Development of a Tightly Coupled Vision/GNSS System
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 loose and tight integration of a stereo-vision system with a Global Navigation Satellite System (GNSS) based navigation system. A simplified vehicular dynamic model was chosen and implemented in order to gain maximum advantage from the vision sensor’s information. Data collected in open-sky as well as urban environments was processed in post-mission with the University of Calgary’s GSNRx™ software GNSS receiver. The results include performance measures of the loose and tight integration approaches using high-quality GPS-synchronized computer vision cameras, which are compared to the output of a GNSS-only solution as well as a tactical-grade reference trajectory. More than 20,000 images and 30 minutes of raw GNSS measurements in a dynamic scenario with a total travelled distance of more than 10 km were collected, processed and analyzed, and the resulting errors in the trajectories were compared.
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 | 0.001 | 0.001 |
| 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 | 0.002 | 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