Papers
11
Total Citations
121
H-Index
7
About
Kuo-Ho Su is a robotics and intelligent control researcher whose work sits at the intersection of fuzzy logic, neural networks, and autonomous systems. His most significant contributions center on two-wheeled robot stabilization and control, where he pioneered neural-fuzzy and adaptive fuzzy sliding-mode approaches to tackle the inherent instability and nonlinearity of such platforms. His 2010 paper on neural-fuzzy-based controllers for autonomously driven wheeled robots stands as his most influential work, accumulating 40 citations and establishing a foundational framework that informed subsequent studies on balance control and robust tracking under real-world disturbances such as bumpy terrain. Beyond mobile robotics, Su has extended intelligent control methods to robotic grasping grippers, integrating pressure sensing and smart fuzzy controllers to enable adaptive manipulation, as well as to autonomous path planning, developing fuzzy-inference-based systems capable of dynamic obstacle avoidance in real time. His breadth is further demonstrated by contributions to ship stabilization through heuristic genetic optimization and, more recently, smart medical care systems for elderly facilities. With a total of over 110 citations across his published work, Su's research consistently demonstrates the practical power of soft-computing techniques in solving complex, uncertain engineering problems.
Research Focus
Key Achievements
Top Papers
- 1
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- 3Development of Robotic Grasping Gripper Based on Smart Fuzzy Controller15 citations · 2015
- 4Balance control for two-wheeled robot via neural-fuzzy technique11 citations · 2010
- 5Robot path planning and smoothing based on fuzzy inference10 citations · 2014
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- 7Dynamic path planning under randomly distributed obstacle environment7 citations · 2014
- 8Adaptive fuzzy balance controller for two-wheeled robot5 citations · 2012
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