Xuemei Ma

National University of Defense Technology

Papers

Total Citations

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About

Xuemei Ma is a researcher in mobile robotics, with a primary focus on simultaneous localization and mapping (SLAM) and multi-sensor information fusion. Her most-cited work, "SLAM Method Based on Multi-Sensor Information Fusion" (2021), addresses a critical challenge in autonomous navigation: the limitations of single-sensor positioning. By integrating data from multiple sensors, Ma’s approach significantly enhances the accuracy and robustness of SLAM systems, enabling mobile robots to navigate more reliably in complex environments. This contribution has garnered 8 citations, reflecting its relevance to advancing real-world robotic autonomy. Ma’s research is particularly valuable for applications in logistics, exploration, and service robotics, where precise localization is essential. Her work underscores the importance of sensor fusion in overcoming the inherent weaknesses of individual sensors, such as drift or occlusion. For students and researchers entering the field of robotics, Ma’s studies offer a clear example of how combining complementary sensing modalities can solve practical navigation problems. Her ongoing efforts continue to push the boundaries of autonomous mobile robot performance, making her a notable contributor to the SLAM community.