MétaCan
Menu
Back to cohort
Record W2146317414 · doi:10.1109/taes.2011.5937255

Sun Sensor Navigation for Planetary Rovers: Theory and Field Testing

2011· article· en· W2146317414 on OpenAlexafffundabout
Paul Furgale, John Enright, Timothy D. Barfoot

Bibliographic record

VenueIEEE Transactions on Aerospace and Electronic Systems · 2011
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
FundersUniversity of Toronto
KeywordsInclinometerHeading (navigation)CompassEphemerisOrientation (vector space)GeodesyComputer scienceReference frameRemote sensingSuiteField (mathematics)Frame (networking)Computer visionAerospace engineeringEngineeringGeologySatelliteGeographyTelecommunications

Abstract

fetched live from OpenAlex

In this paper, we present an experimental study of sun sensing as a rover navigational aid. Algorithms are outlined to determine rover heading in an absolute reference frame. The sensor suite consists of a sun sensor, inclinometer, and clock (as well as ephemeris data). We describe a technique to determine ground-truth orientation in the field (without using a compass) and present a large number of experimental results (both in Toronto and on Devon Island) showing our ability to determine absolute rover heading to within a few degrees.

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)0.006
metaresearch head score (Gemma)0.018
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.205
Teacher spread0.190 · 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

Citations45
Published2011
Admission routes3
Has abstractyes

Explore more

Same venueIEEE Transactions on Aerospace and Electronic SystemsSame topicInertial Sensor and NavigationFrench-language works237,207