Papers
3
Total Citations
42
H-Index
3
About
Yoan Sallami is a robotics researcher whose work lies at the intersection of socially intelligent human-robot interaction (HRI) and advanced spatial reasoning. As a key contributor to the EU-funded MuMMER project, Sallami helped develop a social robot capable of interacting naturally and flexibly with users in complex public spaces like shopping malls—a system that integrates audio-visual sensing and social signal processing to achieve 17 citations. Addressing the fundamental challenge of perception inconsistency in HRI, Sallami introduced simulation-based physics reasoning for consistent scene estimation, enabling robots to accurately interpret tabletop environments despite occlusions or overlapping objects. Perhaps most notably, Sallami created the UNDERWORLDS framework (15 citations), a lightweight system for cascading spatio-temporal situation assessment that allows robots to represent their environment through real-time distributed data structures combining 3D scene graphs and geometry. This work bridges the gap between raw sensor data and actionable robotic understanding, making robots more reliable in dynamic, human-centered spaces. Sallami’s contributions are shaping how robots perceive, reason about, and safely interact within the unpredictable real world.
Research Focus
Key Achievements
Top Papers
- 1MuMMER: Socially Intelligent Human-Robot Interaction in Public Spaces17 citations · 2019
- 2UNDERWORLDS: Cascading Situation Assessment for Robots15 citations · 2018
- 3