A new empirical EHD feedforward controller using polynomial surface fit outperforms learning-based methods in closed-loop robustness and lap times during high-fidelity autonomous racing simulation.
Differentiable weights-varying nonlinear mpc via gradient-based policy learning: An autonomous vehicle guid- ance example,
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Benchmarking Empirical and Learning-Based Approaches for Feedforward Steering Control in Autonomous Racing
A new empirical EHD feedforward controller using polynomial surface fit outperforms learning-based methods in closed-loop robustness and lap times during high-fidelity autonomous racing simulation.