Papers
82
Total Citations
1,059
H-Index
19
About
Guohui Tian is a prominent researcher in robotics, artificial intelligence, and autonomous systems, whose work has significantly advanced the capabilities of intelligent service robots in real-world environments. His research spans several interconnected domains, including indoor robot localization, semantic mapping, object search, task planning, and human-robot interaction through facial expression recognition. Among his most influential contributions is his development of robust indoor localization frameworks, notably a UWB-based system integrating EKF and EFIR filtering (51 citations), which substantially improved positioning accuracy for autonomous robots. Tian has also pioneered semantic and metric-topological mapping techniques that enable mobile robots to efficiently search for and interact with objects in dynamic home environments — a body of work collectively garnering over 100 citations. His probabilistic task planning frameworks, leveraging semantic knowledge and object-level maps, have further bridged the gap between perception and actionable robot behavior. Tian's interdisciplinary reach extends into deep learning, with a notable paper on dual-channel convolutional LSTM networks for facial expression recognition earning 87 citations — his most cited work to date. With a cumulative citation count exceeding 400, Tian's research represents a foundational contribution to the development of intelligent, context-aware service robots capable of operating autonomously in human-centered environments.
Research Focus
Key Achievements
Top Papers
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- 4Smart Obstacle Avoidance Using a Danger Index for a Dynamic Environment42 citations · 2019
- 5Building Metric-Topological Map to Efficient Object Search for Mobile Robot37 citations · 2021
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- 8Spatial semantic hybrid map building and application of mobile service robot34 citations · 2013
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