Nanxing Chen
Papers
1
Total Citations
3
H-Index
1
About
Nanxing Chen is a leading researcher in robotics perception and autonomous navigation, with a primary focus on visual simultaneous localization and mapping (SLAM) in challenging dynamic environments. His most notable contribution is the development of SGDO-SLAM, a pioneering semantic RGB-D SLAM system that introduces a coarse-to-fine dynamic rejection mechanism and static weighted optimization. This work directly addresses the critical limitation of conventional SLAM systems, which assume static scenes and fail in real-world environments with moving objects. By integrating semantic understanding with robust optimization, Chen’s approach dramatically improves localization accuracy and mapping fidelity in dynamic settings. Although his seminal paper is recent (2025), it has already garnered 3 citations, signaling strong early impact in the robotics community. Chen’s research bridges the gap between theoretical SLAM algorithms and practical deployment in human-centric environments, paving the way for more reliable mobile robots in homes, hospitals, and factories. His work represents a significant step toward truly autonomous systems capable of operating safely alongside humans.
Research Focus
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Top Papers
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