Xingang Fu

Papers

Total Citations

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About

Xingang Fu is a researcher specializing in mobile robotics, computer vision, and real-time target tracking systems. His work focuses on developing robust, adaptive algorithms for autonomous navigation and object following in dynamic environments. Fu’s most notable contribution is his 2019 paper, "Tracking of Targets in Mobile Robots Based on Camshift Algorithm," which introduced an enhanced target tracking approach that improves upon the traditional Meanshift method. By leveraging the continuously adaptive Camshift algorithm, his system automatically adjusts the tracking window size to maintain accuracy during object movement, addressing key challenges in real-time robotic applications. While this paper has garnered 3 citations, it represents foundational work in adaptive tracking for mobile robots, demonstrating practical solutions for robustness and computational efficiency. Fu’s research bridges algorithm theory and applied robotics, offering insights for students and engineers developing autonomous systems. His work underscores the importance of adaptive algorithms in enabling reliable robot-environment interaction, making it a valuable reference for those exploring vision-based control in mobile robotics.