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Record W2169695004 · doi:10.1109/acc.2011.5990812

Inertial measurements Based dynamic attitude estimation and velocity-free attitude stabilization

2011· article· en· W2169695004 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsLakehead UniversityWestern University
Fundersnot available
KeywordsQuaternionInertial frame of referenceAttitude controlAngular velocityControl theory (sociology)Mathematical proofInertial navigation systemComputer scienceControl (management)Inertial measurement unitEstimationMathematicsControl engineeringArtificial intelligenceEngineeringPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

This paper deals with the attitude estimation and control problems for rigid bodies, using inertial vector measurements. First, we revisit the attitude estimation algorithm on SO(3) that has been recently proposed in the literature, and propose some practical extensions and new insightful unit quaternion based proofs. Then, we propose an attitude stabilization control scheme using only inertial vector measurements. The originality of this control strategy stems from the fact that the explicit reconstruction of the attitude as well as the angular velocity measurements are not required anymore.

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 score0.582
Threshold uncertainty score0.473

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 head0.031
GPT teacher head0.225
Teacher spread0.195 · 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

Quick stats

Citations44
Published2011
Admission routes1
Has abstractyes

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