Papers
3
Total Citations
52
H-Index
2
About
Javier Cremona is a leading researcher in agricultural robotics, specializing in the development of robust localization systems for autonomous field robots. His work focuses on integrating Visual-Inertial Odometry (VIO) and Simultaneous Localization and Mapping (SLAM) with GNSS and stereo-inertial sensors to overcome the unique challenges of arable farming environments, such as repetitive crop rows and uneven terrain. Cremona’s major contributions include the experimental evaluation of VIO systems for farming, demonstrating their feasibility for tasks like sowing and weed control, and the advancement of GNSS-stereo-inertial SLAM to reduce drift in exploratory trajectories. His most-cited paper, “Experimental evaluation of Visual‐Inertial Odometry systems for arable farming” (2022, 35 citations), and its follow-up on GNSS-stereo-inertial SLAM (2023, 16 citations) have significantly influenced the field. Notably, he co-created “The Rosario dataset v2” (2025), a multi-modal dataset with over two hours of sensor data from soybean fields, providing a critical resource for benchmarking agricultural robotics algorithms. Cremona’s work is pivotal in advancing precision agriculture, enabling more reliable and autonomous farming operations.
Research Focus
Key Achievements
Top Papers
- 1
- 2GNSS‐stereo‐inertial SLAM for arable farming16 citations · 2023
- 3The Rosario dataset v2: Multi-modal dataset for agricultural robotics1 citations · 2025