AMZ Driverless: The Full Autonomous Racing System
Juraj Kabzan, Miguel de la Iglesia Valls, Victor Reijgwart, Hubertus, Franciscus Cornelis Hendrikx, Claas Ehmke, Manish Prajapat, Andreas B\"uhler,, Nikhil Gosala, Mehak Gupta, Ramya Sivanesan, Ankit Dhall, Eugenio Chisari,, Napat Karnchanachari, Sonja Brits, Manuel Dangel
TL;DR
This paper details the development of an autonomous racecar system combining perception, estimation, and control, achieving top competition results through robust, reliable, and extensible algorithms and architecture.
Contribution
It introduces a comprehensive autonomous racing system integrating multiple robotics techniques, with a focus on robustness and real-world performance in competitions.
Findings
Achieved 1st place in multiple Formula Student competitions.
Demonstrated robustness and reliability of the system in unknown track racing.
Provided experimental evaluation of each module in the autonomous system.
Abstract
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.
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