Benxian Xiao

Papers

Total Citations

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About

Benxian Xiao is a researcher specializing in mobile robotics, with a particular focus on autonomous self-localization systems for indoor environments. Their work addresses one of the most fundamental challenges in robotics: enabling mobile robots to accurately determine their position without relying on pre-built environmental maps, thereby reducing algorithmic complexity and improving practical deployability. Xiao's most notable contributions lie in the development of vision-based localization frameworks that leverage both monocular and binocular camera systems combined with advanced probabilistic filtering techniques. Their 2009 paper on monocular vision paired with an Extended Kalman Filter, which has garnered 6 citations, demonstrates an innovative approach to map-free indoor localization. Complementing this, their earlier 2007 work introduced a binocular camera system combined with an Unscented Kalman Filter, utilizing line-segment-based environmental descriptions and clustering technology to extract depth information automatically, accumulating 3 citations. Together, these contributions reflect a coherent research trajectory aimed at making robot self-localization more computationally accessible and adaptable to real-world indoor settings. While Xiao's citation record is modest, their foundational work in sensor fusion and probabilistic localization offers valuable insights for students and researchers exploring autonomous navigation and computer vision applications in robotics.