Lantian Zhang

State Key Laboratory of Remote Sensing Science

Papers

Total Citations

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About

Lantian Zhang is an emerging researcher specializing in robotics perception, autonomous navigation, and 3D scene understanding, with a particular focus on LiDAR-based sensing systems for mobile robots operating in complex, real-world environments. Zhang's work addresses critical challenges at the intersection of simultaneous localization and mapping (SLAM) and deep learning-based scene comprehension. Among Zhang's most notable contributions is research on semantic-constrained LiDAR SLAM in dynamic environments, which tackles a fundamental limitation of traditional SLAM systems — their susceptibility to pose estimation errors caused by moving objects. This work, which has accumulated 10 citations since its 2021 publication, represents a meaningful step toward deploying reliable robotic navigation in realistic, unpredictable settings. Zhang has also made strides in real-time panoptic segmentation using spatiotemporal sequential data fusion, unifying semantic and instance segmentation within a single framework to enable fast, accurate scene understanding for autonomous systems. Published in 2022 and already garnering 7 citations, this work highlights Zhang's commitment to practical, efficient solutions for robot perception. Together, these contributions position Zhang as a promising voice in the robotics and autonomous systems research community.