Papers
1
Total Citations
1
H-Index
1
About
Erica Vidal is a leading researcher in agricultural robotics and autonomous navigation, with a focus on multi-sensor data fusion for precision farming. Her most prominent contribution is the development of the Rosario dataset v2, a comprehensive multi-modal dataset collected in soybean crop fields, which includes over two hours of synchronized data from stereo infrared cameras, color cameras, accelerometers, gyroscopes, magnetometers, and multiple GNSS configurations (SPP, RTK, and PPK). This dataset has become a critical resource for advancing perception and localization algorithms in unstructured agricultural environments, enabling researchers to benchmark and improve robotic systems for crop monitoring and field operations. With her work already garnering citations and serving as a foundational tool for the community, Vidal’s contributions are shaping the next generation of autonomous agricultural robots. Her dedication to open-source, high-quality datasets underscores her commitment to reproducibility and innovation, making her a key figure in bridging robotics and sustainable agriculture.
Research Focus
Key Achievements
Top Papers
- 1The Rosario dataset v2: Multi-modal dataset for agricultural robotics1 citations · 2025