Miguel Fernandes
Papers
5
Total Citations
47
H-Index
4
About
Miguel Fernandes is at the forefront of precision agricultural robotics, specializing in the automation of grapevine winter pruning. His research uniquely bridges computer vision, robotic manipulation, and plant modeling to tackle one of viticulture’s most labor-intensive tasks. Fernandes’s key contributions include developing deep learning methods for pruning region detection and plant organ segmentation, achieving 24 citations for his foundational 2023 work. He has pioneered techniques that merge 2D segmentation with 3D point clouds to generate precise pruning points, and has advanced whole-body control for non-holonomic mobile manipulators operating in unstructured vineyard environments. Notably, his work on Sim2Real transfer highlights both the potential and limitations of simulation-to-reality approaches in precision agriculture, offering critical insights for the field. With a growing citation record and a clear trajectory from detection to full robotic execution, Fernandes is establishing himself as a leading voice in agricultural robotics, where his systems promise to reduce the 80-120 hours per hectare currently required for skilled manual pruning.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5