MétaCan
Menu
Back to cohort
Record W2190168015 · doi:10.13053/cys-19-3-2014

Cockpit Design for First Person View Flight for a Remotely Operated Quadrotor Helicopter

2015· article· en· W2190168015 on OpenAlexaff
Héctor A. Pérez-Sánchez, B. Castillo–Toledo, Alexander G. Loukianov, Luis F. Luque-Vega, Maarouf Saad

Bibliographic record

VenueComputación y Sistemas · 2015
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsÉcole de Technologie Supérieure
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsCockpitHeading (navigation)Computer scienceAeronauticsFlight management systemKey (lock)Graphical user interfaceInterface (matter)Human–computer interactionWorkloadSimulationFlight simulatorSystems engineeringEngineeringAerospace engineeringComputer securityOperating system

Abstract

fetched live from OpenAlex

Recently, technological advances have been focused on the cockpit of modern unmanned aerial vehicles (UAVs) in order to reduce pilot requirements and workload to operate them. First person view (FPV) flight represents a key point when UAVs perform tasks beyond the line of sight. This paper presents the design and implementation of a cockpit for a remotely operated quadrotor. We have developed an intuitive graphical user interface (GUI) for piloting the quadrotor encompassing the most relevant flight instruments as an altimeter, attitude, heading, and ground speed indicators. The GUI is developed using the programming development environment LabVIEW®.

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: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.182
GPT teacher head0.308
Teacher spread0.127 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueComputación y SistemasSame topicRobotic Path Planning AlgorithmsFrench-language works237,207