Zhiyong Liao

National University of Defense Technology

Papers

Total Citations

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About

Zhiyong Liao is a researcher advancing the intersection of robotics, semantic mapping, and knowledge representation. His primary research areas include topological scene understanding, indoor environment modeling, and the integration of knowledge graphs into robotic systems. Liao’s major contribution is the development of the Topological Scene Map (TSM), a novel semantic mapping framework that combines behavioral topological maps with scene graphs to enable comprehensive indoor environment understanding. This work, published in 2020, has garnered 8 citations and addresses a critical need in robotics: achieving rich, structured scene representation for tasks like navigation and human-robot interaction. Additionally, his 2019 review on knowledge graphs in robotics, with 2 citations, synthesizes how structured knowledge can enhance robot reasoning and decision-making. Liao’s research bridges the gap between low-level spatial data and high-level semantic understanding, offering practical tools for more intelligent and context-aware robots. His work is particularly notable for its focus on topological structures, which provide efficient and scalable representations for real-world deployment.