This paper considers an AUV guidance system for subsurface ice intelligence. A topologically organized neural network model is used to represent the operating environment. The dynamics of each neuron, characterized by a shunting equation, are used to represent the local environmental information. Targeted areas have the highest values. The AUV moves from areas with low dynamics to areas with higher dynamics like in a potential field navigation. The kinematic constraints of the AUV are taken into account by using Dubins theory to generate feasible paths.

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