Model-Based Adaptive Behavior Framework for Optimal Acoustic Communication and Sensing by Marine Robots
Author(s)Schneider, Toby; Schmidt, Henrik
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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.
DepartmentMassachusetts Institute of Technology. Center for Ocean Engineering; Massachusetts Institute of Technology. Department of Mechanical Engineering; Woods Hole Oceanographic Institution
IEEE Journal of Oceanic Engineering
Institute of Electrical and Electronics Engineers (IEEE)
Schneider, Toby, and Henrik Schmidt. “Model-Based Adaptive Behavior Framework for Optimal Acoustic Communication and Sensing by Marine Robots.” IEEE J. Oceanic Eng. 38, no. 3 (July 2013): 522–533.