Papers
12
Total Citations
242
H-Index
7
About
Hang Wu is a versatile robotics researcher whose work spans mobile robot design, brain-computer interfaces (BCIs), and human-robot interaction. Based at the intersection of mechanical engineering and intelligent systems, Wu has made significant contributions to adaptive robot locomotion, rehabilitation robotics, and neural control of robotic systems. Wu's most influential work, a 2017 study on transformable wheel-legged mobile robots (119 citations), demonstrated innovative solutions for navigating complex terrains by integrating wheeled and legged locomotion — a landmark contribution to mobile robotics. Complementing this, his research on visual terrain classification and suspension mechanisms for rescue robots further advances autonomous navigation capabilities. In the domain of BCIs, Wu has pioneered shared control frameworks for brain-actuated robotic grasping, addressing the formidable challenge of controlling high-degree-of-freedom robotic systems through neural signals alone. His Fused Fuzzy Petri Nets approach and asynchronous BCI systems have each garnered strong scholarly attention. More recently, his work on gait recognition for lower limb exoskeletons reflects a growing focus on rehabilitation applications. Wu's diverse portfolio — totaling over 230 citations — reflects a researcher steadily bridging theoretical robotics with practical, human-centered applications, making his work particularly valuable to students in rehabilitation engineering, autonomous systems, and neural interfaces.
Research Focus
Key Achievements
Top Papers
- 1A transformable wheel-legged mobile robot: Design, analysis and experiment119 citations · 2017
- 2
- 3Asynchronous brain-computer interface shared control of robotic grasping23 citations · 2019
- 4
- 5
- 6An intermediate point obstacle avoidance algorithm for serial robot13 citations · 2018
- 7
- 8
- 9An Asynchronous Mi-Based BCI for Brain-Actuated Robot Grasping Control3 citations · 2017
- 10