Yingjing Shi

University of Electronic Science and Technology of China

Papers

Total Citations

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About

Yingjing Shi is a robotics researcher whose work centers on visual tracking and autonomous navigation for real-world robotic systems. Her most impactful contribution is a high-speed, long-term visual object tracking algorithm designed specifically for real robot platforms, published in 2021 and cited 24 times—a strong indicator of its practical relevance in the field of computer vision and robotics. This work addresses the critical challenge of maintaining robust object tracking under real-time constraints, enabling robots to persistently follow targets in dynamic environments. Shi has also made notable theoretical contributions to motion control, particularly in the problem of guiding a single robot to circle a target using only bearing measurements. Her 2018 paper on this topic proposes control schemes for two distinct scenarios—constant forward speed and constant angular velocity—offering elegant solutions for situations where distance information is unavailable. This work has applications in surveillance, pursuit-evasion, and environmental monitoring. Together, Shi’s research bridges the gap between theoretical control strategies and practical implementation, making her work valuable for students and engineers developing autonomous robotic systems that must interact with and track moving objects in real time.