Papers
17
Total Citations
523
H-Index
7
About
Guanzheng Tan is a versatile researcher whose work spans robotics, artificial intelligence, and speech processing, with particular expertise in mobile robot navigation, swarm intelligence, and emotion recognition in speech. His early contributions to autonomous robotics are among his most enduring: his 2007 paper on applying the Ant Colony System algorithm to real-time globally optimal path planning for mobile robots garnered 133 citations, while related work from 2006 on hybrid Dijkstra and ant system approaches further cemented his standing in the field. Tan's research portfolio also reflects a sustained interest in biomedical robotics, including foundational reviews of prosthetic limb development and dynamic walking mechanics for biped robots. Pivoting toward machine learning applications, his 2017 study combining feature selection with an Extreme Learning Machine decision tree for speech emotion recognition became his most-cited work, accumulating 260 citations and demonstrating meaningful advances in speaker-independent affective computing. More recently, his 2024 exploration of deep reinforcement learning for mapless navigation in industrial autonomous mobile robots signals a continued evolution toward cutting-edge AI-driven robotics. Across more than two decades, Tan has built a cohesive body of work connecting intelligent navigation, human-robot interaction, and signal processing.
Research Focus
Key Achievements
Top Papers
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- 9Swarm-robot grid distribution and motion in complicated environment5 citations · 2008
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