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Record W2164694129 · doi:10.1109/cvpr.1988.196219

A new approach to robot orientation by orthogonal lines

2003· article· en· W2164694129 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
FieldComputer Science
TopicImage and Object Detection Techniques
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsRobotVanishing pointCeiling (cloud)Artificial intelligenceOrientation (vector space)Computer visionMetric (unit)GeneralizationComputer sciencePoint (geometry)Image (mathematics)MathematicsGeographyEngineeringGeometryMathematical analysis

Abstract

fetched live from OpenAlex

A novel method is proposed in which the image of three arbitrary orthogonal lines is used to determine the orientation of the robot. Such an image occurs frequently in natural in-house environments such as warehouses, factories, and offices. This method generalizes a previous method where a house-corner was used in the sense that, with the new method, the lines need not intersect at a single point. This generalization seems to be possible because the approach is algebraically simpler. The three-dimensional position of the robot can be derived from the orientation to the robot once the metric of the world is known. Such a metric can be obtained with the usual approach based on any real-world measurements that appear in the image, such as the distance from the camera to the ceiling.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: Methods
Teacher disagreement score0.897
Threshold uncertainty score0.244

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 head0.013
GPT teacher head0.253
Teacher spread0.240 · 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

Citations3
Published2003
Admission routes1
Has abstractyes

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