Enabling Persistent Autonomy for Underwater Gliders with Ocean Model Predictions and Terrain-Based Navigation

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Enabling Persistent Autonomy for Underwater Gliders with Ocean Model Predictions and Terrain-Based Navigation

Effective study of ocean processes requires sampling over the duration of long (weeks to months) oscillation patterns. Such sampling requires persistent, autonomous underwater vehicles that have a similarly, long deployment duration. The spatiotemporal dynamics of the ocean environment, coupled with limited communication capabilities, make navigation and localization difficult, especially in co...

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Persistent ocean monitoring with underwater gliders: Adapting sampling resolution

Ryan N. Smith School of Engineering Systems, Queensland University of Technology, Brisbane, Queensland 4000, Australia e-mail: [email protected] Mac Schwager GRASP Lab, University of Pennsylvania, Philadelphia, Pennsylvania 19104 e-mail: [email protected] Stephen L. Smith Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada e-mail: stephen.smi...

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Ocean processes are dynamic, complex, and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dyna...

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ژورنال

عنوان ژورنال: Frontiers in Robotics and AI

سال: 2016

ISSN: 2296-9144

DOI: 10.3389/frobt.2016.00023