About

Antonello Venturini is a leading researcher in multi-vehicle systems and distributed control, with a focus on autonomous navigation in complex, unknown environments. His work bridges theoretical advances in model predictive control and moving horizon estimation with practical applications in logistics and Industry 5.0. Venturini’s most cited paper (2020, 38 citations) introduces a distributed model predictive control strategy that combines receding horizon control with leader-follower formations, enabling flexible and robust coordination for vehicle teams navigating unknown obstacles. He has further advanced multi-vehicle localization through distributed moving horizon estimation over sensor networks with sporadic measurements, a technique that efficiently exploits environmental constraints to improve accuracy. His recent work (2024) develops a grid-based receding horizon control for unicycle robots in dynamic logistic operations, integrating grid-based path planning with real-time control. With a growing citation record and contributions to both theoretical frameworks and experimental validation, Venturini’s research is shaping the future of autonomous multi-agent systems in industrial and field environments.

Research Focus

Key Achievements

4
H-Index
4
Papers
60
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
A Distributed Model Predictive Control Strategy for Constrained Multi-Vehicle Systems Moving in Unknown Environments
38 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Université Paris-Saclay, Centre National de la Recherche Scientifique, Laboratoire des signaux et systèmes, University of Calabria

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago