Design, Manufacturing and Testing of a Long Endurance UAV - Effect of Control Simulations
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">A long endurance high efficiency Unmanned Aerial Vehicle (UAV) is being developed by a group of researchers and students in the Mechanical Engineering Technology program at Algonquin College, Ottawa, ON, Canada. The design is based on a tailless, staggered tandem wing configuration, with a carbon fiber frame and electric propulsion. The developed aircraft has a maximum weight of 12.5 kg, well within the 25 kg limit outlined by Transport Canada for permission-free operation. The UAV was designed to fly missions exceeding 24 hours, performing surveillance and oil pipeline monitoring and inspection, either autonomously or under radio control from a ground station, with medium to high payload capacity.</div><div class="htmlview paragraph">This paper describes the process of designing, manufacturing and testing the developed configuration. The operational requirements are delineated as conceptualized by the development team. A description of the prototype development, including aerodynamics, structural and stability performance, and stability derivatives is included, based on data generated through analytical analysis, simulations in the aerodynamics and stability design software, <i>XFLR5</i>, and testing. The configuration was developed and modeled in the software package <i>SolidWorks</i>, leading to the manufacturing plans for the prototype. As this UAV performs radio controlled and autonomous flights, it makes use of the <i>APM Arduplane</i>, which is an open source hardware and software autopilot package. In order to achieve PID tuning, Hardware in the Loop (HIL) simulations were performed between the autopilot board and two computers simultaneously running the <i>Mission Planner</i> software and the flight simulator <i>X-Plane 10</i> software. A description of this tuning process is provided. The paper concludes with the results of performed flight tests, documenting performance achievements, and an outline of recommendations for further development.</div></div>
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".