KE Xi-lin

Xi'an Railway Survey and Design Institute

Papers

Total Citations

H-Index

About

Ke Xi-lin is a researcher whose work sits at the intersection of computer vision, robotics, and spatial intelligence, with a particular focus on advancing SLAM (Simultaneous Localization and Mapping) technology. Their most cited paper, "3D Scene Localization and Mapping Based on Omnidirectional SLAM" (2021), addresses a critical challenge in autonomous navigation: improving the accuracy of multi-view SLAM for robots and unmanned vehicles. By integrating omnidirectional imaging with traditional SLAM frameworks, Xi-lin’s work enhances the robustness of 3D scene reconstruction and localization, offering a wider field of view and more reliable mapping in complex environments. This contribution is foundational for applications ranging from autonomous driving to robotic exploration. With 6 citations, this paper has already garnered attention in the growing field of omnidirectional vision-based navigation. Xi-lin’s research directly tackles the practical limitations of existing SLAM models, making their work highly relevant for students and engineers developing next-generation autonomous systems. Their focus on fusing novel imaging techniques with established algorithms positions them as a promising contributor to the future of spatial AI and robotics.