Yuekai Liu

Southwest Jiaotong University, Guizhou Electric Power Design and Research Institute

Papers

Total Citations

257

H-Index

About

Yuekai Liu is a leading researcher in computer vision and robotics, with a primary focus on semantic simultaneous localization and mapping (SLAM) and deep learning for autonomous navigation in complex environments. His most impactful contribution is the development of YOLO-SLAM, a pioneering semantic SLAM system that integrates object detection with geometric constraints to robustly handle dynamic scenes. This work, published in 2022, has already garnered over 255 citations, reflecting its significant influence on advancing SLAM technology beyond static assumptions. Liu’s research also addresses practical challenges in power line inspection, where he applied deep learning to detect obstacles under variable lighting and scale conditions in mountainous terrain. His work bridges the gap between theoretical computer vision and real-world robotic applications, particularly in infrastructure maintenance. By combining semantic understanding with geometric reasoning, Liu has helped enable more reliable autonomous systems for unstructured environments, making his contributions highly relevant for researchers working on field robotics, autonomous driving, and visual perception.