PEPITA: A Design of Robot Pet Interface for Promoting Interaction

Nuñez, Eleuda; Uchida, Kyohei; Suzuki, Kenji

doi:10.1007/978-3-319-02675-6_55

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…More research is needed to assess how other types of behavioral feedback impact the training interaction and how to correctly implement that demeanor into current machine learning techniques. Notwithstanding, research with non-humanoid robots that communicate with nonverbal cues like light [55,56], sound [57,58] or both [37,59,60] is an ongoing area of study in the field of Social Robotics. The next step of this research aims to identify and design light cues and audio utterances that can improve the experience of training robots.…”

Section: Discussionmentioning

confidence: 99%

Design and Evaluation of a Spherical Robot with Emotion-Like Feedback during Human-Robot Training

Onchi

Lee

2020

Transactions of Japan Society of Kansei Engineering

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While robotic assistants capable of automating many a task are becoming more ubiquitous, the complexity and unfamiliarity of such machines may discourage users from interacting and personalizing their robots. For that reason, the goal of this research is to study how a robot that expresses emotion-like feedback using movement affects the training interaction experience of non-expert users.To that end, a single-eyed spherical robot was developed using a Kansei design approach. A within-subjects experiment, between the robot expressing feedback and a control version that did not, was conducted with participants who had little to no experience interacting with robots. The results showed an increase in arousal when the robot expressed feedback and the overall interaction was considered engaging. Also, a positive correlation between bonding scores and relevance of the task was found. The contributions of this research are toward the development of human-trainable robots with transparent learning behavior.

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Section: Discussionmentioning

confidence: 99%

Design and Evaluation of a Spherical Robot with Emotion-Like Feedback during Human-Robot Training

Onchi

Lee

2020

Transactions of Japan Society of Kansei Engineering

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“…The second part of the questionnaire explored the modalities used by robots to convey affective expressions visually. We compared two categories: facial expressions using mechanical faces (Zeno [32] and Probo [31]) and facial expressions using a display (Buddy [11] and Pepita [58]). Considering we need video stimulus for these items, robots that fall in this category and that had video available to the public were selected.…”

Section: Questionnaire Overviewmentioning

confidence: 99%

“…Then, methods for conveying the robot's affective expressions were evaluated. We compared robots that used mechanical facial expressions (Probo [31] and Zeno [32]) and two robots that used a display to manage the robot's facial expressions (Pepita [58] and Buddy [11]). The results showed that there was a significant difference between Pepita and the other three robots.…”

Section: Exploring the Design Of Pepitamentioning

confidence: 99%

Design of a Huggable Social Robot with Affective Expressions Using Projected Images

Nuñez¹,

Hirokawa²,

Suzuki³

2018

Applied Sciences

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We introduce Pepita, a caricatured huggable robot capable of sensing and conveying affective expressions by means of tangible gesture recognition and projected avatars. This study covers the design criteria, implementation and performance evaluation of the different characteristics of the form and function of this robot. The evaluation involves: (1) the exploratory study of the different features of the device, (2) design and performance evaluation of sensors for affective interaction employing touch, and (3) design and implementation of affective feedback using projected avatars. Results showed that the hug detection worked well for the intended application and the affective expressions made with projected avatars were appropriated for this robot. The questionnaires analyzing users’ perception provide us with insights to guide the future designs of similar interfaces.

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