Coopération entre perception déportée et embarquée sur un robot guide pour l’aide à sa navigation
Bibliographic record
Abstract
RESUME. Cet article decrit une strategie de cooperation entre des cameras d’ambiance et des capteurs embarques sur un robot mobile pour : (i) suivre une personne donnee et identifiee par un tag/badge radio frequence (RF), et (ii) faciliter sa navigation en presence de passants lors de l’execution de cette mission. Nous privilegions une approche tracking-by-detection qui fusionne au sein d’un filtre particulaire par chaine de Markov les detections visuelles deportees et les detections issues des divers capteurs embarques (laser, vision active, RFID). Les performances du traqueur multi-personne sont caracterisees par des evaluations qualitatives et quantitatives sur sequences pre-enregistrees. Enfin, l’integration du systeme perceptuel sur le robot et le controle de ses actionneurs via des techniques d’asservissement visuel et du diagramme d’espace libre au voisinage immediat du robot, illustrent la capacite du robot a suivre une personne donnee en espace humain encombre.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.009 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".