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Record W2001809775 · doi:10.1109/robio.2012.6490987

A miniature biped wall-climbing robot for inspection of magnetic metal surfaces

2012· article· en· W2001809775 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
TopicSoft Robotics and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsClimbRobotUltrasonic sensorClimbingModular designComputer scienceSimulationEngineeringMechanical engineeringAcousticsArtificial intelligenceStructural engineeringAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

In order to carry out automatic ultrasonic inspection tasks, a miniature biped wall-climbing robot, the so-called MiniBibot-W, has been developed in inspiration of inchworm climbing. Developed with a modular method, this robot consists of six joint modules connected in series as the main body and two electromagnetic adhesion modules at the two ends as the two feet. An ultrasonic probe is mounted to one of the feet. MiniBibot-W thus can not only climb on magnetic surfaces with high mobility, but also perform ultrasonic inspections. In this paper, the development of the robotic system is first presented, and then three climbing gaits and inspection action are introduced. Driving force and adhesion force are analyzed to ensure the safety during climbing and manipulating procedure. A series of experiments are conducted to verify the feasibility and effectiveness of the proposed robotic system and the analysis. A potential application with MiniBibot-W is also demonstrated in ultrasonic detection.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.235

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)0.0000.000

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 head0.017
GPT teacher head0.233
Teacher spread0.216 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

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