This paper presents the algorithms and system architecture of an autonomous racecar. The introduced vehicle is powered by a software stack designed for robustness, reliability, and extensibility. In order to autonomously race around a previously unknown track, the proposed solution combines state of the art techniques from different fields of robotics. Specifically, perception, estimation, and control are incorporated into one high-performance autonomous racecar. This complex robotic system, developed by AMZ Driverless and ETH Zurich, finished 1st overall at each competition we attended: Formula Student Germany 2017, Formula Student Italy 2018 and Formula Student Germany 2018. We discuss the findings and learnings from these competitions and present an experimental evaluation of each module of our solution.
@article{arxiv.1905.05150,
title = {AMZ Driverless: The Full Autonomous Racing System},
author = {Juraj Kabzan and Miguel de la Iglesia Valls and Victor Reijgwart and Hubertus Franciscus Cornelis Hendrikx and Claas Ehmke and Manish Prajapat and Andreas Bühler and Nikhil Gosala and Mehak Gupta and Ramya Sivanesan and Ankit Dhall and Eugenio Chisari and Napat Karnchanachari and Sonja Brits and Manuel Dangel and Inkyu Sa and Renaud Dubé and Abel Gawel and Mark Pfeiffer and Alexander Liniger and John Lygeros and Roland Siegwart},
journal= {arXiv preprint arXiv:1905.05150},
year = {2019}
}
Comments
40 pages, 32 figures, submitted to Journal of Field Robotics