Francesco Leofante
University of Genoa, University of Sassari, RWTH Aachen University, Imperial College London
Papers
9
Total Citations
61
H-Index
4
About
Francesco Leofante is a researcher at the intersection of artificial intelligence, formal verification, and robotics, with a focus on ensuring safety and optimality in autonomous systems. His work centers on multi-robot coordination, task planning, and the reliable integration of AI into real-world environments, particularly in logistics and manufacturing. Leofante’s major contributions include pioneering the use of Optimization Modulo Theories (OMT) and Satisfiability Modulo Theories (SMT) for synthesizing and executing optimal, verifiable plans for multi-robot systems, as demonstrated in his highly cited 2018 paper on integrated synthesis and execution in logistics (20 citations). He has also advanced assistive robotics by applying formal verification to improve the reliability of myocontrol for upper-limb prosthetics (15 citations), addressing a long-standing challenge in the field. His work spans from humanoid robot safety—such as combining static and runtime methods for stable standing-up—to swarm robotics and autonomous driving education. With a growing citation impact, Leofante’s research bridges theory and practice, offering provable guarantees for complex robotic tasks, making him a notable figure in dependable AI and robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Improving Reliability of Myocontrol Using Formal Verification15 citations · 2019
- 3SMT-based Planning for Robots in Smart Factories6 citations · 2019
- 4
- 5
- 6Task Planning with OMT: An Application to Production Logistics3 citations · 2018
- 7Robot Swarms as Hybrid Systems: Modelling and Verification3 citations · 2022
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- 9