Flow-aware Optimal Navigation in Unsteady Flows through Reinforcement Learning
Autonomous robotic navigation in nonstationary time-varying fluid flows remains a fundamental challenge due to partial observability and the unpredictability of realistic environments. While classical optimal control frameworks employed in
https://arxiv.org/abs/2607.13553v1 ↗Thesis fit
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Andrea Maria Braghin
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Nicolò Botteghi
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Matteo Tomasetto
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Andrea Manzoni
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Gabriele Cazzulani
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