Hang-Tian Zhang

Chengdu University of Information Technology

Papers

Total Citations

H-Index

About

Hang-Tian Zhang is a robotics researcher specializing in simultaneous localization and mapping (SLAM), with a particular focus on lidar-inertial odometry and dynamic environment perception. His most notable work, "An improved LIO-SAM lidar inertial odometer with dynamic point filtering" (2024), addresses a critical limitation in the widely-used LIO-SAM algorithm by integrating dynamic point filtering and Iris loop detection to enhance robustness in cluttered, moving environments. This contribution improves trajectory estimation and mapping accuracy for mobile robots operating in real-world conditions, where static scene assumptions often fail. Though early in his career—with his primary paper accumulating 3 citations to date—Zhang’s work demonstrates a clear trajectory toward advancing SLAM reliability in dynamic settings. His research bridges the gap between theoretical SLAM frameworks and practical deployment challenges, making it relevant for autonomous navigation, field robotics, and intelligent transportation systems. Zhang’s focus on filtering dynamic objects and improving loop closure detection positions him as an emerging contributor to the next generation of robust, real-time localization systems.