Design of an autonomous racecar: Perception, state estimation and system integration

Miguel Valls, Hubertus Hendrikx, Victor Reijgwart, Fabio Meier, Inkyu Sa, Renaud Dube, Abel Gawel, Mathias Bürki and Roland Siegwart

IEEE International Conference on Robotics and Automation (ICRA) 2018

This paper introduces fluela 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 fluela’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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@inproceedings{valls2018design,
  title={Design of an autonomous racecar: Perception, state estimation and system integration},
  author={Valls, Miguel I and Hendrikx, Hubertus FC and Reijgwart, Victor JF and Meier, Fabio V and Sa, Inkyu and Dub{\'e}, Renaud and Gawel, Abel and B{\"u}rki, Mathias and Siegwart, Roland},
  booktitle={2018 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={2048--2055},
  year={2018},
  organization={IEEE}
}