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Xingxing Zuo
Researcher at Zhejiang University
Publications - 33
Citations - 586
Xingxing Zuo is an academic researcher from Zhejiang University. The author has contributed to research in topics: Computer science & Inertial measurement unit. The author has an hindex of 8, co-authored 19 publications receiving 215 citations. Previous affiliations of Xingxing Zuo include ETH Zurich.
Papers
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Proceedings ArticleDOI
Robust visual SLAM with point and line features
TL;DR: The orthonormal representation is employed as the minimal parameterization to model line features along with point features in visual SLAM and analytically derive the Jacobians of the re-projection errors with respect to the line parameters, which significantly improves the SLAM solution.
Proceedings ArticleDOI
LIC-Fusion: LiDAR-Inertial-Camera Odometry
TL;DR: LiDAR-inertial camera fusion (LIC-Fusion) as discussed by the authors performs online spatial and temporal sensor calibration between all three asynchronous sensors, in order to compensate for possible calibration variations.
Posted Content
LIC-Fusion 2.0: LiDAR-Inertial-Camera Odometry with Sliding-Window Plane-Feature Tracking
TL;DR: This paper develops a sliding-window filter based LiDAR-Inertial-Camera odometry with online spatiotemporal calibration with LIC-Fusion 2.0, and performs the observability analysis for the IMU-LiDAR subsystem under consideration and reports the degenerate cases for spatiotmporal calibration using plane features.
Journal ArticleDOI
Visual-Inertial Localization With Prior LiDAR Map Constraints
TL;DR: A low-cost stereo visual-inertial localization system, which leverages efficient multi-state constraint Kalman filter (MSCKF)-based visual- inertial odometry while utilizing an a priori LiDAR map to provide bounded-error three-dimensional navigation.
Posted Content
LIC-Fusion: LiDAR-Inertial-Camera Odometry
TL;DR: The proposed LIC-Fusion outperforms the state-of-the-art visual-inertial odometry (VIO) and LiDAR odometry methods in terms of estimation accuracy and robustness to aggressive motions.