Autonomous Racing using Learning Model Predictive Control

2016/10/20 by Ugo Rosolia, Rosolia, Ugo, Ashwin Carvalho +3 · 2 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #cs.LG #math.OC

paper · pdf · doi:10.48550/arxiv.1610.06534

Extended version of the paper accepted to ACC

arxiv created 2017/11/09 · arxiv updated 2017/11/10

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.

Cited by

• End2Race: Efficient End-to-End Imitation Learning for Real-Time F1Tenth Racing
• Improving Drone Racing Performance Through Iterative Learning MPC

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