Xiaoyan Wang

Xi'an University of Architecture and Technology

Papers

Total Citations

H-Index

About

Xiaoyan Wang’s research centers on computer vision and robotics, with a particular focus on simultaneous localization and mapping (SLAM) systems. Her most cited work, “Research on SLAM Road Sign Observation Based on Particle Filter,” tackles the critical challenge of enhancing visual target tracking robustness in complex environments. Wang’s contributions address the growing dependency of real-time tracking algorithms on hardware solutions, proposing innovative particle filter methods to improve SLAM road sign observation. Her work has garnered attention in the field, with this key paper accumulating 7 citations—a solid foundation for an emerging researcher. Wang’s investigations into how algorithms can adapt to diverse and unpredictable backgrounds are vital for advancing autonomous navigation and mobile robotics. By bridging theoretical particle filtering with practical SLAM applications, she is helping to build more reliable and efficient systems for real-world deployment. Her research trajectory promises further breakthroughs in making visual tracking more resilient, directly impacting the development of intelligent robots and autonomous vehicles.