Nonlinear Observer for Quadrotor Waypoint Navigation Using Only Range Measurements
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes a novel nonlinear estimator for the position of a quadrotor in waypoint navigation using range measurements. It is assumed that the flying vehicle follows a straight line at a constant altitude between two waypoints. The positions of the waypoints are known and the measurements are assumed to be the squared distance to the point source located at the departure waypoint. The measurement is corrupted by additive noise. Under these conditions it is shown that the dynamics of the estimation error are described by a nonlinear Verhulst logistc equation. This observation unveils a link between navigation of a vehicle using range measurements and population dynamics, which to the best of the authors' knowledge is new. The stability of the error dynamics and the stationary distribution of the error are investigated for both constant and ramp velocity inputs. The performance of the proposed estimator is evaluated and compared with a Kalman filter for an augmented system. A numerical example illustrates the proposed method.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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