Yuanliang Zhang

Jiangsu Ocean University, Jeonbuk National University

Papers

Total Citations

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About

Yuanliang Zhang is a researcher specializing in mobile robot navigation, with a particular focus on integrating Global Positioning System (GPS) and Dead Reckoning (DR) technologies. His core contributions lie in developing data fusion methods that enhance positioning accuracy and reliability for outdoor mobile robots, especially when using low-cost, single-frequency GPS receivers. Zhang's most impactful work, "An GPS/DR navigation system using neural network for mobile robot" (2014, 7 citations), pioneered the application of neural networks to intelligently fuse GPS and DR data, overcoming the limitations of each individual system. In his subsequent research, such as "A GPS/DR Data Fusion Method Based on the GPS Characteristics" (2014, 5 citations), he further refined these techniques by accounting for the specific characteristics of GPS signals to improve navigation robustness. His earlier foundational work, "GPS/DR Navigation Data Fusion Research Using Neural Network" (2009, 4 citations), established the cost-effective approach of using neural networks to achieve reliable positioning without expensive differential GPS equipment. Collectively, Zhang's research has advanced practical, affordable navigation solutions for autonomous mobile robots, demonstrating how intelligent algorithms can compensate for hardware limitations in real-world outdoor environments.