Xue Iuan Wong

University at Buffalo, State University of New York

Papers

Total Citations

H-Index

About

Xue Iuan Wong is a robotics researcher whose work focuses on advancing localization and mapping technologies for autonomous systems, particularly in challenging field environments. His most-cited paper, "Extended Kalman Filter for Stereo Vision-Based Localization and Mapping Applications" (2017, 15 citations), makes a significant contribution to simultaneous localization and mapping (SLAM) by integrating stereo vision with extended Kalman filtering. Wong's approach exploits the continuity of image features and builds upon point correspondence tracking algorithms to deliver instantaneous, robust localization solutions—a critical capability for field robotics operating in GPS-denied or unstructured settings. This work addresses fundamental challenges in autonomous navigation, enabling robots to maintain accurate spatial awareness using only visual data. While his citation count reflects a focused, emerging impact, Wong's research sits at the intersection of computer vision, sensor fusion, and mobile robotics, offering practical frameworks for real-world deployment. His contributions are particularly relevant for applications in agricultural robotics, search-and-rescue operations, and planetary exploration, where reliable visual SLAM is essential for mission success.