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arXiv:1610.06534cs.LG

Autonomous Racing using Learning Model Predictive Control

Ugo Rosolia, Ashwin Carvalho, Francesco Borrelli

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Abstract

A novel learning Model Predictive Control technique is applied to the autonomous racing problem. The goal of the controller is to minimize the time to complete a lap. The proposed control strategy uses the data from previous laps to improve its performance while satisfying safety requirements. Moreover, a system identification technique is proposed to estimate the vehicle dynamics. Simulation results with the high fidelity simulator software CarSim show the effectiveness of the proposed control scheme.

arXiv comments
Extended version of the paper accepted to ACC
Journal reference
DOI
Subjects
cs.LGMachine Learning math.OCOptimization and Control

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  1. Fast line-following robots 1 comment

    • I'm aware of one paper which tries to fit a local polynomial model to the lateral dynamics, and they have a different model for different positions on the track (it requires really good localization to work): https://arxiv.org/abs/1610.06534 I had some of the vehicle parameters…

      a1k0nView on HNParent context

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