Papers
79
Total Citations
3,625
H-Index
27
About
Manoj Karkee is a leading researcher in agricultural robotics and precision automation, with a particular focus on robotic harvesting systems, computer vision, and AI-driven sensing technologies for tree fruit crops. His work has fundamentally advanced the field of autonomous agricultural machinery, most notably through the design and field evaluation of robotic apple harvesters — a breakthrough achievement given that, despite four decades of research, no commercially viable mechanical harvester existed for fresh-market apples. His 2015 review on fruit detection sensors (557 citations) established a critical foundation for the field, while his pioneering harvesting robot designs (387 and 112 citations) demonstrated real-world feasibility using soft-robotic end-effectors and 3D machine vision. Karkee has also driven deep learning adoption in orchard environments, applying Faster R-CNN, YOLOv8, and Mask R-CNN frameworks to detect, localize, and segment fruit across challenging field conditions — work collectively cited hundreds of times. His research extends to kiwifruit detection, automated tree training, and fruit size estimation, reflecting remarkable breadth. With over 2,270 cumulative citations across his top works, Karkee's contributions represent transformative progress toward fully autonomous orchard management systems.
Research Focus
Key Achievements
Top Papers
- 1Sensors and systems for fruit detection and localization: A review557 citations · 2015
- 2Design, integration, and field evaluation of a robotic apple harvester387 citations · 2017
- 3Multi-class fruit-on-plant detection for apple in SNAP system using Faster R-CNN326 citations · 2020
- 4
- 5
- 6
- 7Kiwifruit detection in field images using Faster R-CNN with ZFNet133 citations · 2018
- 8AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges120 citations · 2025
- 9
- 10Apple fruit size estimation using a 3D machine vision system101 citations · 2018