An approach of automatic calibration and online estimation for camera-IMU extrinsic parameters in monocular visual-inertial SLAM (Simultaneous Localization and Mapping) is proposed in this paper. Firstly, the camera-IMU extrinsic rotation is estimated with the hand-eye calibration as well as the gyroscope bias. Secondly, the scale factor, gravity and camera-IMU extrinsic translation are approximated without considering the accelerometer bias. All these parameters are refined with the gravitational magnitude and accelerometer bias taken into account at last. Furthermore, the camera-IMU extrinsic parameters are put into state vectors for online estimation. Experiment result with the EuRoC dataset shows that the algorithm automatically calibrates and estimates the camera-IMU extrinsic parameter with the extrinsic orientation and translation’s error within 0.5° and 0.02 m separately, which contributes to the rapid use and accuracy of the VI-SLAM system.
CITATION STYLE
Pan, L., Tian, F., Ying, W., & She, B. (2019). Monocular Visual-Inertial SLAM with Camera-IMU Extrinsic Automatic Calibration and Online Estimation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11743 LNAI, pp. 706–721). Springer Verlag. https://doi.org/10.1007/978-3-030-27538-9_61
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