Andrea Arlotta
Papers
2
Total Citations
8
H-Index
2
About
Andrea Arlotta is a robotics researcher focused on precision agriculture, where she develops autonomous systems for unstructured outdoor environments. Her work centers on object detection, relative localization, and multi-object tracking for mobile robots, addressing challenges like variable lighting and complex field conditions. In her 2023 paper, "A ROS-based Architecture for Object Detection and Relative Localization for a Mobile Robot with an Application to a Precision Farming Scenario," she introduced a modular framework that integrates ROS for robust perception in agricultural settings. Her related work, "An EKF-Based Multi-Object Tracking Framework for a Mobile Robot in a Precision Agriculture Scenario," proposes an Extended Kalman Filter approach to reliably track multiple targets over time, overcoming the limitations of instantaneous identification. Both papers have garnered 4 citations each, reflecting early recognition of their practical relevance. Arlotta’s contributions are notable for bridging robotics and agri-tech, offering scalable solutions that enhance autonomy in farming. Her research is particularly valuable for students and engineers interested in field robotics, sensor fusion, and real-world deployment of perception systems in challenging environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2