<title>Comparison of pose estimation methods of a 3D laser tracking system using triangulation and photogrammetry techniques</title>
Bibliographic record
Abstract
In this paper, we compare the accuracy and resolution of a 3D-laser scanner prototype that tracks in real-time and computes the relative pose of objects in a 3D space. This 3D-laser scanner prototype was specifically developed to study the use of such a sensor for space applications. The main objective of this project is to provide a robust sensor to assist in the assembly of the International Space Station where high tolerance to ambient illumination is paramount. The laser scanner uses triangulation based range data and photogrammetry methods to calculate the relative pose of objects. Range information is used to increase the accuracy of the sensing system and to remove erroneous measurements. Two high-speed galvanometers and a collimated laser beam address individual targets mounted on an object to a resolution corresponding to an equivalent imager of 10000 by 10000 pixels. Knowing the position coordinates of predefined targets on the objects, their relative poses can be computed using either the scanner calibrated 3D coordinates or spatial resection methods.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".