Xiaofeng Wang

East China University of Science and Technology

Papers

Total Citations

H-Index

About

Xiaofeng Wang is a robotics researcher whose work centers on intelligent motion planning and control systems for robotic manipulators. His most recognized contribution focuses on developing obstacle avoidance strategies and methods for the UR (Universal Robots) manipulator, addressing one of the fundamental challenges in deploying robotic arms within complex, real-world environments. In this 2021 study, Wang investigated algorithmic approaches for enabling six-degree-of-freedom manipulators to navigate safely and efficiently around obstacles, directly targeting limitations that hinder operational performance in industrial and collaborative robotics settings. By tackling the intersection of path planning, kinematics, and environmental awareness, his research contributes to making robotic systems more adaptive and capable in dynamic workspaces. While his work is in its early stages of accumulating citations, with his obstacle avoidance paper garnering 2 citations, Wang's research addresses genuinely pressing problems in modern robotics — particularly as collaborative robots become increasingly integrated into manufacturing and automation workflows. His efforts reflect a broader commitment to advancing the practical intelligence and reliability of robotic arm systems for next-generation applications.