Zhengyan Chang

Taiyuan University of Science and Technology

Papers

Total Citations

H-Index

About

Zhengyan Chang is a researcher specializing in intelligent transportation systems and automation, with a particular focus on the application of artificial potential field methods to industrial machinery. Their most-cited work, "Route planning of intelligent bridge cranes based on an improved artificial potential field method" (2021, 11 citations), pioneers the adaptation of path planning algorithms—traditionally used for driverless cars and mobile robots—to the obstacle avoidance and autonomous navigation of bridge cranes. This contribution addresses a critical gap in industrial automation, enhancing safety and efficiency in material handling. By refining the artificial potential field method to account for crane-specific constraints, Chang has opened new avenues for smart manufacturing and logistics. Their research bridges robotics and heavy machinery, offering practical solutions for real-world industrial environments. With a growing citation record, Chang's work is gaining recognition among engineers and researchers seeking to automate complex, high-risk tasks. Their innovative approach underscores a commitment to advancing intelligent systems in traditionally manual sectors, making them a notable figure in the field of industrial automation and robotics.