ICODE-MPPI uses Input Concomitant Neural ODEs to learn residual dynamics and reduce vehicle cross-tracking error by up to 69% under disturbances compared with standard MPPI.
Controlsynth neural odes: Modeling dynamical systems with guaranteed convergence,
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Robust Path Tracking for Vehicles via Continuous-Time Residual Learning: An ICODE-MPPI Approach
ICODE-MPPI uses Input Concomitant Neural ODEs to learn residual dynamics and reduce vehicle cross-tracking error by up to 69% under disturbances compared with standard MPPI.