Affine Formation Control of Multiple Quadcopters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper considers the distributed time-varying formation tracking control problem of multi-quadcopter systems using affine formation control strategies with multiple virtual leaders. A novel two-layer (formation layer and local control layer) affine formation control structure is established to account for the underactuated nature of the quadcopter dynamics. In the formation layer, a quadcopter is abstracted as a virtual double-integrator agent and affine formation controllers are then designed based on the networked double-integrator dynamics. The resultant virtual affine formation control inputs from the formation layer are converted to the desired attitudes based on the quadcopter dynamics, and a sliding mode controller is then proposed to ensure flnite-time tracking convergence to the desired attitude in the local control layer. Numerical simulations were carried out using a group of six quadcopters in the XY-plane to demonstrate and validate the effectiveness of the developed controllers.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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