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arXiv · 2404.08362

Optimization-Based System Identification and Moving Horizon Estimation Using Low-Cost Sensors for a Miniature Car-Like Robot

Sabrina Bodmer·Lukas Vogel·Simon Muntwiler·Alexander Hansson·Tobias Bodewig·Jonas Wahlen·Melanie N. Zeilinger·Andrea Carron
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Abstract

This paper presents an open-source miniature car-like robot with low-cost sensing and a pipeline for optimization-based system identification, state estimation, and control. The overall robotics platform comes at a cost of less than \$\,700 and thus significantly simplifies the verification of advanced algorithms in a realistic setting. We present a modified bicycle model with Pacejka tire forces to model the dynamics of the considered all-wheel drive vehicle and to prevent singularities of the model at low velocities. Furthermore, we provide an optimization-based system identification approach and a moving horizon estimation (MHE) scheme. In extensive hardware experiments, we show that the presented system identification approach results in a model with high prediction accuracy, while the MHE results in accurate state estimates. Finally, the overall closed-loop system is shown to perform well even in the presence of sensor failure for limited time intervals. All hardware, firmware, and control and estimation software is released under a BSD 2-clause license to promote widespread adoption and collaboration within the community.

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Sabrina Bodmer, Lukas Vogel, Simon Muntwiler, Alexander Hansson, Tobias Bodewig, Jonas Wahlen, Melanie N. Zeilinger, Andrea Carron. 2024-04-12. Optimization-Based System Identification and Moving Horizon Estimation Using Low-Cost Sensors for a Miniature Car-Like Robot. https://arxiv.org/abs/2404.08362

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