Yi-Jan Hung
Papers
1
Total Citations
4
H-Index
1
About
Dr. Yi-Jan Hung is a robotics researcher whose work centers on intelligent control systems for legged locomotion, with a particular emphasis on hexapod robots. His most cited paper, "An Effective Hexapod Robot Control Design Based on a Fuzzy Neural Network and a Kalman Filter" (2018, 4 citations), introduces a novel control architecture that integrates fuzzy neural networks with Kalman filtering to achieve stable, adaptive walking. This design enables the robot to autonomously adjust its posture and maintain high stability while navigating alongside walls and avoiding obstacles—a significant step toward practical, real-world deployment of multi-legged robots in unstructured environments. Hung’s contribution lies in fusing soft computing with state estimation to create robust, sensor-driven locomotion. Though his citation count is modest, the work demonstrates a clear, applied impact in the field of bio-inspired robotics. His research offers a compelling foundation for students and engineers interested in bridging neural control, sensor fusion, and autonomous navigation in legged systems.
Research Focus
Key Achievements
Top Papers
- 1