Universal IMU-Centric Spatiotemporal Calibration Algorithm for Heterogeneous Information

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Universal IMU-Centric Spatiotemporal Calibration Algorithm for Heterogeneous Information
Title:
Universal IMU-Centric Spatiotemporal Calibration Algorithm for Heterogeneous Information
Journal Title:
2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring)
Keywords:
Publication Date:
25 September 2024
Citation:
Shi, Y., Lian, B., Zeng, Y., Ma, Y., & Liu, Y. (2024). Universal IMU-Centric Spatiotemporal Calibration Algorithm for Heterogeneous Information. 2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring), 1–5. https://doi.org/10.1109/vtc2024-spring62846.2024.10683438
Abstract:
Spatiotemporal calibration is an essential problem in the fusion system with heterogeneous multi-source information. Therefore, a universal spatiotemporal calibration algorithm for heterogeneous information is much needed. This paper proposes a universal spatiotemporal calibration technique with the inertial sensor as the central coordinate system. Firstly, it employs a high-order spline interpolation method to transform the output data of the inertial sensor into a continuous form. Subsequently, the calibration model is established by combining the output data from other sensors. The paper provides detailed descriptions of the spatiotemporal calibration models for LiDAR (Light Detection and Ranging) data, and visual data, respectively. In the simulations, the proposed calibration models are applied to existing open-source programs using publicly available datasets. The results demonstrate that, with the adoption of the proposed calibration algorithm, the position estimation accuracy of the fusion system can be improved by 39%.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the NRF - FCP
Grant Reference no. : FCP-NTURG- 2022-021, FCP-ASTAR-TG-2022-003

This research / project is supported by the National Natural Science Foundation of China - Grant
Grant Reference no. : 62173276, 62171735, 62101458, 62001392, 61803310, 61801394

This research / project is supported by the Natural Science Basic Research Program of Shaanxi - GY, JQ
Grant Reference no. : 2022GY-097,2021JQ-122, 2021JQ-693

This research / project is supported by the China Postdoctoral Science Foundation - Grant
Grant Reference no. : 2020M673482, 2020M673485
Description:
© 2024 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISSN:
2577-2465
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