Evolution of station keeping as a response to flows in an aquatic robot

Abstract

Developing complex behaviors for aquatic robots is a difficult en- gineering challenge due to the uncertainty of an underwater environment. Neuroevolution provides one method of dealing with this type of problem. Artificial neural networks discern different conditions by mapping sensory input to responses, and evolutionary computation provides a training… (More)
DOI: 10.1145/2463372.2463402

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