Drone-Based Cable-Suspended Payload Tracking and Estimation Using Simulated LiDAR Measurements and an Extended Kalman Filter
Why this work is in the frame
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Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2022-2290.vid The ability of drones to navigate through remote terrain and avoid ground-based vehicular traffic has led to an increase in remote sensing studies and drone-based transportation services. Such applications require a payload to be suspended from the drone via a cable which can introduce instability in the drone's flight resulting from the sway of the suspended payload. Therefore, to maintain a stable flight it is key to measure the position of the payload relative to the drone. This study uses a Vicon motion capture system to measure the position of the drone and simulated Light Detection and Ranging (LiDAR) measurements for the position of the payload. LiDAR measurements are simulated using a LiDAR noise model developed from experimental results using the Velodyne VLP-16 sensor. A nonlinear dynamic model of a drone-based single cable-suspended payload is developed and a discrete Extended Kalman Filter is used to obtain an accurate estimate of the position of the drone and the position of the payload relative to the drone.
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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 | 0.001 | 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 it