Yunpeng Li

Cornell University, Tianjin Polytechnic University, Wuhan University of Technology

Papers

Total Citations

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About

Yunpeng Li is a researcher whose work spans computer vision, autonomous robotics, and intelligent navigation systems. Li's early contributions focused on feature matching in one-dimensional panoramic images, developing scale-invariant methods for mobile robot localization and navigation using omnidirectional cameras — work that earned recognition with 12 citations for the 2006 study and laid a foundation for robust visual navigation techniques. This research demonstrated a practical approach to extracting locally scale-invariant feature points from image scale spaces, addressing real-world challenges in robot perception. Li's more recent work reflects an evolution toward cutting-edge autonomous systems. A 2023 study explored deep reinforcement learning for underwater vehicle path planning, tackling the particularly demanding challenge of continuous action spaces in complex aquatic environments. Complementing this, a 2024 paper introduced novel dynamic tracking methods for coded targets amid complex background noise, showcasing Li's sustained interest in precision visual tracking under difficult conditions. While Li's citation counts remain modest, the breadth of contributions — from panoramic vision to deep learning-driven underwater robotics — reflects a researcher steadily building expertise across multiple frontier areas of autonomous systems and computer vision, with growing relevance in modern robotics research.