Zhiqing Fan

Papers

Total Citations

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About

Zhiqing Fan is a researcher focused on advancing autonomous navigation and robotics, with particular expertise in simultaneous localization and mapping (SLAM) and particle filter algorithms. Their most cited work, "An Improved Particle Filter SLAM Algorithm for AGVs" (2020), addresses critical limitations in traditional particle filter methods used for robot localization, including high computational costs, poor real-time performance, and insufficient positioning accuracy. By developing the IPF-SLAM (Improved Particle Filtering SLAM) algorithm, Fan has contributed a more efficient and accurate solution for automated guided vehicles (AGVs), directly impacting the fields of industrial automation and mobile robotics. With 6 citations, this work demonstrates growing recognition in the robotics community. Fan's research bridges theoretical algorithm improvements with practical applications in autonomous systems, making their work particularly valuable for students and engineers seeking to enhance real-time navigation in dynamic environments. Their contributions continue to influence the development of more robust and computationally efficient SLAM techniques for real-world deployment.