Optimization-Based System Identification and Moving Horizon Estimation Using Low-Cost Sensors for a Miniature Car-Like Robot
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arXiv
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| Auteurs principaux: | , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909427684081664 |
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| author | Bodmer, Sabrina Vogel, Lukas Muntwiler, Simon Hansson, Alexander Bodewig, Tobias Wahlen, Jonas Zeilinger, Melanie N. Carron, Andrea |
| author_facet | Bodmer, Sabrina Vogel, Lukas Muntwiler, Simon Hansson, Alexander Bodewig, Tobias Wahlen, Jonas Zeilinger, Melanie N. Carron, Andrea |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_08362 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimization-Based System Identification and Moving Horizon Estimation Using Low-Cost Sensors for a Miniature Car-Like Robot Bodmer, Sabrina Vogel, Lukas Muntwiler, Simon Hansson, Alexander Bodewig, Tobias Wahlen, Jonas Zeilinger, Melanie N. Carron, Andrea Robotics Systems and Control 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. |
| title | Optimization-Based System Identification and Moving Horizon Estimation Using Low-Cost Sensors for a Miniature Car-Like Robot |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2404.08362 |