Xiaoyan Gu

Papers

Total Citations

H-Index

About

Xiaoyan Gu’s research centers on environment perception and computer vision, with a particular focus on enabling robots to better understand and navigate indoor spaces. Her most cited work, “Dynamic image stitching for moving object” (2016), addresses a critical challenge in robotics: creating a seamless, wide-angle view of a dynamic environment using low-cost image sensors. By developing methods to stitch multiple images while accounting for moving objects, Gu’s research helps robots achieve a more complete and stable global perception of their surroundings—a foundational step for autonomous navigation and control. Though her citation count is modest (8 citations for this key paper), the work represents a practical contribution to affordable, real-time environmental sensing. Gu’s research sits at the intersection of robotics, image processing, and intelligent systems, offering solutions that enhance how machines perceive and interact with the world. Her work is particularly valuable for students and researchers interested in low-cost perception systems, visual SLAM, or indoor robotics applications.