Jingjing Zhai

Nanjing University of Aeronautics and Astronautics

Papers

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About

Jingjing Zhai is a leading researcher in intelligent robotics and computer vision, with a primary focus on autonomous navigation in complex industrial environments. Her most impactful work addresses the critical challenge of vision-guided automated guided vehicles (AGVs) operating under adverse conditions, such as non-uniform illumination, sight-line occlusion, and path stripe damage. In her highly cited 2019 paper, "Intelligent Path Recognition against Image Noises for Vision Guidance of Automated Guided Vehicles in a Complex Workspace," Zhai developed novel algorithms that enable AGVs to robustly recognize and follow paths even when visual input is incomplete or deformed—a problem that has stymied the field for decades. This work, which has garnered 21 citations, represents a significant leap forward in making autonomous mobile robots viable for real-world manufacturing and logistics settings. Her contributions bridge the gap between theoretical computer vision and practical deployment, offering solutions that enhance the reliability and safety of automated systems. Zhai’s research continues to influence the next generation of intelligent transportation and industrial automation, positioning her as a key innovator in the intersection of robotics and artificial intelligence.