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Record W4236352143 · doi:10.1002/rob.20295

Transmission line maintenance robots capable of crossing obstacles: State‐of‐the‐art review and challenges ahead

2009· article· en· W4236352143 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Field Robotics · 2009
Typearticle
Languageen
FieldEngineering
TopicPower Line Inspection Robots
Canadian institutionsHydro-QuébecMcGill University
FundersUniversidade Federal de Minas GeraisHydro-Québec
KeywordsRoboticsMobile robotRobotElectric power transmissionTransmission (telecommunications)Transmission lineState (computer science)Artificial intelligenceLine (geometry)EngineeringState of artPower transmissionComputer scienceSystems engineeringPower (physics)Electrical engineeringBiochemical engineering

Abstract

fetched live from OpenAlex

Abstract Power line inspection and maintenance already benefit from developments in mobile robotics. This paper presents a comprehensive review of the state of the art. It focuses on mobile robots designed to cross obstacles found on a typical transmission line while using the conductor as support for traveling. Promising areas of research and development as well as challenges that remain to be solved are discussed with a view to developing fully autonomous technologies. Maintenance tasks, including inspection and repairs, are identified as high‐value applications in transmission live‐line work. Conclusions are drawn from experience, and the future of mobile robotics applied to transmission line maintenance is discussed. © 2009 Wiley Periodicals, Inc.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.751
Threshold uncertainty score0.354

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 head0.019
GPT teacher head0.247
Teacher spread0.228 · 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