Nanning Zheng
Papers
2
Total Citations
3
H-Index
1
About
Nanning Zheng is a researcher whose work sits at the intersection of robotics, computer vision, and autonomous systems. His research focuses on mobile robot navigation and visual place recognition, addressing core challenges in how autonomous agents perceive and move through their environments. Among his contributions, Zheng has developed innovative approaches to trajectory generation for mobile robots, proposing methods that dynamically adapt path planning based on real-time conditions encountered during robot travel. This work on iterative waypoint-based trajectory generation represents a practical advance in making robotic movement more responsive and reliable in complex environments. More recently, Zheng has turned his attention to visual place recognition, exploring how event cameras — sensors that capture changes in light rather than conventional frames — can overcome limitations of traditional cameras in challenging conditions such as glare or high-speed motion. His EFormer-VPR framework fuses event-based and frame-based data using transformer architectures, pushing the boundaries of robust scene recognition for autonomous driving systems. While still building his citation record, Zheng's research addresses genuinely difficult problems in autonomous systems, combining classical robotics concerns with cutting-edge deep learning approaches, making his work of growing relevance to both the robotics and computer vision communities.
Research Focus
Key Achievements
Top Papers
- 1
- 2