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Record W1968172492 · doi:10.1115/1.1387010

An Input-Output Linearization Approach to the Control of an n-Body Articulated Vehicle

2001· article· en· W1968172492 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

VenueJournal of Dynamic Systems Measurement and Control · 2001
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsPolytechnique Montréal
FundersCentre National de la Recherche Scientifique
KeywordsControl theory (sociology)AxleOffset (computer science)Feedback linearizationLinearizationArticulated vehicleTractorPath (computing)Point (geometry)Computer scienceTracking (education)Control (management)Control engineeringEngineeringMathematicsNonlinear systemAutomotive engineeringArtificial intelligencePhysicsGeometry

Abstract

fetched live from OpenAlex

The problem of path-tracking for an autonomous vehicle composed of a tractor and n−1 trailers with off-axle hitching is considered in this paper. It is shown that an input-output feedback linearization technique can be adopted both in forward and backward maneuvers, leading to the stabilization of the path-tracking offset dynamics about circular paths. The location of the guide-point needs to be selected according to the direction of motion, and, when moving backward, the off-axle distances must be all positive.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.553
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.198
Teacher spread0.189 · 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