RIs-Calib: An Open-Source Spatiotemporal Calibrator for Multiple 3D Radars and IMUs Based on Continuous-Time Estimation
<|reference_start|>RIs-Calib: An Open-Source Spatiotemporal Calibrator for Multiple 3D Radars and IMUs Based on Continuous-Time Estimation: Aided inertial navigation system (INS), typically consisting of an inertial measurement unit (IMU) and an exteroceptive sensor, has been widely accepted as a feasible solution for navigation. Compared with vision-aided and LiDAR-aided INS, radar-aided INS could achieve better performance in adverse weather conditions since the radar utilizes low-frequency measuring signals with less attenuation effect in atmospheric gases and rain. For such a radar-aided INS, accurate spatiotemporal transformation is a fundamental prerequisite to achieving optimal information fusion. In this work, we present RIs-Calib: a spatiotemporal calibrator for multiple 3D radars and IMUs based on continuous-time estimation, which enables accurate spatiotemporal calibration and does not require any additional artificial infrastructure or prior knowledge. Our approach starts with a rigorous and robust procedure for state initialization, followed by batch optimizations, where all parameters can be refined to global optimal states steadily. We validate and evaluate RIs-Calib on both simulated and real-world experiments, and the results demonstrate that RIs-Calib is capable of accurate and consistent calibration. We open-source our implementations at (https://github.com/Unsigned-Long/RIs-Calib) to benefit the research community.<|reference_end|>
@article{chen2024ris-calib:,
    title={RIs-Calib: An Open-Source Spatiotemporal Calibrator for Multiple 3D
  Radars and IMUs Based on Continuous-Time Estimation},
    author={Shuolong Chen, Xingxing Li, Shengyu Li, Yuxuan Zhou, and Shiwen Wang},
    journal={arXiv preprint arXiv:2408.02444},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.02444},
    primaryClass={cs.RO}
}