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Record W2086412156 · doi:10.1109/plans.2010.5507301

New method for magnetometers based orientation estimation

2010· article· en· W2086412156 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/ION Position, Location and Navigation Symposium · 2010
Typearticle
Languageen
FieldEngineering
TopicIndoor and Outdoor Localization Technologies
Canadian institutionsUniversity of Calgary
FundersWestern Economic Diversification CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMagnetometerHeading (navigation)CalibrationOrientation (vector space)Computer scienceComputationComputer visionConstant (computer programming)Work (physics)Artificial intelligenceMagnetic fieldAlgorithmMathematicsEngineeringGeodesyPhysicsGeographyStatistics

Abstract

fetched live from OpenAlex

Low cost magnetometers can be used for estimating the orientation with respect to the magnetic North. Although magnetometers work very well in clean magnetic environments like in the outdoors, they are strongly influenced by magnetic perturbations produced by manmade infrastructure in the indoors. Calibration techniques exist that can be used to compensate for these perturbations only if they are constant and associated with the navigation platform itself. But in the indoors, these perturbations vary spatially and render the previously available calibration techniques useless. In this paper, we present a new calibration technique that can be used to compensate for the varying magnetic perturbations on the host platform with better accuracy. Based on this new calibration algorithm, magnetic heading is estimated using multiple magnetometers mounted in a special geometric arrangement. Results show that the new calibration technique and heading computation successfully estimate the cumulative effects of perturbations and gives a better orientation estimate as compared with previous work.

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 score0.837
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.264
Teacher spread0.258 · 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