Xiqing Zhang

Shanxi Transportation Research Institute

Papers

Total Citations

H-Index

About

Xiqing Zhang is a leading researcher in robotics and intelligent control systems, with a primary focus on advancing path planning algorithms for manipulators operating in complex, obstacle-dense environments. Their most notable contribution is the development of the HP-APF-RRT* algorithm, an improved variant of the Rapidly-exploring Random Tree (RRT*) method, specifically designed to address critical challenges in six-degree-of-freedom robotic arms, such as low sampling efficiency and path search failures in three-dimensional multi-obstacle spaces. This work, published in 2025 and already garnering 8 citations, demonstrates Zhang’s ability to solve practical, high-impact problems in automation and industrial robotics. By integrating artificial potential fields with RRT*, Zhang’s algorithm enhances both the speed and reliability of motion planning, making it highly relevant for applications in manufacturing, logistics, and autonomous systems. Their research not only pushes the boundaries of robotic dexterity but also provides a scalable framework for real-world deployment. As a rising scholar, Zhang’s innovative approach to algorithmic optimization continues to influence the next generation of intelligent robotic systems.