Sun Sensor Geolocalization System: Field Testing and Navigational Application
Bibliographic record
Abstract
This thesis presents a sun sensor and inclinometer-based geolocalization system intended for mobile robots. Using only the on-board sensors, combined with solar ephmeris information, terrestrial location and heading estimates are generated. This concept is validated using a post-processing approach, with field test data collected from an instrumentation package developed for this research. Simulations of this system are created to show potential performance with improved hardware. This sun sensor geolocalization system is then applied to an aided wheel odometry-based relative positioning framework. A novel algorithm, Fused Wheel Odometry, is proposed. This algorithm is designed to provide heading information during a mobile robot traversal, followed by an absolute localization update. Simulated data is used to show the improvements of this algorithm over typical aided wheel odometry methodologies. Potential applications of this geolocalization and aided wheel odometry system are explored, showing how this navigational approach could be incorporated into a typical rover mission.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".