Localization and mapping for agricultural robotics

Scope

Research in this area focuses on localization, mapping, control, and planning algorithms for mobile robots operating in unstructured natural environments such as vineyards, orchards, forests, and crop fields. These environments present numerous perceptual challenges, including—but not limited to—wind, glare, satellite signal interference, self-similar geometries, and dust.

The ultimate goal is to automatically build a digital twin of these environments using a fleet of autonomous, heterogeneous mobile robots, pushing the boundaries of precision agriculture.

To achieve this, both model-based methods, such as factor graph Simulaneous Localization and Mapping (SLAM), and emerging spatial AI techniques will be explored.

Expected Outcomes

The expected outcomes of this research include the development of novel real-time SLAM methods, their validation in real-world agricultural environments, and their integration with autonomous navigation, trajectory planning, and safe control algorithms. Additionally, this research will also integrate dynamic modeling of various mobile robot platforms -- such as tracked, wheeled, aerial, and legged systems -- to improve their mapping capability to build a digital twin of the field.

Publications and Patents

M. Focchi, D. Fontanelli, and L. Palopoli, "Pseudo-kinematic trajectory control of tracked vehicles," Submitted to 2025 IEEE International Conference on Robotics and Automation (ICRA), 2025.
R. Bussola, M. Focchi, N. Zilio, L. Palopoliand D. Fontanelli, "Distributed Robot Perception for Tracked Vehicles", Sixth Italian Conference on Robotics and Intelligent Machines (2024) doi: 10.5281/zenodo.14731170.
C. M. El Bou, M. Focchi, M. R. Chang, M. Camurri and K. D. von Ellenrieder, "Smooth Human–Robot Shared Control for Autonomous Orchard Monitoring With UGVs," IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 13603-13620, 2025, doi: 10.1109/TASE.2025.3554368.
M. Govindaraju, D. Fontanelli, S. S. Kumar, & A. S. Pillai, "Optimized Offline-Coverage Path Planning Algorithm for Multi-Robot for Weeding in Paddy Fields", IEEE Access, 2023

Personnel

Reference person: Marco Camurri
DII members: Davide Dorigoni (PhD student), Prof. Daniele Fontanelli
External collaborators: Tommaso Faraci (UniTN - DISI PhD student), Dr. Michele Focchi (UniTN - DISI RTT)

Report abuse