Zaijuan Li

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About

Zaijuan Li is a researcher in robotics and computer vision, with a focus on visual odometry and cooperative perception systems. Their most notable contribution is the development of MOMA (Visual Mobile Marker Odometry), a pioneering framework that enables cooperative visual localization by detecting and tracking mobile markers in dynamic environments. This work, published in 2018, introduced a novel scheme that leverages accurate fixed marker-based camera positioning to realize robust mobile marker odometry, while also systematically characterizing the error patterns inherent to such systems. With 11 citations, this paper has laid important groundwork for collaborative robotics applications, particularly in scenarios where multiple agents must coordinate their spatial awareness without relying on external infrastructure. Li’s research addresses critical challenges in real-time visual localization, offering practical solutions for autonomous navigation in cluttered or GPS-denied settings. Their work stands out for its elegant integration of fixed and mobile markers, advancing the field’s understanding of cooperative perception and error modeling.