Ground
Ground
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Behavior-Based Unmanned Ground Vehicles
Navigation and Control of ground robots for diverse applications, with a particular emphasis on precision agriculture.
Investigation of autonomous path planning, obstacle avoidance, and adaptive control strategies to enable reliable operation in complex, unstructured environments such as open fields or greenhouses.
Research objectives
Research objectives
Development of Gaussian Process algorithms on low-power and efficient hardware
Design of algorithms exploiting vision sensors for enhancing robot versatility
Implementation and testing of Deep Reinforcement Learning algorithms in simulation (ROS/Gazebo) and in real-world scenarios
Design of intelligent robotic systems for multi-purpose missions
Ground & Air Control
Ground & Air Control
Another core focus of this research is the coordination of multi-agent systems, specifically the collaborative operation between UAVs and ground robots in agricultural environments.
By leveraging the complementary strengths of aerial and ground platforms, the system enhances coverage, responsiveness, and autonomy in precision farming tasks.
The activity is in the framework of a PRIN 2017 Project, Cooperation and REliable Autonomous TEchnologies to Foster Operations Relying on Unmanned Aircraft Systems (CREATEFORUAS), in collaboration with Prof. G. Fasano, Università Federico II, and with Dr. A. Mancini, Università Politecnica delle Marche.
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