Nan Geng
Papers
1
Total Citations
8
H-Index
1
About
Nan Geng is a researcher whose work lies at the intersection of agricultural robotics and computer vision, with a particular focus on enabling autonomous navigation in complex orchard environments. Her most cited paper, "An Obstacle Detection System Based on Monocular Vision for Apple Orchard Robot" (2017), tackles a fundamental challenge in field robotics: how to reliably detect obstacles using only a single camera. This work is critical for the safe and efficient operation of agricultural robots, where real-time perception must contend with variable lighting, irregular terrain, and dense foliage. While her citation count is modest, the paper’s contribution is foundational for researchers developing low-cost, vision-based navigation systems for precision agriculture. Geng’s approach demonstrates how monocular vision—a simpler and more affordable alternative to LiDAR or stereo systems—can be effectively leveraged for obstacle avoidance in unstructured outdoor settings. Her research continues to influence the design of intelligent mobile robots for fruit orchards, where autonomy is key to reducing labor costs and improving harvest efficiency.
Research Focus
Key Achievements
Top Papers
- 1