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Model-Based Adaptive Behavior Framework for Optimal Acoustic Communication and Sensing by Marine Robots

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2 Author(s)
Toby Schneider ; Center for Ocean Engineering in the Department of Mechanical Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA ; Henrik Schmidt

In this paper, a hybrid data- and model-based autonomous environmental adaptation framework is presented which allows autonomous underwater vehicles (AUVs) with acoustic sensors to follow a path which optimizes their ability to maintain connectivity with an acoustic contact for optimal sensing or communication. The adaptation framework is implemented within the behavior-based mission-oriented operating suite-interval programming (MOOS-IvP) marine autonomy architecture and uses a new embedded high-fidelity acoustic modeling infrastructure, the generic robotic acoustic model (GRAM), to provide real-time estimates of the acoustic environment under changing environmental and situational scenarios. A set of behaviors that combine adaptation to the current acoustic environment with strategies that extend the decision horizon beyond that of typical behavior-based systems have been developed, implemented, and demonstrated in a series of field experiments and virtual experiments in a MOOS-IvP simulation.

Published in:

IEEE Journal of Oceanic Engineering  (Volume:38 ,  Issue: 3 )