A Universal Formulation for Path-Parametric Planning and Control
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913713910448128 |
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| author | Arrizabalaga, Jon ŠÍR, Zbyněk Manchester, Zachary Ryll, Markus |
| author_facet | Arrizabalaga, Jon ŠÍR, Zbyněk Manchester, Zachary Ryll, Markus |
| contents | We present a unified framework for path-parametric planning and control. This formulation is universal as it standardizes the entire spectrum of path-parametric techniques -- from traditional path following to more recent contouring or progress-maximizing Model Predictive Control and Reinforcement Learning -- under a single framework. The ingredients underlying this universality are twofold: First, we present a compact and efficient technique capable of computing singularity-free, smooth and differentiable moving frames. Second, we derive a spatial path parameterization of the Cartesian coordinates for any arbitrary curve without prior assumptions on its parametric speed or moving frame, and that perfectly interplays with the aforementioned path parameterization method. The combination of these two ingredients leads to a planning and control framework that unites existing path-parametric techniques in literature. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_04664 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Universal Formulation for Path-Parametric Planning and Control Arrizabalaga, Jon ŠÍR, Zbyněk Manchester, Zachary Ryll, Markus Robotics Systems and Control We present a unified framework for path-parametric planning and control. This formulation is universal as it standardizes the entire spectrum of path-parametric techniques -- from traditional path following to more recent contouring or progress-maximizing Model Predictive Control and Reinforcement Learning -- under a single framework. The ingredients underlying this universality are twofold: First, we present a compact and efficient technique capable of computing singularity-free, smooth and differentiable moving frames. Second, we derive a spatial path parameterization of the Cartesian coordinates for any arbitrary curve without prior assumptions on its parametric speed or moving frame, and that perfectly interplays with the aforementioned path parameterization method. The combination of these two ingredients leads to a planning and control framework that unites existing path-parametric techniques in literature. |
| title | A Universal Formulation for Path-Parametric Planning and Control |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2410.04664 |