Alessandro Antonucci
Papers
9
Total Citations
97
H-Index
5
About
Alessandro Antonucci is a robotics researcher whose work sits at the intersection of human-robot interaction, autonomous navigation, and intelligent motion planning. His research focuses primarily on enabling mobile and service robots to operate safely and naturally within human-populated environments — a challenge that demands both technical precision and social awareness. Among his most significant contributions is the development of physics-inspired neural networks for human motion prediction, a method that achieves both accuracy and computational efficiency critical for real-time robotics applications, earning 28 citations since 2021. Complementing this, his work on indoor localization using wireless ranging has advanced uncertainty-aware path planning in crowded indoor scenarios, accumulating 21 citations. His socially-aware multi-agent navigation framework further demonstrates his commitment to designing robots that move intuitively alongside people. Antonucci has also pioneered innovative paradigms such as teach-by-showing navigation, where humans directly guide robots through unknown environments, and human-assisted robot navigation systems that balance human initiative with autonomous correction. From early behavioral modeling work in 2018 through to his 2023 contributions on humanizing robot control, his research consistently prioritizes safety, social compatibility, and practical deployment — making him a valuable voice in the growing field of human-centered robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4Performance Assessment of a People Tracker for Social Robots10 citations · 2019
- 5
- 6Humanising robot-assisted navigation4 citations · 2023
- 7
- 8
- 9Humans as Path-Finders for Safe Navigation2 citations · 2021