Bingzheng Yan

National University of Defense Technology

Papers

Total Citations

H-Index

About

Bingzheng Yan’s research lies at the intersection of computer vision and robotics, with a particular focus on scene understanding and remote robotic control. In his widely cited 2017 review, Yan systematically examined the enduring challenge of indoor-outdoor scene classification—a problem that has resisted a one-size-fits-all solution for nearly two decades. His work synthesized diverse approaches, from image retrieval to robot navigation, providing a critical roadmap for researchers tackling general scene classification. With 14 citations, this review remains a foundational reference for those seeking to bridge the gap between visual perception and real-world application. Yan also made notable contributions to robotics through the development of HiBot, a generic ROS-based framework for remote robot control. Addressing the growing complexity of multi-robot systems, HiBot offered a scalable, modular architecture that simplified task deployment and application management. This work, though early in its citation trajectory, reflects Yan’s commitment to practical, interoperable solutions in automation. His research demonstrates a clear arc: from understanding how machines “see” their environment to enabling them to act within it. For students and researchers, Yan’s work offers a compelling example of how foundational vision problems can directly inform the design of intelligent, remotely operated robotic systems.