Lorenzo Gentilini

Marconi University, University of Bologna

Papers

Total Citations

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About

Lorenzo Gentilini is a robotics researcher specializing in autonomous navigation and control systems for agricultural unmanned ground vehicles (UGVs). His work focuses on two critical challenges in field robotics: trajectory planning and slip-aware motion control for skid-steering platforms operating in rough terrain. In his most-cited paper (8 citations), Gentilini developed a Robot Operating System (ROS) service for generating polynomial trajectories, enabling a tracked robotic platform to follow waypoints reliably in open-field agricultural scenarios. His subsequent work on Data-Driven Model Predictive Control (2 citations) addresses the fundamental challenge of skid-steering vehicles—estimating track slip to execute precise maneuvers in narrow, uneven spaces typical of farms. By combining model predictive control with data-driven slip estimation, Gentilini’s research bridges the gap between theoretical control methods and practical agricultural deployment. His contributions are particularly valuable for precision agriculture, where autonomous robots must navigate unpredictable terrain while maintaining accuracy. Gentilini’s work represents an important step toward making field robotics more robust and reliable for real-world farming operations, demonstrating how advanced control strategies can be implemented on cost-effective robotic platforms.