Kaiyang Xu

Harbin University of Science and Technology

Papers

Total Citations

H-Index

About

Kaiyang Xu is a researcher at the frontier of medical robotics and computer vision, with a primary focus on advancing surgical navigation through deep learning and simultaneous localization and mapping (SLAM) technologies. His most cited work, "Semantic SLAM Based on Deep Learning in Endocavity Environment" (2022, 18 citations), addresses a critical challenge in minimally invasive surgery: the restricted field of view in traditional endoscopic procedures. By integrating semantic understanding into SLAM systems, Xu has pioneered methods that enable robots to intelligently map and navigate complex, confined anatomical spaces—such as lumens and cavities—using only endoscopic video sequences. This contribution is pivotal for the next generation of robot-assisted laparoscopic techniques, enhancing both visualization and autonomy during surgery. Xu’s research bridges the gap between deep learning perception and real-time robotic control, offering tangible improvements in surgical precision and safety. His work has already garnered attention from the medical robotics community, and his innovations hold promise for transforming how surgeons interact with internal environments during minimally invasive procedures.