Simone Angarano
Papers
11
Total Citations
134
H-Index
6
About
Simone Angarano is an emerging researcher at the intersection of robotics, computer vision, and precision agriculture, with a growing body of work that is reshaping how autonomous systems operate in complex outdoor environments. His research focuses on GPS-free autonomous navigation, deep learning-based perception, and efficient edge inference — areas where his contributions are already making a measurable impact, with his most cited work on deep reinforcement learning for vineyard navigation accumulating 45 citations since 2022. Angarano's most significant contributions lie in enabling robotic platforms to navigate agricultural row crops — vineyards, orchards, and dense tree rows — without relying on precise GPS localization. His use of deep semantic segmentation, contrastive clustering for waypoint generation, and domain generalization techniques addresses real-world deployment challenges where environmental variability would otherwise cripple standard systems. Complementing this agricultural focus, his work on Generative Adversarial Network-based super-resolution at the edge, achieved through knowledge distillation, demonstrates a strong interest in making powerful vision models viable on resource-constrained hardware. Additional work on odometry correction, robotic manipulation, and instance segmentation underscores the breadth of his robotics expertise, marking him as a versatile and productive voice in the field.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10