Compact Ocean Models Enable Onboard AUV Autonomy and Decentralized Adaptive Sampling
Abstract
Long-term goals are to improve synoptic observations and enhance ocean prediction through development of new capabilities for persistent underwater ocean surveillance. Multi-platform ocean observing systems are typically centrally controlled from shore limiting their ability to adapt to new observations which would inform more effective sampling strategies. Our objectives: 1. Enhance the ability of mobile agents to respond adaptively by providing them with a synoptic realization of the environment in the form of compact models of the observed ocean, similar to [Frolov, 2007; Frolov et al., 2009; van der Merwe et al., 2007a]. 2. Develop compact representation of the ocean models that can be economically computed or transmitted onboard of an AUV. 3. Develop algorithms for adaptive planning of AUV surveys. 4. Validate the developed compact ocean models and onboard planning algorithms in a vehicle simulation environment for Monterey Bay.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2010
- Accession Number
- ADA542692
Entities
People
- Igor G. Shulman
- James Bellingham
- Sergey Frolov
Organizations
- United States Naval Research Laboratory