There's No Place Like Home: Visual Teach and Repeat for Emergency Return of Multirotor UAVs During GPS Failure
Why this work is in the frame
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Bibliographic record
Abstract
Redundant navigation systems are critical for safe operation of UAVs in high-risk environments. Since most commercial UAVs almost wholly rely on GPS, jamming, interference, and multi-pathing are real concerns that usually limit their operations to low-risk environments and visual line-of-sight. This letter presents a vision-based route-following system for the autonomous, safe return of UAVs under primary navigation failure such as GPS jamming. Using a Visual Teach and Repeat framework to build a visual map of the environment during an outbound flight, we show the autonomous return of the UAV by visually localizing the live view to this map when a simulated GPS failure occurs, controlling the vehicle to follow the safe outbound path back to the launch point. Using gimbal-stabilized stereo vision and inertial sensing alone, without reliance on external infrastructure, Visual Odometry and localization are achieved at altitudes of 5-25 m and flight speeds up to 55 km/h. We examine the performance of the visual localization algorithm under a variety of conditions and also demonstrate closed-loop autonomy along a complicated 450 m path.
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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