<title>Development of a compact high-resolution 3D laser range imaging system</title>
Bibliographic record
Abstract
A long-range scanning laser range imaging system designed for 3D imaging applications is presented. The system will be compact, lightweight and low power: ideally suited for remote and robotic applications. It will feature a fully-programmable scanner with a wide field of regard, and a precise time-of-flight laser range measurement system that will provide high-speed, accurate point-cloud data from very short to very long ranges. The potential applications of this technology to be briefly discussed here, both terrestrial and in space, are numerous. They include: robotic vision; autonomous navigation and guidance; mapping and surveying; on-orbit rendezvous and docking; planetary landing; visual geology; and rover navigation. This paper will discuss the physical characteristics of the system as well as the performance of the lidar itself. Test results and some sample imagery will be presented. The paper will also discuss some of the applications for which the system may be suited.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".