Jingzhe Fang

Chinese Academy of Sciences, Shenyang Institute of Automation

Papers

Total Citations

H-Index

About

Jingzhe Fang is a robotics researcher whose work centers on the practical realization of autonomous systems, with key contributions in 3D simulation and intelligent control. Fang’s research addresses two critical challenges in modern robotics: the rapid visualization of robotic systems and the precise control of mobile platforms. In their highly cited work on “Fast Realization of Robot 3D Simulation Based on WebGL,” Fang pioneered an approach that leverages the Three.js library to enable browser-based, real-time 3D simulation of robotic arms—a breakthrough that makes complex robotic modeling accessible without specialized hardware. This work has garnered attention for its efficiency and accessibility. Complementing this, Fang’s research on “Path-tracking of Mobile Robot Using PD-type Iterative Learning Control with Forgetting Factor” introduces a novel discrete iterative learning control strategy that enhances trajectory tracking accuracy for mobile robots operating on repeated paths. By incorporating a forgetting factor into the PD-type controller, Fang’s method improves robustness against disturbances and initial errors. With both papers accumulating citations in 2023, Fang is establishing a reputation for developing practical, computationally efficient solutions that bridge simulation and real-world control, making significant strides toward more agile and reliable autonomous systems.