High-Speed Obstacle-Avoidance with Agile Fixed-Wing Aircraft
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
Agile fixed-wing aircraft aim to bridge the gap between rotor-craft and conventional fixed-wing aircraft, with the capability of maneuverable and even hovering flight like a rotor-craft, and of efficient long distance flight like a conventional fixed-wing aircraft. Avoiding obstacles in unknown environments is a challenging task with these platforms, as they have complicated dynamics and a limited payload, and they fly at high speeds. In this work, we present an obstacle-avoidance strategy that avoids collisions while steering the aircraft to the goal. The strategy does not rely on a prior map of the environment, or the ability to build a map in real-time, and can be run in real-time on-board the aircraft. We utilize a library of optimal trajectories, both conventional and aerobatic maneuvers, that are solved off-line. A sequence of these trajectories is pieced together to form a collision-free motion plan within the field of view of the depth camera that steers the aircraft towards the goal region. We validate the approach in a high-fidelity simulation environment. The aircraft flies autonomously through a forest-like map to a goal region, using conventional maneuvers such as banked and helical turns, as well as aerobatic maneuvers such as an aggressive turnaround.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it