Lorenzo Lucignano

Istituto Nazionale di Fisica Nucleare, Sezione di Napoli, École Polytechnique Fédérale de Lausanne

Papers

Total Citations

H-Index

About

Lorenzo Lucignano’s research lies at the intersection of human-robot interaction (HRI) and multimodal dialogue systems, where he has pioneered frameworks that make robot communication more natural, robust, and context-aware. His most influential work, “A dialogue system for multimodal human-robot interaction” (2013, 41 citations), introduces a POMDP-based dialogue system designed to handle the uncertainty and complexity of real-world HRI. By modeling interaction as a dialogical paradigm, Lucignano enables robots to interpret and respond to human speech, gestures, and environmental cues with greater flexibility. Building on this, his 2014 paper “Attentional regulations in a situated human-robot dialogue” (17 citations) advances the field by integrating an attentional system that dynamically guides the robot’s focus during structured task execution. This work demonstrates how multimodal dialogue can be regulated by attention, allowing robots to prioritize relevant information and maintain coherent, goal-oriented interactions. Lucignano’s contributions have been instrumental in shifting HRI from rigid command-based systems to adaptive, dialogue-driven frameworks, earning him recognition for improving the robustness and intuitiveness of human-robot collaboration. His research continues to influence the development of socially aware robots capable of seamless, situated communication.