One Model to Drift Them All: Physics-Informed Conditional Diffusion Model for Driving at the Limits
Controls vehicles near handling limits using conditional diffusion. A physics-informed dynamics-parameter distribution is conditioned on online measurements and integrated into model predictive control.
Overview
Controls vehicles near handling limits using conditional diffusion. A physics-informed dynamics-parameter distribution is conditioned on online measurements and integrated into model predictive control.
Controls vehicles near handling limits using conditional diffusion. A physics-informed dynamics-parameter distribution is conditioned on online measurements and integrated into model predictive control.
When reading the original paper, identify its problem, inputs, outputs, and methodological assumptions.
Controls vehicles near handling limits using conditional diffusion. A physics-informed dynamics-parameter distribution is conditioned on online measurements and integrated into model predictive control.
Check the baselines, datasets, evaluation protocol, and ablations in the original paper. This directory overview does not provide an independent evaluation or experimental results table.
References
ID: corl-2024-one-model-to-drift · Last verified:
