Longfei Gao

Beijing Technology and Business University

Papers

Total Citations

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About

Longfei Gao is a researcher advancing the frontiers of robotic perception and visual navigation. His primary focus lies in visual feature extraction and tracking, a critical component for enabling autonomous robots to understand and navigate their environment. Gao’s most-cited work, "Visual Feature Extraction and Tracking Method Based on Corner Flow Detection" (2024), tackles the fundamental challenge of how a robot can reliably process streaming visual data. By developing a method that extracts and matches feature points across successive image frames, his research directly improves the accuracy and robustness of front-end visual odometry—the process by which a robot estimates its own motion from camera input. This contribution is essential for applications ranging from autonomous driving to drone navigation. With his work already garnering attention in the field, Gao is establishing himself as a key contributor to the practical implementation of vision-based robotic systems, laying the groundwork for more reliable and perceptive autonomous agents.