developing children younger than 4 in the first-order false-belief task “Maxi and the chocolate” is analyzed from the perspective of conversational pragmatics. An ambiguous question asked by an adult experimenter (perceived as a teacher) can receive different interpretations based on a search for relevance, by which children according to their age attribute different intentions to the questioner, within the limits of their own meta-cognitive knowledge. The adult experimenter tells the child the following story of object-transfer: “Maxi puts his chocolate into the green cupboard before going out to play. In his absence, his mother moves the chocolate from the green cupboard to the blue one.” The child must then predict where Maxi will pick up the chocolate when he returns. To the child, the question from an adult (a knowledgeable person) may seem surprising and can be understood as a question of his own knowledge of the world, rather than on Maxi's mental representations. In our study, without any modification of the initial task, we disambiguate the context of the question by (1) replacing the adult experimenter with a humanoid robot presented as “ignorant” and “slow” but trying to learn and (2) placing the child in the role of a “mentor” (the knowledgeable person). Sixty-two typical children of 3 years-old completed the first-order false belief task “Maxi and the chocolate,” either with a human or with a robot. Results revealed a significantly higher success rate in the robot condition than in the human condition. Thus, young children seem to fail because of the pragmatic difficulty of the first-order task, which causes a difference of interpretation between the young child and the experimenter.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: The Robot-pupil Solutionmentioning

confidence: 99%

Pragmatics in the False-Belief Task: Let the Robot Ask the Question!

et al. 2020

View full text Add to dashboard Cite

show abstract

Child–Robot Relationship Formation: A Narrative Review of Empirical Research

Straten

Peter

Kühne

2019

Int J of Soc Robotics

103

View full text Add to dashboard Cite

This narrative review aimed to elucidate which robot-related characteristics predict relationship formation between typically-developing children and social robots in terms of closeness and trust. Moreover, we wanted to know to what extent relationship formation can be explained by children's experiential and cognitive states during interaction with a robot. We reviewed 86 journal articles and conference proceedings published between 2000 and 2017. In terms of predictors, robots' responsiveness and role, as well as strategic and emotional interaction between robot and child, increased closeness between the child and the robot. Findings about whether robot features predict children's trust in robots were inconsistent. In terms of children's experiential and cognitive states during interaction with a robot, robot characteristics and interaction styles were associated with two experiential states: engagement and enjoyment/liking. The literature hardly addressed the impact of experiential and cognitive states on closeness and trust. Comparisons of children's interactions with robots, adults, and objects showed that robots are perceived as neither animate nor inanimate, and that they are entities with whom children will likely form social relationships. Younger children experienced more enjoyment, were less sensitive to a robot's interaction style, and were more prone to anthropomorphic tendencies and effects than older children. Tailoring a robot's sex to that of a child mainly appealed to boys.

show abstract

Help-Estimator: Robot Requests for Help from Humans by Estimating a Person’s Subjective Time

Kimoto

Yasumatsu

Imai

2021

Int J of Soc Robotics

Self Cite

View full text Add to dashboard Cite

In human-robot cooperation, it is effective for a robot to ask a human partner for help to reduce the time required for a task. However, the person might not be able to help the robot if she or he is engaged in something else. In this study, we focused on the person's subjective estimation of the time for a task and investigated its effect on the likelihood of agreeing to help the robot. For this purpose, we developed a Help-Estimator system that decides whether the robot should request help by considering the required time for both the person and the robot to finish their tasks. We conducted an experiment to evaluate such help requests that incorporate the human's subjective time estimation for a task. We found that appropriate timing for requesting help, as estimated from the person's viewpoint, increases the likelihood of the person helping the robot and improves the person's impression of the robot as a partner.

show abstract

I Can Help You

Cited by 9 publications

References 3 publications

Pragmatics in the False-Belief Task: Let the Robot Ask the Question!

Pragmatics in the False-Belief Task: Let the Robot Ask the Question!

Child–Robot Relationship Formation: A Narrative Review of Empirical Research

Help-Estimator: Robot Requests for Help from Humans by Estimating a Person’s Subjective Time

Contact Info

Product

Resources

About