Automated Laser Scanner 2D Positioning and Orienting by Method of Triangulateration for Underground Mine Surveying
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".