Development of a Plug-and-Play Infrared Landing System for Multirotor Unmanned Aerial Vehicles
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
Precise landing of multirotor unmanned aerial vehicles (UAVs) in confined, GPS-denied and vision-compromised environments presents a challenge to common autopilot systems. In this work we outline an autonomous infrared (IR) landing system using a ground-based IR radiator, UAV-mounted IR camera, and image processing computer. Previous work has focused on UAV-mounted IR sources for UAV localization, or systems using multiple distributed ground-based IR sources to estimate UAV pose. We experimented with the use of a single ground-based IR radiator to determine the UAV's relative location in three-dimensional space. The outcome of our research significantly simplifies the landing zone setup by requiring only a single IR source, and increases operational flexibility, as the vision-based system adapts to changes in landing zone position. The usefulness of our system is especially demonstrated in vision-compromised applications such as nighttime operations, or in smoky environments observed during forest fires. We also evaluated a high-power IR radiator for future research in the field of outdoor autonomous point-to-point navigation between IR sources where GPS is unavailable.
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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