Ben Harel
Papers
6
Total Citations
115
H-Index
5
About
Ben Harel is a leading researcher in agricultural robotics, specializing in the intersection of computer vision, automation, and economic optimization for precision harvesting. His work centers on overcoming critical challenges in robotic fruit picking, particularly for sweet peppers, where unstructured environments and variable lighting have historically limited detection and classification accuracy. Harel’s major contributions include developing controlled lighting systems that enable illumination-independent target detection, significantly boosting real-time performance for cost-efficient applications. His 2019 paper on this topic, with 68 citations, is a foundational work in the field. He has also pioneered viewpoint analysis for maturity classification, demonstrating that strategic camera positioning can improve detection rates from 65% to over 90%, and formulated selective harvest planning as a nonlinear programming problem to maximize profit. With a total of over 115 citations across his key publications, Harel’s research has direct implications for reducing labor costs and increasing yield in commercial greenhouses. His notable achievements include integrating economic decision-making into robotic vision systems, ensuring that each additional viewpoint is justified by potential profit gains. For students and researchers, Harel’s work offers a compelling model of how to bridge computer science, agronomy, and operations research to solve real-world agricultural challenges.
Research Focus
Key Achievements
Top Papers
- 1
- 2Viewpoint Analysis for Maturity Classification of Sweet Peppers20 citations · 2020
- 3
- 4Sweet pepper maturity evaluation8 citations · 2017
- 5
- 6Sweet pepper maturity evaluation via multiple viewpoints color analyses5 citations · 2016