Papers
3
Total Citations
77
H-Index
3
About
Yuan Xu is a researcher specializing in indoor mobile robot navigation, sensor fusion, and autonomous navigation systems. His work sits at the intersection of inertial navigation, wireless sensor networks, and advanced filtering algorithms, addressing one of robotics' most persistent challenges: achieving accurate, continuous localization in GPS-denied indoor environments. Xu's most influential contribution, "Improving ultrasonic-based seamless navigation for indoor mobile robots utilizing EKF and LS-SVM" (2016), has garnered 51 citations, demonstrating the field's strong uptake of his hybrid sensing approach. This work exemplifies his broader research philosophy of combining probabilistic filtering with machine learning to overcome the limitations of individual sensing modalities. His development of the Adaptive Iterated Extended Kalman Filter (AIEKF), introduced in 2014, represents a particularly notable algorithmic contribution — refining classical Kalman filtering by incorporating noise statistics estimation to enhance data fusion accuracy in real-world navigation scenarios. Earlier work on INS/WSN integration systems further established Xu's reputation for designing practical, deployable solutions for indoor robot navigation. Across his publications, he has consistently pushed toward more robust, adaptive fusion frameworks, making meaningful contributions to the robotics and autonomous systems community that continue to inform contemporary indoor navigation research.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3