Pushing the envelope: a novel hybrid vehicle design and real-time control concept
Bibliographic record
Abstract
Unmanned aerial vehicles (UAVs) are rapidly finding application in a variety of fields and as they do the demand for improvements in vehicle performance and control also escalates. Though a great deal of research has been directed to the field of unmanned and autonomous aircraft, it has been primarily through the lens of traditional fixed-wing aircraft. A number of applications exist, including a variety of surveillance and remote sensing tasks, for which the ability to hover is a strong requirement. Rotary-wing aircraft such as helicopters can fill this need but have difficulty achieving the required payload and mission duration goals and are sensitive to failures. Airships and lighter-than-air-vehicles have very high persistence capabilities and have low power requirements but are difficult to control at low speed and suffer poor performance in windy conditions. This paper discusses the unique real-time control design for and development of a novel, highly redundant hybrid UAV platform able to demonstrate precision hover and efficient translation for longer mission durations. The vehicle combines the low power-long duration aspects of airships with the manoeuvrability and control of such hovering vehicles as rotary winged aircraft.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".