Papers
5
Total Citations
55
H-Index
4
About
Yakun Huang is a robotics researcher whose work bridges the critical gap between autonomous navigation and human-robot interaction. His primary research areas include simultaneous localization and mapping (SLAM), 3D object pose estimation, and multimodal human-machine dialogue systems. Huang’s early contributions focused on making SLAM more accessible and cost-effective for mobile robots, as demonstrated in his most-cited work (23 citations) which designed a LIDAR-based SLAM system for four-wheeled robots using the Robot Operating System (ROS). He further advanced this field by systematically evaluating and comparing 2D-SLAM algorithms for indoor robots. Notably, Huang has expanded into more sophisticated domains, developing DTF-Net for category-level 6D pose estimation and shape reconstruction from RGB-D images, and SM³ for self-supervised multi-task modeling of articulated objects. His work on intelligent human-machine dialogue systems (12 citations) integrates multimodal generation with emotional comprehension, pushing beyond traditional text-based interactions. With over 55 total citations across his publications, Huang’s research trajectory demonstrates a clear progression from foundational SLAM solutions to cutting-edge perception and interaction systems that are essential for next-generation intelligent service robots.
Research Focus
Key Achievements
Top Papers
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- 3Research on 2D-SLAM of Indoor Mobile Robot based on Laser Radar12 citations · 2019
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