Yinling Wang
Papers
2
Total Citations
10
H-Index
2
About
Yinling Wang is a researcher whose work bridges the critical gap between raw sensor data and practical robotic vision. Her primary research areas include image distortion correction and mobile robot control, with a focus on enabling robust, real-world autonomy. Wang’s most notable contribution is a practical, single-image method for correcting the strong distortions produced by fisheye lenses—a key challenge in robotic vision, surveillance, and autonomous navigation. Her 2015 paper on this topic, which has garnered 8 citations, provides an accessible solution that eliminates the need for complex calibration setups, making it valuable for engineers and researchers deploying wide-angle cameras. In earlier work, Wang explored trajectory tracking for mobile robots using iterative learning control in polar coordinates (2010), addressing the precision and repeatability required for autonomous movement. Though her citation counts are modest, her contributions are foundational for practitioners seeking efficient, deployable solutions in visual sensing and motion control. Wang’s work exemplifies how targeted, practical innovations can directly support the advancement of field robotics and computer vision applications.
Research Focus
Key Achievements
Top Papers
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