Luca Baglivo

University of Trento, University of Padua, Instituto Politécnico de Lisboa, Space (Italy)

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About

Luca Baglivo is a robotics researcher whose work focuses on autonomous navigation, object localization, and industrial mobile robotics. His key contributions lie in developing robust sensor fusion and control algorithms for wheeled mobile robots operating in cluttered, real-world environments. Baglivo’s most impactful work, “Autonomous pallet localization and picking for industrial forklifts” (42 citations), introduces the RLPF algorithm, a novel combination of laser and camera data that enables autonomous forklifts to identify and precisely pick pallets even when their position and orientation are highly uncertain. This work directly addresses a critical bottleneck in warehouse automation. He further advanced object localization and path planning in “An object localization and reaching method for wheeled mobile robots using laser rangefinder” (13 citations), proposing an efficient scheme for real-time target reaching. His research on “Four path following controllers for rhombic like vehicles” (6 citations) explores specialized kinematic models for agile, steerable robots. Baglivo’s work is notable for its practical, application-driven approach, bridging the gap between theoretical control and industrial deployment. His contributions to sensor-based autonomy and reactive obstacle avoidance have laid important groundwork for the next generation of intelligent, self-navigating industrial vehicles.