Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2022-0757.vid This paper develops a method to model the air flow downwash effect generated by the quadrotor unmanned aerial vehicle (UAV) and its effect on the neighboring UAVs. The downwash model derives the resultant downwash force and torque and takes the UAV attitude into the account. Each UAV is shaped by a virtual structure for collision-free path planning. The shape is modified from a standard spherical body to a proposed cylinder to better minimize downwash impact. A flock-based path planning algorithm and an optimal reciprocal collision avoidance (ORCA) algorithm are implemented and investigated in this study to analyze the downwash effect and the performance of the proposed cylindrical shape UAV model. The downwash model simulation shows how the UAV can be affected when it counters the downwash air flow. A flock-based algorithm and an ORCA algorithm along with the spherical and cylindrical shape UAV models are simulated to demonstrate the cylindrical model can improve path planning performance.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".