Papers
23
Total Citations
1,035
H-Index
11
About
Huijun Gao is a prolific researcher whose work spans control systems theory, robotics, and signal processing, with particular expertise in multi-agent systems, filtering, and autonomous robot applications. His foundational contributions to stochastic and networked control systems are evidenced by his highly cited work on leader-following consensus in delayed multi-agent systems (310 citations) and finite-horizon H∞ filtering with missing measurements and quantization effects (226 citations), both of which have become important references in robust control literature. Gao has also made significant strides in mobile robotics, developing two time-scale tracking control strategies for nonholonomic wheeled mobile robots (149 citations) that improve transient performance under real-world disturbances. More recently, his research has expanded into industrial automation and human-robot interaction, including autonomous spray painting systems, augmented reality-based teleoperation for ultrasound procedures, and trajectory tracking of variable centroid objects using vision-force fusion. His computationally relaxed Unscented Kalman Filter addresses critical real-time constraints in autonomous vehicles and advanced robotics. With a body of work totaling hundreds of citations across diverse domains, Gao represents a versatile and influential voice bridging theoretical control engineering and cutting-edge robotic applications.
Research Focus
Key Achievements
Top Papers
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- 3Two Time-Scale Tracking Control of Nonholonomic Wheeled Mobile Robots149 citations · 2016
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- 7Computationally Relaxed Unscented Kalman Filter30 citations · 2022
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