Xiaoying Han
Papers
1
Total Citations
8
H-Index
1
About
Xiaoying Han is a researcher specializing in sensor-based environmental perception and uncertainty modeling, with a particular focus on ultrasonic detection technologies. Her work addresses critical challenges in estimating indoor environment contours, where measurement uncertainties—such as ranging errors and directional inaccuracies—pose significant obstacles. Han’s most cited paper, "DSmT-Based Ultrasonic Detection Model for Estimating Indoor Environment Contour" (2019), introduces an innovative ultrasonic distance measurement model that leverages Dezert-Smarandache Theory (DSmT) to represent and manage these uncertainties. This model provides a robust framework for reconstructing the shape and boundaries of indoor spaces, with applications in robotics, autonomous navigation, and smart building systems. While her citation count reflects a growing interest in this niche area, Han’s contribution lies in bridging the gap between theoretical uncertainty management and practical sensor deployment. Her work offers a foundation for more reliable environmental mapping in cluttered or dynamic settings, making it valuable for researchers developing low-cost, non-visual sensing solutions. Through this research, Han demonstrates a commitment to advancing sensor fusion and probabilistic reasoning in real-world engineering contexts.
Research Focus
Key Achievements
Top Papers
- 1