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Record W2525150698 · doi:10.1017/s000192400000350x

Simulation of automatic helicopter deck landings using nature inspired flight control

2010· article· en· W2525150698 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

VenueThe Aeronautical Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCockpitComputer scienceControl theory (sociology)Control (management)SimulationAeronauticsEngineeringAerospace engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Research studies have indicated that the optical flow parameter, time to close tau, is the basis of purposeful control in the animal world, and used by both fixed wing and helicopter pilots during manoeuvring. This parameter is defined as the instantaneous time to close a gap (spatial or force) at the current closing rate. A novel automatic flight control strategy has been developed that makes use of optical flow theory and in particular, the parameter tau. This strategy has been applied to two distinct problems; (1) the landing of a helicopter on a ship and (2) the lateral repositioning of a helicopter. The first is a challenging case because the landing of a helicopter on a ship is one of the most dangerous of all helicopter flight operations. Furthermore, helicopters are often subject to torque oscillations during rapid collective control, which increases pilot workload significantly when operating with low power margins and/or whilst performing tasks that require accurate heave control. The second case demonstrates the generality of the technique. Both automatic manoeuvres were simulated successfully within desired limits, with the novel control strategy creating a ‘natural’, smooth, tau motion.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.385

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 integrity0.0000.001
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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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