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Record W2128352910 · doi:10.1145/2317956.2318045

Style by demonstration for interactive robot motion

2012· article· en· W2128352910 on OpenAlexaff
Jeffrey Allen, James E. Young, Daisuke Sakamoto, Takeo Igarashi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicSocial Robot Interaction and HRI
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsHuman–computer interactionRobotStyle (visual arts)Computer scienceDanceAction (physics)Motion (physics)Interface (matter)Task (project management)Focus (optics)PerceptionArtificial intelligencePsychologyVisual artsEngineeringArt

Abstract

fetched live from OpenAlex

As robots continue to enter people's everyday spaces, we argue that it will be increasingly important to consider the robots' movement style as an integral component of their interaction design. That is, aspects of the robot's movement which are not directly related to a task at hand (e.g., pick up a ball) can have a strong impact on how people perceive that action (e.g., aggressively or hesitantly). We call these elements the movement style. We believe that perceptions of this kind of style will be highly dependent on the culture, group, or individual, and so people will need to have the ability to customize their robot. Therefore, in this work we use Style by Demonstration, a style focus on the more-traditional programming by demonstration technique, and present the Puppet Dancer system, an interface for constructing paired and interactive robotic dances. In this paper we detail the Puppet Dancer interface and interaction design, explain our new algorithms for teaching dance by demonstration, and present the results from a formal qualitative study.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.048
GPT teacher head0.399
Teacher spread0.351 · 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; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations13
Published2012
Admission routes1
Has abstractyes

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