Eye-safe digital 3-D sensing for space applications
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.
Bibliographic record
Abstract
This paper focuses on the characteristics and performance of an eye-safe laser range scanner (LARS) with short- and medium-range 3-D sensing capabilities for space applications. This versatile LARS is a precision measurement tool that will complement the current Canadian Space Vision System. The major advantages of the LARS over conventional video-based imaging are its ability to operate with sunlight shining directly into the scanner and its immunity to spurious reflections and shadows, which occur frequently in space. Because the LARS is equipped with two high-speed galvanometers to steer the laser beam, any spatial location within the field of view of the camera can be ad-dressed. This versatility enables the LARS to operate in two basic scan pattern modes: (1) variable-scan-resolution mode and (2) raster-scan mode. In the variable-resolution mode, the LARS can search and track targets and geometrical features on objects located within a field of view of 30 by 30 deg and with corresponding range from about 0.5 to 2000 m. The tracking mode can reach a refresh rate of up to 130 Hz. The raster mode is used primarily for the measurement of registered range and intensity information on large stationary objects. It allows, among other things, target-based measurements, feature-based measurements, and surface-reflectance monitoring. The digitizing and modeling of human subjects, cargo payloads, and environments are also possible with the LARS. Examples illustrating its capabilities are presented.
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 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 it