Papers
12
Total Citations
94
H-Index
6
About
Tran Thien Huan is a leading researcher in bipedal and humanoid robotics, specializing in gait generation, optimization, and stable locomotion control. His core contributions lie in developing novel optimization algorithms—including Modified Differential Evolution, Central Force Optimization, Jaya, and Particle Swarm Optimization—to solve the complex constrained optimization problems inherent in biped walking. His work has produced adaptive and nature-inspired gait generators that enable humanoid robots to walk stably and naturally, with over 28 citations for his pioneering 2018 paper on adaptive evolutionary neural models. Huan has also advanced balance control through flywheel-based systems and adaptive fuzzy sliding mode control for nonlinear robot systems, demonstrating versatility across pneumatic artificial muscle actuators. His research consistently bridges theoretical optimization with practical robotic implementation, as seen in his multi-objective Jaya algorithm for gait planning. With a cumulative citation impact exceeding 90 across his most-cited works, Huan’s innovations in stable, optimal gait generation continue to influence the design of more agile and reliable humanoid robots for real-world applications.
Research Focus
Key Achievements
Top Papers
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- 5Stable Gait Optimization for Small-Sized Humanoid Robot Using CFO8 citations · 2018
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- 8Advanced Flywheel-based Balance for Biped Robot Stably Walking3 citations · 2022
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