Narayan Panthi
Papers
1
Total Citations
3
H-Index
1
About
Narayan Panthi is a researcher at the forefront of agricultural robotics, specializing in computer vision and precision harvesting. His work centers on bridging the gap between laboratory-developed technologies and real-world farming challenges, with a particular focus on fruit detection and localization for robotic harvesters. In his most-cited paper, "Harvesting tomatoes with a Robot: an evaluation of Computer-Vision capabilities" (2023), Panthi conducted a rigorous comparative study of two 3D cameras—Intel RealSense D435 and Zivid Two—for detecting and localizing tomatoes in both controlled lab and dynamic greenhouse environments. By integrating these cameras with the YOLO object detection model, he systematically evaluated image quality and performance, providing critical insights into the trade-offs between cost, accuracy, and environmental robustness. This work has already garnered 3 citations, signaling its relevance to the growing field of automated agriculture. Panthi’s contributions are vital for advancing the reliability of robotic systems in unstructured settings, directly impacting the efficiency of fruit harvesting and reducing labor dependency. His research exemplifies the practical application of AI-driven vision systems in sustainable agriculture.
Research Focus
Key Achievements
Top Papers
- 1