1 code implementation • 27 Mar 2021 • Shayan Taherian, Sampo Kuutti, Marco Visca, Saber Fallah
It is shown that, torque-vectoring controller with parameter tuning via reinforcement learning performs well on a range of different driving environment e. g., wide range of friction conditions and different velocities, which highlight the advantages of reinforcement learning as an adaptive algorithm for parameter tuning.