Weina Xi

Chinese Academy of Sciences, Harbin Institute of Technology, Shenzhen Institutes of Advanced Technology

Papers

Total Citations

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About

Weina Xi is a robotics researcher whose work focuses on making Simultaneous Localization and Mapping (SLAM) practical and affordable for commercial mobile robots. Her key research area addresses the critical challenge of achieving reliable localization and navigation using low-cost laser range finders (LRFs), which typically suffer from lower resolution and higher noise than expensive sensors. Xi’s major contribution is the development of an FFT-based scan-matching method for SLAM applications, detailed in her most-cited paper (27 citations). This approach leverages Fast Fourier Transformation to improve the accuracy and robustness of pose estimation even with noisy, low-cost sensor data. She has also proposed an improved serial implementation strategy that combines FFT with the Iterative Closest Point (ICP) algorithm, balancing computational cost and real-time performance—a crucial factor for resource-constrained robots. By tackling the trade-off between cost and performance, Xi’s work helps bridge the gap between high-end research platforms and practical, deployable robotic systems. Her research is particularly valuable for students and engineers seeking to implement efficient SLAM solutions in real-world, budget-sensitive applications.