Xiangfei Wu

University of Electronic Science and Technology of China

Papers

Total Citations

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About

Xiangfei Wu’s research centers on advancing robotic perception and multi-robot coordination, with a particular focus on stereo vision systems and autonomous area coverage. Her major contributions include a rigorous analysis of ranging errors in parallel binocular vision systems, which identified critical accuracy limitations in depth estimation for mobile robots—a foundational issue for 3D reconstruction and obstacle avoidance. She also designed a novel stereo image acquisition system with adjustable baseline and relative angle, addressing synchronization and calibration challenges that had been poorly documented in field robotics and 3D wave reconstruction. In multi-robot systems, Wu developed a coverage optimization algorithm based on virtual force refinement, improving area detection efficiency for applications like geological surveys and disaster response. Her most-cited work, “Analysis of Ranging Error of Parallel Binocular Vision System,” has garnered 7 citations, reflecting its practical relevance. Wu’s research bridges theoretical error analysis with system-level design, offering tangible solutions for real-world robotic navigation and environmental monitoring.