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Record W2025962723 · doi:10.1109/icra.2012.6225120

Design & Personalization of a Cooperative Carrying Robot Controller

2012· article· en· W2025962723 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsObject (grammar)Controller (irrigation)Task (project management)RobotPersonalizationComputer scienceAdmittanceVariety (cybernetics)Human–computer interactionControl theory (sociology)Control engineeringEngineeringControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

In the near future, as robots become more advanced and affordable, we can envision their use as intelligent assistants in a variety of domains. An exemplar human-robot task identified in many previous works is cooperatively carrying a physically large object. An important task objective is to keep the carried object level. In this work, we propose an admittance-based controller that maintains a level orientation of a cooperatively carried object. The controller raises or lowers its end of the object with a human-like behavior in response to perturbations in the height of the other end of the object (e.g., the end supported by the human user). We also propose a novel tuning procedure, and find that most users are in close agreement about preferring a slightly under-damped controller response, even though they vary in their preferences regarding the speed of the controller's response.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score1.000

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)0.0010.000

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 head0.074
GPT teacher head0.272
Teacher spread0.199 · 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

Quick stats

Citations14
Published2012
Admission routes1
Has abstractyes

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