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Record W166715645 · doi:10.22260/isarc2013/0078

Automated Laser Scanner 2D Positioning and Orienting by Method of Triangulateration for Underground Mine Surveying

2013· article· en· W166715645 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of the ... ISARC · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsQueen's University
Fundersnot available
KeywordsLaser scanningScannerComputer scienceComputer visionLaserRemote sensingArtificial intelligenceGeologyOpticsPhysics

Abstract

fetched live from OpenAlex

Automated Laser Scanner 2D Positioning and Orienting by Method of Triangulateration for Underground Mine Surveying Julian V. Simela, Joshua A. Marshall, Laeeque K. Daneshmend Pages 708-717 (2013 Proceedings of the 30th ISARC, Montréal, Canada, ISBN 978-1-62993-294-1, ISSN 2413-5844) Abstract: Conventional methods of underground surveying use theodolites/total stations and 3D laser scanners to obtain information about the underground environment. Current methods of geo-referencing these instruments to a mine reference system include triangulation, trilateration and resection. However, despite technological advancements, surveying procedures have remained slow, laborious and relatively unchanged during the last half-century. Recent innovations in the robotics community have shown that automated mapping of underground mining tunnels can be undertaken using 2D/3D laser scanners. These techniques have the potential to, in turn, improve upon current underground surveying and mapping methods. Automating surveying and mapping using current surveying tools without changing the setting up procedures or removing current constraints, or even changing the type of equipment used, does not change the status quo. The problem of moving from a static, tripod based surveying and mapping system to an unconstrained mobile surveying and mapping system is the subject of this paper. A current challenge for automated mapping is the ability to automatically geo-reference a mobile mapping system to a mine reference system. For a mobile mapping system that uses a horizontally mounted 2D laser scanner to gather data of the underground environment, the challenge of determining its position and orientation within the mine environment is magnified even more. This paper introduces Mobile Automated Scanner Triangulateration (MAST), a technique under development at Queen's that is designed to geo-reference a mobile mapping system to a mine reference system for the purposes of underground mine surveying. MAST quickly and automatically determines scanner 2D position and orientation (azimuth) in a mine reference frame by using minimal human input. Keywords: Underground surveying, mobile robotics, Laser-based positioning DOI: https://doi.org/10.22260/ISARC2013/0078 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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