Learning Input Constrained Control Barrier Functions for Guaranteed Safety of Car-Like Robots
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866913237502525440 |
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| author | Brüggemann, Sven Nightingale, Dominic Silberman, Jack de Oliveira, Maurício |
| author_facet | Brüggemann, Sven Nightingale, Dominic Silberman, Jack de Oliveira, Maurício |
| contents | We propose a design method for a robust safety filter based on Input Constrained Control Barrier Functions (ICCBF) for car-like robots moving in complex environments. A robust ICCBF that can be efficiently implemented is obtained by learning a smooth function of the environment using Support Vector Machine regression. The method takes into account steering constraints and is validated in simulation and a real experiment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_12512 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Learning Input Constrained Control Barrier Functions for Guaranteed Safety of Car-Like Robots Brüggemann, Sven Nightingale, Dominic Silberman, Jack de Oliveira, Maurício Robotics Systems and Control We propose a design method for a robust safety filter based on Input Constrained Control Barrier Functions (ICCBF) for car-like robots moving in complex environments. A robust ICCBF that can be efficiently implemented is obtained by learning a smooth function of the environment using Support Vector Machine regression. The method takes into account steering constraints and is validated in simulation and a real experiment. |
| title | Learning Input Constrained Control Barrier Functions for Guaranteed Safety of Car-Like Robots |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2402.12512 |