Papers
5
Total Citations
32
H-Index
4
About
Hao Guan is a robotics researcher whose work spans wheeled mobile robots, hydraulic quadruped systems, and humanoid facial mechanisms. His primary research areas include adaptive neural network control, disturbance observer design, and trajectory planning for autonomous robots operating in uncertain environments. Guan’s most influential contribution is his 2014 paper on wheeled mobile robot RBFNN dynamic surface control based on a disturbance observer (16 citations), where he developed a nonlinear observer to compensate for external disturbances and used neural networks to handle uncertain parameters—a key advancement for robust mobile robot navigation. He has also made notable contributions to hydraulic quadruped robots, studying precise position recognition and control methods for single-leg joints to meet varying motion-stage requirements. Earlier work includes the mechanical design of a humanoid robot head using Pro/E and fuzzy control integration for obstacle avoidance in unknown environments. Guan’s research on museum robot trajectory planning further demonstrates his interest in practical applications, combining cameras, infrared sensors, and MP3 modules for autonomous commentary and motion. With a career spanning over a decade, his work continues to influence adaptive control strategies for mobile and legged robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Mechanism Design of a Facial Robot4 citations · 2011
- 4
- 5Study on Museum Robot Trajectory Planning Based on the Controlled Path2 citations · 2013