Visual-inertial state estimation based on Chebyshev polynomial optimization
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866914737236738048 |
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| author | Zhang, Hongyu Zhu, Maoran Cai, Qi Wu, Yuanxin |
| author_facet | Zhang, Hongyu Zhu, Maoran Cai, Qi Wu, Yuanxin |
| contents | This paper proposes an innovative state estimation method for visual-inertial fusion based on Chebyshev polynomial optimization. Specifically, the pose is modeled as a Chebyshev polynomial of a certain order, and its time derivatives are used to calculate linear acceleration and angular velocity, which, along with inertial measurements, constitute dynamic constraints. This is coupled with a visual measurement model to construct a visual-inertial bundle adjustment formulation. Simulation and public dataset experiments show that the proposed method has better accuracy than the discrete-form preintegration method. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_01150 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Visual-inertial state estimation based on Chebyshev polynomial optimization Zhang, Hongyu Zhu, Maoran Cai, Qi Wu, Yuanxin Robotics This paper proposes an innovative state estimation method for visual-inertial fusion based on Chebyshev polynomial optimization. Specifically, the pose is modeled as a Chebyshev polynomial of a certain order, and its time derivatives are used to calculate linear acceleration and angular velocity, which, along with inertial measurements, constitute dynamic constraints. This is coupled with a visual measurement model to construct a visual-inertial bundle adjustment formulation. Simulation and public dataset experiments show that the proposed method has better accuracy than the discrete-form preintegration method. |
| title | Visual-inertial state estimation based on Chebyshev polynomial optimization |
| topic | Robotics |
| url | https://arxiv.org/abs/2404.01150 |