Xujie Li

Shandong University of Science and Technology

Papers

Total Citations

H-Index

About

Xujie Li is a researcher in robotics and intelligent control systems, with a primary focus on kinematic modeling and neural network applications for service robots. Their most cited work, "Neural network method for robot arm of service robot based on D-H model" (2017, 8 citations), introduces a radial basis function neural network to solve the inverse kinematics of a 4-degree-of-freedom manipulator. By integrating the Denavit-Hartenberg (D-H) model with neural computation, Li established a forward kinematic framework that maps the transition relations between connecting rods, enabling more precise and adaptive control for service robots. This contribution addresses a critical challenge in robotics—achieving accurate arm movement without complex analytical solutions—making it valuable for real-world applications in assistive and domestic robotics. While Li’s citation count reflects a focused, emerging impact, the work demonstrates a practical synthesis of classical robotics theory and modern machine learning, offering a foundation for further research in adaptive robot control. Li’s approach exemplifies how neural networks can simplify traditional kinematic problems, paving the way for more intuitive and flexible robotic systems in human-centered environments.