Yueyue Chen

Hangzhou Dianzi University, Huazhong University of Science and Technology

Papers

Total Citations

H-Index

About

Yueyue Chen is a robotics researcher whose work focuses on intelligent control, path planning, and multi-robot coordination. Her research spans three key areas: fuzzy control systems for unstable robots, optimal path planning for industrial automation, and distributed formation control for multi-robot teams. In her 2016 study on unicycle robots, Chen pioneered a Takagi-Sugeno (T-S) fuzzy control scheme that linearizes complex nonlinear dynamics using Lagrange modeling, enabling stable trajectory tracking through a parallel distributed compensator. Her 2020 work on robot shelf picking systems introduced an optimal path planning algorithm for 6-DOF robots, significantly improving warehouse automation efficiency by minimizing travel distances during order fulfillment. Most notably, her 2021 paper on multi-robot formation tracking proposed an innovative distance-based sensor self-calibration method that eliminates reliance on external positioning systems like optical motion capture, enabling truly autonomous swarm coordination. While each of her papers has garnered 3 citations, their practical contributions to robotics—from fuzzy logic control to industrial automation and decentralized swarm systems—demonstrate Chen’s versatility in addressing real-world robotic challenges. Her work continues to influence the development of more autonomous, efficient, and scalable robotic systems.