activity
20172022
most citedLIC-Fusion: LiDAR-Inertial-Camera Odometry

10 citations · 33 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CV20221 cited

High-Quality RGB-D Reconstruction via Multi-View Uncalibrated Photometric Stereo and Gradient-SDF

Lu Sang, Bjoern Haefner, Xingxing Zuo +1

Fine-detailed reconstructions are in high demand in many applications. However, most of the existing RGB-D reconstruction methods rely on pre-calculated accurate camera poses to re…

cs.RO2022

Observability-Aware Intrinsic and Extrinsic Calibration of LiDAR-IMU Systems

Jiajun Lv, Xingxing Zuo, Kewei Hu +3

Accurate and reliable sensor calibration is essential to fuse LiDAR and inertial measurements, which are usually available in robotic applications. In this paper, we propose a nove…

cs.RO20226 cited

Online Self-Calibration for Visual-Inertial Navigation Systems: Models, Analysis and Degeneracy

Yulin Yang, Patrick Geneva, Xingxing Zuo +1

In this paper, we study in-depth the problem of online self-calibration for robust and accurate visual-inertial state estimation. In particular, we first perform a complete observa…

cs.RO20211 cited

CLINS: Continuous-Time Trajectory Estimation for LiDAR-Inertial System

Jiajun Lv, Kewei Hu, Jinhong Xu +3

In this paper, we propose a highly accurate continuous-time trajectory estimation framework dedicated to SLAM (Simultaneous Localization and Mapping) applications, which enables fu…

cs.CV2021

MBA-VO: Motion Blur Aware Visual Odometry

Peidong Liu, Xingxing Zuo, Viktor Larsson +1

Motion blur is one of the major challenges remaining for visual odometry methods. In low-light conditions where longer exposure times are necessary, motion blur can appear even for…

cs.RO20205 cited

LIC-Fusion 2.0: LiDAR-Inertial-Camera Odometry with Sliding-Window Plane-Feature Tracking

Xingxing Zuo, Yulin Yang, Patrick Geneva +4

Multi-sensor fusion of multi-modal measurements from commodity inertial, visual and LiDAR sensors to provide robust and accurate 6DOF pose estimation holds great potential in robot…