Fault-tolerant Localization for multi-UAV cooperative flight
Why this work is in the frame
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Bibliographic record
Abstract
A novel fault-tolerant localization method for low-cost UAVs flying at constant altitude is proposed in this paper, which is based on measuring relative ranges from one UAV to other UAVs. Contrast to the traditional navigation methods of single aerial vehicle, like INS/GPS and SINS/GPS, the proposed method is more suitable for low-cost small-size UAVs because of its low requirement to the navigation device. Furthermore, its localization accuracy is higher than other methods for multi-UAV because the sharable information in multi-UAV network is made full of use. Similar to the principle of GPS, the method takes three other UAVs as the reference points of an UAV whose GPS receiver works improperly due to failure. Thus the UAV's location in 2D horizontal plane can be determined by using the relative ranges from the faulty UAV to the other three UAVs at known location in inertial coordinate system. In order to improve the accuracy of estimated location, a Kalman filter is designed, which can calculate the variance of observations in terms of horizontal dilution of positioning (HDOP) adaptively. Meanwhile, option of the reference points is also optimized in the paper. Simulation results in Matlab\Simulink show the effectiveness of the proposed approach.
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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 | 0.000 | 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 it