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Lifeguard UAV System: Scout Quadcopter and Rescue Coaxial Hexacopter with In-Arm Pitch Axis for Extended and Symmetric Dual-Axis Tilt Rotor

2024· article· en· W4402040516 on OpenAlexaff
Angelina Kim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Control Systems
Canadian institutionsBishop's University
Fundersnot available
KeywordsQuadcopterTilt (camera)CoaxialRotor (electric)Dual (grammatical number)Computer scienceAerospace engineeringControl theory (sociology)EngineeringArtificial intelligenceStructural engineeringMechanical engineering

Abstract

fetched live from OpenAlex

An Unmanned Aerial Vehicle (UAV) lifeguard system with scout and rescue UAVs is proposed and prototypes are demonstrated. For dynamic rescue operation, a novel symmetric in-arm pitch rotor tilt axis design is introduced for pitch angle extension by more than 65% over conventional end-arm pitch axis. The rescue UAV implements a coaxial hexacoptor with ±45 degree pitch angle and ±180 degree roll angle for dual-axis rotor tilt at each arm. The extended dual-tilt rotors will be able to adjust thrust to pull a victim to safety adaptively. The rescue UAV folds into itself three times to reduce its diameter by 45% for transportation in passenger vehicles. Its rotor tilting and initial flights were demonstrated. The scout UAV is a quadcopter that deploys an AI-capable mission controller, establishes triple radio channels for control redundancy, and increases payload capacity for a larger battery and a longer scout flight. Multiple autonomous beach flights were conducted to analyze beach hazards through image processing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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)0.0040.002

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 head0.005
GPT teacher head0.197
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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