Universal IMU-Centric Spatiotemporal Calibration Algorithm for Heterogeneous Information

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%.