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DynSSM: A Physics-Aware State-Space Memory Framework for Learning Vehicle Dynamics
Accurate modeling of nonlinear vehicle dynamics is essential for high-speed autonomous racing, where controllers operate at the handling limits. Model-based methods are interpretable but rely on simplifying assumptions, while purely learned models capture nonlinearities yet often lack physical consi
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