Towards improvement of autonomous glider navigation accuracy through the use of regional ocean models
Data(s) |
01/06/2010
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Resumo |
Autonomous underwater gliders are robust and widely-used ocean sampling platforms that are characterized by their endurance, and are one of the best approaches to gather subsurface data at the appropriate spatial resolution to advance our knowledge of the ocean environment. Gliders generally do not employ sophisticated sensors for underwater localization, but instead dead-reckon between set waypoints. Thus, these vehicles are subject to large positional errors between prescribed and actual surfacing locations. Here, we investigate the implementation of a large-scale, regional ocean model into the trajectory design for autonomous gliders to improve their navigational accuracy. We compute the dead-reckoning error for our Slocum gliders, and compare this to the average positional error recorded from multiple deployments conducted over the past year. We then compare trajectory plans computed on-board the vehicle during recent deployments to our prediction-based trajectory plans for 140 surfacing occurrences. |
Formato |
application/pdf |
Identificador | |
Publicador |
ASME - American Society Mechanical Engineering |
Relação |
http://eprints.qut.edu.au/40121/1/654.pdf http://www.asmeconferences.org/omae2010/ Smith, Ryan N. , Kelly, Jonathan, Chao, Yi, Jones, Burton H., & Sukhatme, Gaurav S. (2010) Towards improvement of autonomous glider navigation accuracy through the use of regional ocean models. In Proceedings of the 29th International Conference on OCean, Offshore and Arctic Engineering, ASME - American Society Mechanical Engineering, Grand Hyatt Hotel, Shanghai, China, pp. 597-606. |
Direitos |
Copyright 2010 ASME |
Fonte |
Faculty of Built Environment and Engineering; School of Engineering Systems |
Palavras-Chave | #040503 Physical Oceanography #080101 Adaptive Agents and Intelligent Robotics #091103 Ocean Engineering #091106 Special Vehicles #Autonomous Underwater Vehicle #Ocean modeling #Path Planning #Kalman filter |
Tipo |
Conference Paper |