Yaojie Zhang

Chinese Academy of Sciences, University of Chinese Academy of Sciences

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About

Yaojie Zhang is a robotics researcher specializing in multi-sensor fusion, simultaneous localization and mapping (SLAM), and multi-robot localization systems. His work addresses critical challenges in autonomous navigation, particularly in complex or GPS-denied environments. Zhang’s key contribution includes developing an adaptive factor weight adjustment method for multi-sensor SLAM, which dynamically modifies factor weights in graph optimization to improve localization and mapping robustness under adverse conditions. He has also advanced multi-robot global localization by introducing a neighbor-constraint approach that enables accurate position estimation without prior knowledge of robot poses, solving the difficult data association problem between different robot viewpoints. While his work is still early in its citation lifecycle—with his most-cited paper “Adaptive Adjustment of Factor’s Weight for a Multi-Sensor SLAM” (2023) accumulating 3 citations and “Robust Multi-Robot Global Localization” (2024) reaching 2 citations—these publications represent foundational contributions to resilient autonomous navigation. Zhang’s research is particularly relevant for applications in search-and-rescue, industrial automation, and field robotics, where robust localization under uncertainty is paramount.