AquaFly Project: Autonomous Multi-Drone Water Sampling with a Payload Deployment and Retraction Mechanism
Bibliographic record
Abstract
The AquaFly project is a research collaboration between the Flight Systems and Control (FSC) Laboratory at the University of Toronto Institute for Aerospace Studies (UTIAS) and Queen’s University Biology Department in Canada to offer a fast, reliable, and efficient method of sampling water bodies by using autonomous Unmanned Aerial Systems (UAS). To this end, two UAS are custom-designed and flown for autonomous water sampling, incorporating an octocopter configuration and a ratchet and pawl mechanism for retracting and releasing payloads. This design offers easy-to-use and safe deployment and retraction without continuous motor engagement while eliminating load swinging and the risk of instability by positioning the sampler close to the drone’s center of mass. Furthermore, the system enables autonomous water sampling in remote or inaccessible areas with pre-programmed flight paths and sampling locations, ensuring consistent data collection. The sampling mechanism allows controlled retrieval and release of payloads and further facilitates multi-drone operations to support a variety of sampling missions. This innovative UAS has the potential to revolutionize water sampling and enhance efficiency and safety in environmental monitoring, research, and resource management. Flight tests over several water bodies demonstrate successful simultaneous water sampling missions with two UAS. To the best of the authors’ knowledge, this is the first work to include multiple UAS, each equipped with a payload deployment and retraction mechanism, for autonomous water sampling.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Bench or experimental | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".