Gastone Pietro Rosati Papini

University of Trento

Papers

4

Total Citations

66

H-Index

4

About

Gastone Pietro Rosati Papini is a leading researcher at the intersection of human-robot interaction, autonomous driving, and predictive control. His work focuses on enabling robots and autonomous vehicles to safely and intuitively share spaces with humans by predicting human motion and fostering emergent collaboration. A major contribution is the development of physics-inspired neural networks that generate efficient, real-time predictions of human motion—critical for safe robot navigation in crowded environments (28 citations). He has also pioneered a "mental simulation" approach for learning neural-network predictive control in self-driving cars, inspired by human cognitive processes (25 citations). Further, his research on biasing action selection demonstrates how artificial agents can produce emergent, cooperative human-robot interactions by leveraging shared contextual affordances (9 citations). Through these innovations, Rosati Papini is advancing the reliability and naturalness of autonomous systems, making them safer and more collaborative partners in dynamic, real-world settings.

Research Focus

Key Achievements

4
H-Index
4
Papers
66
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Efficient Prediction of Human Motion for Real-Time Robotics Applications With Physics-Inspired Neural Networks
28 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of Trento

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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