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Pilot-Assist Landing System for Hover-Capable Fixed-Wing Unmanned Aerial Vehicles in All Flight Regimes

2021· article· en· W3192904095 on OpenAlexaff
Juan Carlos Hernandez Ramirez, Meyer Nahon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsMcGill University
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsFixed wingThrustComputer scienceFlight simulatorController (irrigation)Position (finance)Nonlinear systemFidelityAerospace engineeringOperator (biology)SimulationControl systemWingControl theory (sociology)EngineeringControl (management)

Abstract

fetched live from OpenAlex

This work presents an integrated guidance and control system designed to assist a remote human operator during the landing operation of a hover-capable fixed-wing aircraft. These platforms are capable of both conventional, steady flight and thrust-borne maneuvering, but are challenging to pilot. The proposed pilot-assist system is valid for both flight regimes, including transitions between them, and enables the pilot to intuitively adjust the landing approach, re-position if necessary, and select between conventional and vertical landing. The control system is constructed around a nonlinear SO(3) attitude control system, together with a nonlinear position controller valid for all flight regimes. A guidance algorithm is developed around the control system that translates pilot inputs into references in an intuitive manner. System performance is verified through numerical simulation using a high-fidelity model of an agile fixed-wing aircraft. Results show the proposed system enables a remote operator to safely land the aircraft while retaining high level authority during the procedure.

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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.498

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 head0.018
GPT teacher head0.227
Teacher spread0.209 · 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 teacher head, 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

Citations3
Published2021
Admission routes1
Has abstractyes

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