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Record W2520406874 · doi:10.1109/tmech.2016.2608862

Input Saturated Visual Servoing for Unmanned Aerial Vehicles

2016· article· en· W2520406874 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2016
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVisual servoingComputer visionArtificial intelligenceComputer scienceController (irrigation)Feature (linguistics)Field of viewKinematicsVisual controlImage (mathematics)

Abstract

fetched live from OpenAlex

This paper presents an input saturated visual servoing controller for a quadrotor unmanned aerial vehicle (UAV). The controller regulates relative pose between the vehicle and a planar horizontal visual target. In order to simplify the control design, the method uses a virtual camera to define a set of image moment features. The image feature kinematics is independent of roll and pitch motion. Since the image feature error is stabilized in the virtual camera, the visual target potentially leaves the real camera's field of view (FoV). To keep the visual target in the camera FoV, an input saturated law is proposed to sufficiently bound the roll and pitch of the vehicle. Furthermore, an adaptive input saturated control law is proposed to ensure positive thrust. Experimental and simulation results are provided to demonstrate controller performance.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.857
Threshold uncertainty score0.778

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 communication0.0000.001
Open science0.0010.000
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 head0.015
GPT teacher head0.281
Teacher spread0.266 · 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