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Notice bibliographique
Résumé
The goal of this thesis is to address the rendezvous problem for multi-agent coordination and search.To rendezvous is to meet or to physically come together, and the applications of this problem range from everyday life to robotics.Example scenarios for these applications are friends coordinating a meeting or robots and autonomous vehicles coming together for load balancing or resource sharing.Each of these tasks require a rendezvous, which can involve a considerable amount of inter-agent coordination.Our goal is to develop energy-efficient rendezvous algorithms so that we can minimize the inter-agent coordination cost, the number of rendezvous attempts, failure rate, total distance traveled and time taken to rendezvous.We study the multi-agent rendezvous problem under two primary constraints: the amount of prior knowledge about the environment and the agents, and the frequency of communication allowed between the agents.These constraints are combined to define four classes of the rendezvous problem, in different environments with different agents.They are: (a) no prior knowledge and no communication, (b) partial prior knowledge and partial communication, (c) no prior knowledge and partial communication and (d) partial prior knowledge and no communication.We specifically consider four scenarios corresponding to each category respectively, as: (1) rendezvous of simulated agents for resource sharing while exploring an unknown environment without communication, (2) rendezvous between humans on street networks with intermittent communication and uncertainties in travel time, (3) rendezvous search by an Autonomous Underwater Vehicle (AUV) for passively floating scientific data collectors with no prior knowledge about the environment or the agent and periodic communication for motion modeling of the floating targets, and lastly, (4) an Autonomous Surface Vehicle (ASV) searching for lost targets at sea with some prior knowledge about the target's probability distribution and no communication until the target is found.We analyze the rendezvous problem in each of these four cases and present algorithms for them.We validate our proposed rendezvous coordination and search algorithms using software tools that we developed for large scale simulation and testing.This thesis is the result of the great mentorship and extreme patience of my advisor, Prof. Gregory Dudek.He introduced me and many other graduate students to the fundamentals of robotics with his very animated course, "Introduction to Robotics and Intelligent Systems".His timely advice during the course of my Ph.D. program was useful not only in my academic life but will also serve me as lessons for a lifetime.He is a generator of excellent ideas, a modern philosopher and a visionary in the true sense of the word.While he closely guided me in my academic life, he also allowed me to wander at times, to explore new possibilities for learning and growing as a researcher.His positive attitude made some of the most difficult times during my research, just a passing phase.His mentoring combined with great lab facilities and awesome colleagues has made my research a truly wonderful experience.During my program, I had the honour of working with some of the brightest minds in
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,008 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle