Papers
5
Total Citations
106
H-Index
4
About
Francesco Cutugno is a leading researcher in human-robot interaction (HRI), specializing in robust, multimodal communication systems that integrate speech, gestures, and dialogue. His major contributions center on developing architectures that allow robots to understand and respond to natural human commands with high reliability, reducing ambiguity in collaborative tasks. His most cited work (2013, 48 citations) introduces an extensible architecture for robust multimodal HRI, prioritizing human safety and effective communication. Complementing this, his POMDP-based dialogue system (2013, 41 citations) enhances interaction flexibility by modeling uncertainty in user intent. Cutugno also spearheaded the EVALITA 2018 SUGAR task (10 citations), creating a benchmark for voice-controlled robotic cooking assistants using authentic spoken data. His research extends to cultural heritage, where he explores humanoid robots that leverage implicit feedback to engage visitors. With a career spanning foundational HRI frameworks and applied challenges, Cutugno’s work has shaped how robots interpret multimodal cues, advancing natural, intuitive human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1An extensible architecture for robust multimodal human-robot communication48 citations · 2013
- 2A dialogue system for multimodal human-robot interaction41 citations · 2013
- 3
- 4
- 5