Edge-Based Event-Triggered Tracking Formation of Multiagent Systems With Bearing Measurements
Why this work is in the frame
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Bibliographic record
Abstract
This article focuses on the event-triggered tracking formation for first-order multiagent systems, utilizing relative bearing information of neighboring agents. To optimize resource utilization and minimize on-board load, we introduce two kinds of edge-based event-triggered control (EBETC) schemes that determine the updating of bearing information and intermittently transmit control signals. Moreover, to reduce the dependence on hardware for persistent signal monitoring, this work further extends into a dynamic self-triggered control scheme, exploring its robustness against bounded disturbances. Employing the Lyapunov method alongside inequality techniques, these control schemes ensure that the bearing and velocity of every agent exponentially converge to the desired values. Compared to the static EBETC scheme, the dynamic approach adjusts the threshold in real-time based on the error, thereby extending the average interevent time and expanding the range of parameter choices. We substantiate these conclusions through the comparative experiment, illustrating the feasibility of our theoretical findings.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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