Jingnan Liu
Papers
4
Total Citations
153
H-Index
4
About
Jingnan Liu is a prominent researcher specializing in multi-sensor fusion and robust state estimation for autonomous navigation systems. His work sits at the intersection of inertial navigation, computer vision, LiDAR sensing, and GNSS technologies, with a particular focus on developing reliable navigation solutions for robotics platforms operating in challenging real-world environments. Liu's most influential contribution is IC-GVINS, an INS-centric GNSS-visual-inertial navigation system that has garnered 106 citations since its 2022 publication. This framework innovatively places the inertial navigation system at the core of the architecture, significantly improving robustness against the environmental vulnerabilities that plague purely visual systems. His subsequent work, LE-VINS, extends this philosophy by integrating solid-state LiDAR to enhance depth estimation for visual landmarks, addressing critical failure modes in visually degraded scenes such as poor lighting or weak texture environments. Earlier foundational work on hybrid sliding window optimization for tightly-coupled visual-inertial systems demonstrates Liu's long-standing commitment to advancing state estimation theory. Collectively accumulating over 150 citations, his research meaningfully advances the field of autonomous robot navigation, offering practical, deployable solutions for wheeled robots and other low-speed platforms navigating complex, unstructured environments.
Research Focus
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