Maurizio Ficocelli
Stony Brook University, State University of New York, University of New Brunswick
Papers
8
Total Citations
301
H-Index
6
About
Maurizio Ficocelli is a robotics researcher whose work spans two deeply interconnected domains: autonomous robot navigation in hazardous environments and socially assistive human-robot interaction. His research has made significant contributions to Urban Search and Rescue (USAR) robotics, where he has tackled the formidable challenge of enabling mobile robots to operate in unknown, cluttered disaster zones. His 2018 paper applying deep reinforcement learning to rough terrain navigation has garnered 86 citations, while his earlier work on cooperative human-robot interaction in USAR environments (2010, 65 citations) helped lay the groundwork for semi-autonomous rescue systems. Ficocelli has also advanced multi-robot coordination, developing supervisory control architectures for heterogeneous robot teams and intuitive graphical interfaces for operators managing complex rescue missions. Equally notable is his pioneering research in socially assistive robotics, exploring how emotionally expressive and socially intelligent robots can enhance patient-centered care. His 2015 paper on robotic emotional behavior has accumulated 75 citations, reflecting broad interest in this emerging field. Altogether, Ficocelli's body of work—spanning machine learning, human-robot interaction, and autonomous systems—represents a sustained effort to deploy intelligent robots in real-world environments where human lives and wellbeing are at stake.
Research Focus
Key Achievements
Top Papers
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- 4Can I be of assistance? The intelligence behind an assistive robot37 citations · 2008
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- 8Social Intelligence for a Task-Driven Assistive Robot2 citations · 2010