Hailiang Tang

Papers

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About

Hailiang Tang is a researcher specializing in multi-sensor fusion navigation systems, with a particular focus on integrating GNSS, visual, and inertial navigation technologies for autonomous robotics. His work centers on developing robust, real-time state estimation frameworks that push the boundaries of localization accuracy and system resilience in challenging environments. Tang's most recognized contribution to date is IC-GVINS, a novel INS-centric GNSS-Visual-Inertial Navigation System designed for wheeled robots, which has garnered 6 citations since its 2022 publication. This system distinguishes itself by deeply embedding precise inertial navigation system (INS) information into both state estimation and visual processing pipelines, significantly enhancing robustness compared to conventional approaches. His research addresses a critical challenge in autonomous systems: maintaining reliable navigation when individual sensors fail or produce degraded measurements. By architecting tightly coupled multi-sensor frameworks, Tang contributes to the foundational infrastructure needed for autonomous vehicles, field robots, and mobile mapping systems. As an emerging researcher in the navigation and robotics community, his work reflects growing momentum in the field of sensor fusion, positioning him as a promising contributor to next-generation autonomous navigation solutions.