Yongqiang Han
Papers
2
Total Citations
5
H-Index
2
About
Dr. Yongqiang Han is a robotics researcher specializing in autonomous navigation and control for mobile robots operating in complex, uncertain environments. His primary research areas include belief space planning, stochastic control, and omnidirectional vehicle systems. Dr. Han’s major contribution lies in developing computationally efficient methods for motion planning under uncertainty, particularly for underwater robots. His most cited work introduces a covariance upper bound technique that dramatically speeds up Gaussian belief space planning, enabling real-time trajectory optimization for robots affected by spatially varying currents and landmark distributions. This work has garnered 3 citations and addresses a critical bottleneck in deploying autonomous underwater vehicles. Additionally, Dr. Han has advanced lane keeping control for Mecanum wheeled omnidirectional vehicles using laser scanners, a contribution cited 2 times that supports the growing demand for automated guided vehicles in manufacturing and logistics. His research bridges theoretical stochastic control with practical robotic systems, offering scalable solutions for robots navigating unpredictable environments. Dr. Han’s work is notable for its focus on real-world applicability, tackling challenges from underwater currents to factory floor navigation, and his methods hold promise for enhancing autonomy in diverse domains.
Research Focus
Key Achievements
Top Papers
- 1
- 2