Guangtao Shang

Nanjing University of Information Science and Technology

Papers

Total Citations

303

H-Index

About

Guangtao Shang is a leading researcher in the field of autonomous robotics, with a primary focus on Simultaneous Localization and Mapping (SLAM) technology. His work bridges the critical gap between traditional sensor-based approaches and modern semantic understanding, addressing fundamental challenges in enabling robots to navigate complex, unstructured environments. Shang’s major contributions include comprehensive surveys that have shaped the research landscape: his 2022 overview on Visual SLAM, which traces the evolution from classical geometric methods to semantic-rich systems, has garnered 202 citations for its systematic analysis of failure modes in challenging environments. He has further advanced the field by synthesizing heterogeneous sensor fusion strategies, as seen in his 2022 work on integrating LIDAR and visual data (69 citations), and by pioneering frameworks for multi-robot collaborative SLAM (2023, 32 citations) that tackle scalability, error accumulation, and computational load in large-scale mapping. Through these influential reviews, Shang has provided the research community with essential roadmaps for developing more robust, efficient, and intelligent autonomous systems, making his work indispensable reading for students and engineers working on next-generation mobile robotics.