Energy efficient navigational methods for autonomous underwater gliders in surface denied regions
Notice bibliographique
Résumé
Autonomous underwater gliders routinely perform long duration profiling missions while characterizing the chemical, physical and biological properties of the water column. These measurements have opened up new ways of observing the ocean’s processes and their interactions with the atmosphere across time and length scales which were not previously possible. Extending these observations to ice-covered regions is of importance due to their role in ocean circulation patterns, increased economic interest in these areas and a general sparsity of observations. This thesis develops an energy optimal depth controller, a terrain aided navigation method and a magnetic measurement method for an autonomous underwater glider. A review of existing methods suitable for navigation in underwater environments as well as the state of the art in magnetic measurement and calibration techniques is also presented. The energy optimal depth controller is developed and implemented based on an integral state feedback controller. A second order linear time invariant system is identified from field data and used to compute the state feedback controller gains through an augmented linear quadratic regulator. The resulting gains and state feedback controller methodology are verified through field trials and found to control the depth of the vehicle while losing less than one percent of the vehicle’s propulsive load to control inputs or lift induced drag. The terrain aided navigation method is developed based on a jittered bootstrap algorithm which is a type of particle filter that makes use of the vehicle’s deadreckoned navigation solution, onboard altimeter and a local digital parameter model (DPM). An evaluation is performed through post-processing offline location estimates from field trials which took place in Holyrood Arm, Newfoundland, overlapping a previously collected DPM. During the post-processing of these trials, the number of particles, jittering variance and DPM grid cell size were varied. Online open loop field trials were performed through integrating a new single board computer. In these trials the localization error remained bounded and improved on the dead reckoning error, validating the filter despite the large dead-reckoned errors, single beam altitude measurements, and short test duration. Terrain aided navigation methods perform poorly in regions of flat terrain or in deep water where the seafloor is beyond the range of the altimeter. Magnetic measurements of the Earth’s main field have been proposed previously to augment terrain aided navigation algorithms in these regions. To this end a low power magnetic instrumentation suite for an underwater glider has been developed. Two calibration methodologies were also developed and compared against regional digital models of the magnetic field. The calibration methods include one for which the actuators in the vehicle were kept in fixed locations and a second for which the calibration coefficients were parameterized for the actuator locations. Both methods were found to agree with the low frequency content in the a-priori regional magnetic anomaly grids.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».