Yosef Cohen
Papers
2
Total Citations
10
H-Index
2
About
Yosef Cohen is a researcher working at the intersection of robotics, motion control, and agricultural automation. His key research areas include trajectory generation, dynamic movement primitives, and computer vision for precision agriculture. Cohen’s major contribution is the development of **Tight Dynamic Movement Primitives (TDMP)** , a novel formulation that enhances the generation of complex, stable trajectories for robotic systems. This work, published in 2013, has garnered 8 citations and provides a more robust framework for motion control compared to traditional approaches. More recently, Cohen has applied his expertise to agricultural robotics, notably in the **artificial synthesis of Medjool date fruit bunch images** (2023). By modeling date bunches in 3D using structural decomposition and Bézier curves, he created annotated synthetic datasets that enable the training of robust computer vision algorithms for robotic thinning—a critical task in date farming. This innovative approach addresses the scarcity of real-world annotated agricultural data and has the potential to significantly advance automation in date production. Cohen’s work bridges fundamental robotics theory with practical, high-impact agricultural applications.
Research Focus
Key Achievements
Top Papers
- 1Tight Dynamic Movement Primitives for Complex Trajectory Generation8 citations · 2013
- 2