Qiying Wang

Papers

Total Citations

154

H-Index

About

Qiying Wang is a researcher whose work centers on autonomous navigation, sensor fusion, and robotics, with particular expertise in integrating GPS and inertial navigation systems (INS) for precise positioning. His research addresses a fundamental challenge in autonomous systems: achieving reliable, accurate localization in complex real-world environments where individual sensors are insufficient on their own. Wang's most significant contribution is his development of adaptive fuzzy Kalman filtering for sensor fusion, a technique that intelligently combines complementary sensor data to overcome the limitations of each individual system. His 2003 paper introducing this method, validated in a three-dimensional environment, has garnered 98 citations, reflecting its lasting influence on the field. Alongside this, his work on low-cost automation using INS/GPS data fusion—cited 56 times—demonstrates a practical commitment to making accurate positioning accessible for industrial and outdoor applications, including autonomous vehicles and robotic manipulators. Wang's contributions are particularly valuable to engineers and researchers seeking affordable yet reliable navigation solutions. His dual focus on theoretical rigor and real-world applicability has made his work a meaningful reference point for those advancing autonomous systems in both factory and field settings.