Yeqing Yan

Papers

Total Citations

H-Index

About

Yeqing Yan’s research focuses on industrial robotics, with key contributions in human-robot interaction and vision-based automation. His most cited work, “Design and Implementation of Teach Pendant for Six Degrees of Freedom Industrial Robot” (2015, 8 citations), introduces a user-friendly touchscreen interface for on-site robot commissioning and monitoring, enabling intuitive command input and function selection—a practical advancement for real-world deployment. In a related study (2016, 2 citations), Yan developed an automatic positioning system using monocular vision, employing efficient localization algorithms to help industrial robots accurately grasp target objects. While his citation counts are modest, these works address foundational challenges in robot usability and precision, reflecting a hands-on engineering approach. Yan’s contributions are notable for bridging hardware design with algorithmic efficiency, offering accessible solutions for industrial automation. His research is particularly relevant for students and engineers seeking to understand the integration of vision systems and user interfaces in robotic platforms, demonstrating how targeted innovations can enhance operational reliability and ease of use in manufacturing environments.