Papers
5
Total Citations
67
H-Index
5
About
Cheng-Hung Chen is a leading researcher in intelligent robotics and soft computing, whose work bridges the gap between autonomous navigation and bio-inspired control systems. His primary research areas include mobile robot control, fuzzy logic systems, and evolutionary optimization algorithms. Chen’s most significant contribution is the development of a fuzzy logic controller enhanced by reinforcement learning and an improved differential search algorithm, which achieved robust wall-following behavior in mobile robots—a foundational study cited 25 times. He further advanced the field with a knowledge-based neural fuzzy controller (KNFC) for navigation, integrating cultural multi-strategy differential evolution to optimize performance, earning 18 citations. His interdisciplinary work extends to biomedical engineering, where he applied particle swarm optimization to leukocyte adhesion molecules and control strategies for smart prosthetic hands (13 citations), demonstrating the versatility of his optimization techniques. Chen’s modified optimal control strategy for a five-finger robotic hand improved accuracy and convergence time, showcasing his impact on dexterous manipulation. With a career spanning over a decade, his adaptive fuzzy neural networks and multi-strategy artificial bee colony algorithms continue to shape autonomous systems, making him a pivotal figure in intelligent robotics and computational intelligence.
Research Focus
Key Achievements
Top Papers
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- 4A Modified Optimal Control Strategy for a Five-Finger Robotic6 citations · 2014
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