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Record W4404553415 · doi:10.1145/3687272.3688310

Research by Design: Mirrly a Humanoid Robot for Child-Robot Interaction

2024· article· en· W4404553415 on OpenAlexaff
Ali Yamini, Ana Djurkovic, Vanessa Italia Anne Hughes, Cory J. Smith, Brandon J. DeHart, Kerstin Dautenhahn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicSocial Robot Interaction and HRI
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHumanoid robotRobotComputer scienceHuman–computer interactionSimulationArtificial intelligence

Abstract

fetched live from OpenAlex

Mirrly is a new humanoid robot designed to facilitate human-robot social interactions, focusing on applications in therapy and education for children. Inspired by the need for engaging and effective interactions, Mirrly’s design incorporates a friendly appearance, articulated expressive face, and multimodal interaction capabilities. A key goal of designing Mirrly was keeping costs low while still retaining affective and expressive qualities of the robot. This paper presents the process of development and design of Mirrly. We also delve into the decisions we made to choose and design hardware, software, and interactions. By comparing existing robots and exploring implications for future research, Mirrly demonstrates the potential for advancing Child-Robot Interaction in many application areas. The open-source nature of Mirrly’s platform further encourages collaboration and innovation in the research community, offering a versatile and potentially impactful platform for a diverse range of applications in human-robot social interactions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.731
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.268
GPT teacher head0.542
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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