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Stability-Aware Imitation Learning from Model Predictive Control for Autonomous Vehicle Lateral Control: Exact Q-Loss and a Novel Training Procedure
US & West ·
arXiv:2609.23506v1 Announce Type: new Abstract: This paper develops a certified imitation-learning framework for approximating model predictive control (MPC) policies with feedforward neural controllers and validates it on autonomous-vehicle lateral control.
Original headline
Stability-Aware Imitation Learning from Model Predictive Control for Autonomous Vehicle Lateral Control: Exact Q-Loss and a Novel Training Procedure
arXiv:2603.25959v2 Announce Type: replace Abstract: Human and animal brains perform planning to enable complex movements and behaviors, a process that can be effectively described using model predictive control (MPC).
arXiv:2609.17697v1 Announce Type: cross Abstract: Integrated deep reinforcement learning (DRL) and model predictive control (MPC) methods are increasingly used to control autonomous systems by combining their complementary capabilities.
arXiv:2511.02114v2 Announce Type: replace Abstract: We propose a Model Predictive Control (MPC) formulation for nonlinear systems without terminal penalty or dedicated stabilizing terminal set, in which state constraints are enforced heterogeneously along the prediction horizon.
