Cerebellar Model Articulation Controller with introspective voting weight updates for quadrotor application
Why this work is in the frame
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Bibliographic record
Abstract
This paper explores control of a four rotor aerial vehicle, or quadrotor. The quadrotor exhibits under-damped and under-actuated dynamics, so designing a feedback control that can provide robustness to disturbances such as wind and adapt to payloads provides a research challenge. The Cerebellar Model Articulation Controller (CMAC) is a type of neural network that can provide the basis for a stable adaptive neurocontrol. However, traditional robust weight update schemes for the CMAC must often sacrifice performance to eliminate bursting caused by weight drift. This work applies an introspective voting weight update scheme to a CMAC to avoid busting, without reducing performance. The proposed scheme achieves stable, adaptive, and robust control in both simulation and experiment.
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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