Human-Robot Interaction

Human-Robot Interaction



  • Diego Reforgiato Recupero
  • Daniele Riboni
  • Emanuele Concas
  • Danilo Dessì

PhD students and Post-Docs

  • Simone Angioni
  • Antonello Meloni
  • Vivek Kumar
  • Wu Zixiu
  • Nino Cauli
  • Alessandro Bonini
  • Emanuele Concas

Research Interests

This laboratory works on a mixture of technologies related to the Deep Learning, Sentiment Analysis, IoT, Assistive Technologies and Semantic Web domains, that we have leveraged for Human-Robot-Interaction. Several use cases and projects have already been developed on top of NAO/Zora, a completely programmable and autonomous humanoid robot, and they aim at allowing NAO/Zora to interact with humans using natural language for different tasks. Example use cases allow the robot:

  • talking to the user and understanding his/her sentiments by using a dedicated Semantic Sentiment Analysis engine;
  • generating answers to open-dialog natural language utterances through a Generative Conversational Agent;
  • performing action commands depending on open-dialog natural language utterances and a Robot Action ontology;
  • identifying which objects the user is showing to the robot cameras by using convolutional neural networks trained on a huge collection of annotated objects;
  • integrating Google Assistant technologies within NAO/Zora to experience a much more natural interaction with the robot;
  • playing with NAO/Zora;
  • using NAO/Zora to control smart objects. The source code of each use case is publicly available in repositories and dedicated videos show how they work.

More info available at:


Research Collaborations

  • STLAB, CNR (Italy)
  • R2M Solution s.r.l. (Italy)

Selected Publications

  • Rubén Alonso, Alessandro Bonini, Diego Reforgiato Recupero, Lucio Davide Spano: Exploiting virtual reality and the robot operating system to remote-control a humanoid robot. Multim. Tools Appl. 81(11): 15565-15592 (2022)
  • Raza Abdulla Saeed, Diego Reforgiato Recupero, Paolo Remagnino: The boundary node method for multi-robot multi-goal path planning problems. Expert Syst. J. Knowl. Eng. 38(6) (2021)
  • Diego Reforgiato Recupero: Technology Enhanced Learning Using Humanoid Robots. Future Internet 13(2): 32 (2021)
  • Antonello Meloni, Simone Angioni, Angelo Antonio Salatino, Francesco Osborne, Diego Reforgiato Recupero, Enrico Motta: AIDA-Bot: A Conversational Agent to Explore Scholarly Knowledge Graphs. ISWC (Posters/Demos/Industry) 2021
  • Mattia Atzeni, Diego Reforgiato Recupero: Multi-domain sentiment analysis with mimicked and polarized word embeddings for human-robot interaction. Future Gener. Comput. Syst. 110: 984-999 (2020)
  • Diego Reforgiato Recupero, Federico Spiga: Knowledge acquisition from parsing natural language expressions for humanoid robot action commands. Inf. Process. Manag. 57(6): 102094 (2020)
  • Raza Abdulla Saeed, Diego Reforgiato Recupero, Paolo Remagnino: A Boundary Node Method for path planning of mobile robots. Robotics Auton. Syst. 123 (2020)
  • Rubén Alonso, Emanuele Concas, Diego Reforgiato Recupero: A Flexible and Scalable Social Robot Architecture Employing Voice Assistant Technologies. cAESAR 2020: 36-40
  • Nino Cauli, Diego Reforgiato Recupero: Video Action Recognition and Prediction Architecture for a Robotic Coach (short paper). SmartPhil@IUI 2020: 69-77
  • Diego Reforgiato Recupero, Danilo Dessì, Emanuele Concas: A Flexible and Scalable Architecture for Human-Robot Interaction. AmI 2019: 311-317
  • Federica Gerina, Barbara Pes, Diego Reforgiato Recupero, Daniele Riboni: Toward Supporting Food Journaling Using Air Quality Data Mining and a Social Robot. AmI 2019: 318-323
  • Raza Abdulla Saeed, Diego Reforgiato Recupero: Path Planning of a Mobile Robot in Grid Space using Boundary Node Method. ICINCO (2) 2019: 159-166
  • Gianluca Bardaro, Danilo Dessì, Enrico Motta, Francesco Osborne, Diego Reforgiato Recupero: Parsing Natural Language Sentences into Robot Actions. ISWC (Satellites) 2019: 93-96
  • Luigi Asprino, Aldo Gangemi, Andrea Giovanni Nuzzolese, Valentina Presutti, Diego Reforgiato Recupero, Alessandro Russo: Ontology-Based Knowledge Management for Comprehensive Geriatric Assessment and Reminiscence Therapy on Social Robots. Data Science for Healthcare 2019: 173-193
  • Mattia Atzeni, Diego Reforgiato Recupero: Deep Learning and Sentiment Analysis for Human-Robot Interaction. ESWC (Satellite Events) 2018: 14-18


  • Raza Saeed

Former Members

  • Federico Spiga
  • Pietro Demuro
  • Mirko Pili
  • Andrea Corronca
  • Alessio Murgioni
  • Mattia Atzeni

Questionario e social

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