Yunfeng Xiang

Papers

Total Citations

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About

Yunfeng Xiang is a researcher specializing in visual simultaneous localization and mapping (VSLAM), with a particular focus on enabling robust robot perception in dynamic indoor environments. His major contributions center on integrating semantic understanding with traditional SLAM frameworks to overcome challenges posed by moving objects and changing scenes. In his highly cited work "ATY-SLAM: A Visual Semantic SLAM for Dynamic Indoor Environments" (2023, 8 citations), Xiang introduces a novel approach that leverages semantic segmentation to filter out dynamic features, significantly improving localization accuracy and map consistency. He further advances the field with "A Closed-loop Detection Algorithm for Online Updating of Bag-Of-Words Model" (2023, 5 citations), which addresses the critical issue of drift in monocular VSLAM by enabling real-time vocabulary updates for more reliable loop closure. Additionally, his "AGAM-SLAM: An Adaptive Dynamic Scene Semantic SLAM Method Based on GAM" (2023, 5 citations) demonstrates an adaptive mechanism that adjusts to varying scene dynamics. Collectively, Xiang’s work has garnered early recognition, with over 18 citations, establishing him as an emerging voice in semantic SLAM and autonomous navigation for mobile robots.