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arXiv · 1804.03252

Design of an Autonomous Racecar: Perception, State Estimation and System Integration

Miguel de la Iglesia Valls·Hubertus Franciscus Cornelis Hendrikx·Victor Reijgwart·Fabio Vito Meier·Inkyu Sa·Renaud Dubé·Abel Roman Gawel·Mathias Bürki·Roland Siegwart
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Abstract

This paper introduces fl\"uela driverless: the first autonomous racecar to win a Formula Student Driverless competition. In this competition, among other challenges, an autonomous racecar is tasked to complete 10 laps of a previously unknown racetrack as fast as possible and using only onboard sensing and computing. The key components of fl\"uela's design are its modular redundant sub-systems that allow robust performance despite challenging perceptual conditions or partial system failures. The paper presents the integration of key components of our autonomous racecar, i.e., system design, EKF-based state estimation, LiDAR-based perception, and particle filter-based SLAM. We perform an extensive experimental evaluation on real-world data, demonstrating the system's effectiveness by outperforming the next-best ranking team by almost half the time required to finish a lap. The autonomous racecar reaches lateral and longitudinal accelerations comparable to those achieved by experienced human drivers.

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Miguel de la Iglesia Valls, Hubertus Franciscus Cornelis Hendrikx, Victor Reijgwart, Fabio Vito Meier, Inkyu Sa, Renaud Dubé, Abel Roman Gawel, Mathias Bürki, Roland Siegwart. 2018-04-09. Design of an Autonomous Racecar: Perception, State Estimation and System Integration. https://arxiv.org/abs/1804.03252

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