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Record W2058326645 · doi:10.1017/s0263574711000373

Abigaille II: toward the development of a spider-inspired climbing robot

2011· article· en· W2058326645 on OpenAlexafffund
Yasong Li, Ausama Ahmed, Dan Sameoto, Carlo Menon

Bibliographic record

VenueRobotica · 2011
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsUniversity of AlbertaSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaEuropean Space Agency
KeywordsHexapodClimbRobotClimbingGaitTripod (photography)Computer scienceSimulationEngineeringArtificial intelligenceMechanical engineeringAerospace engineeringStructural engineeringPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

SUMMARY This paper presents a novel robotic platform, Abigaille II, designed to climb vertical surfaces using dry adhesion. Abigaille II is a lightweight hexapod prototype actuated by 18 miniaturized motors. The robot's feet consist of adhesive patches, which have microhairs with mushroom-shaped caps fixed on the top of millimeter-scale flexible posts. A pentapedal gait is used to climb flat vertical surfaces as this gait maximizes the number of legs in contact to the surface. Abigaille can however also walk by using other gaits, including the tripod gait.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.059
GPT teacher head0.233
Teacher spread0.174 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations85
Published2011
Admission routes2
Has abstractyes

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