Autonomous Multi-Target Interception in Dynamic Settings – On-Line Pursuer Task Allocation
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In this paper, we present a generic task-allocation methodology for time-optimal, autonomous on-line interception of multiple dynamic targets by a team of robotic pursuers. The proposed novel methodology is applicable to problems consisting of numerous variations of multiple pursuers and targets. The targets are assumed to be highly maneuverable with a priori unknown, though real-time trackable, motion trajectories. Guidance theory is employed to allow each of the pursuers to navigate autonomously towards its allocated target. Numerous simulations and experiments have verified that the proposed methodology is tangibly efficient in dynamic (one-to-one) re-pairing of pursuers to targets for minimum total overall interception time.
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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