Zhixin Zhan

Papers

Total Citations

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About

Zhixin Zhan has advanced the field of robotic vision and intelligent control through focused work on automated billiards systems. His research centers on multi-objective recognition, dynamic modeling, and fuzzy neural network applications for robotic manipulation in complex, real-time environments. Zhan’s most cited work, “Design of an efficient multi-objective recognition approach for 8-ball billiards vision system” (2018), has garnered 10 citations, reflecting its practical impact on computer vision and robotics. In his earlier study, “Dynamic modeling based on fuzzy Neural Network for a billiard robot” (2016), he tackled the intricate motion laws of billiards by developing a fuzzy neural network model to predict the cue ball’s final position after stroking and collision. This work established a collision coordinate system to precisely describe ball trajectories, addressing a core challenge in robotic sports. Zhan’s contributions demonstrate a unique blend of theoretical modeling and applied engineering, offering valuable insights for researchers in robotics, artificial intelligence, and autonomous systems. His achievements highlight the potential of intelligent algorithms to master dynamic, unpredictable tasks—a significant step toward more adaptive and capable robots.