Yongqing Jin
Papers
1
Total Citations
3
H-Index
1
About
Yongqing Jin is a robotics researcher whose work focuses on advancing perception and navigation capabilities for autonomous mobile systems. His primary research areas include monocular vision-based robot navigation, real-time ground plane segmentation, and robust environment understanding for mobile robotics. Jin’s most notable contribution is his 2017 paper, "Real-time trust region ground plane segmentation for monocular mobile robots," which addresses the fundamental challenge of segmenting ground planes in dynamic, unknown environments using only a single camera. This work tackles critical issues such as coordinate system initialization and outlier management in the region of interest, offering a geometric-based solution that improves reliability for monocular robot navigation. While his citation count remains modest, Jin’s research has practical significance for low-cost, vision-only robotic platforms, and his approach to handling environmental uncertainty contributes to the broader field of autonomous navigation. His work is particularly relevant for students and researchers interested in real-time computer vision, SLAM, and mobile robotics, demonstrating how careful algorithmic design can overcome the limitations of monocular sensing in unstructured settings.
Research Focus
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Top Papers
- 1