Challenges in Marine Autonomy
Notice bibliographique
Résumé
This talk will consider the challenges associated with autonomous marine systems. The work of the University of Sydney’s Australian Centre for Field Robotics (ACFR) marine robotics group has focused on developing and deploying underwater vehicles and imaging platforms in support of applications in engineering science, marine ecology, archaeology, and geoscience. We have operated an Australia-wide benthic observing program designed to deliver precisely navigated, repeat imagery of the seafloor. This initiative makes extensive use of Autonomous Underwater Vehicles (AUVs) to collect high-resolution stereo imagery, multibeam sonar, and water column measurements on an annual or semi-annual basis at sites around Australia, spanning the full latitudinal range of the continent from tropical reefs in the north to temperate regions in the south. The program has been very successful over the past 15 years, collecting millions of images of the seafloor around Australia and making these available to the scientific community through online data portals developed by the facility and affiliated groups. These observations are providing important insights into the dynamics of key ecological sites and their responses to changes in oceanographic conditions through time. We have also contributed to expeditions to document coral bleaching, cyclone recovery, submerged neolithic settlement sites, ancient shipwrecks, methane seeps, and deepwater hydrothermal vents. The talk will also consider how automated tools for working with this imagery have facilitated the resulting science outcomes. Presenter Bio Prof. Stefan B. Williams is the Head of School of Aerospace, Mechanical and Mechatronic Engineering, and Professor of Marine Robotics at the University of Sydney. He is a member of the Australian Centre for Field Robotics where he leads the Marine Robotics group and is the head of Australia’s Integrated Marine Observing System Autonomous Underwater Vehicle Facility. He was president of the Australian Robotics and Automation Association from 2014-2016 and in 2018 was recognised as a Distinguished Lecturer by the IEEE Ocean Engineering Society. His research interests include Simultaneous Localisation and Mapping in unstructured underwater environments using visual and acoustic sensing, autonomous navigation and control, and classification and clustering of large volumes of data collected by robotic systems. He received his PhD from the University of Sydney in 2002 and completed a Bachelor of Applied Science in Systems Design Engineering at the University of Waterloo, Canada in 1997.
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Comment cette classification a été obtenuedéplier
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».