Durable Interaction with Socially Intelligent Robots

Project Details


This project develops potentially groundbreaking methods that make service robots socially intelligent and capable of establishing durable relationship with their users. This relies on developing the capabilities to sense and express, which faces grand challenges: the low-quality signals and the poor context-awareness. We first propose a new paradigm called reinforcement fusion, which combines sensor signals in an interactive way: e.g. when a robot detects a sound direction, it turns towards the direction to see better and moves towards it to hear better. Reinforcement fusion is analogous to reinforcement learning, a known term in machine learning. It will dramatically improve robot's sensibility to the context including social behaviours. Secondly we propose a concept of social behaviour entrainment to adapt behaviours. Entrainment is the phenomenon that dialogue partners tend to adapt their speaking style of each other. Our hypothesis is that through reinforcement fusion based tracking and social information extraction, machine learning based context and user modelling, and social behaviour entrainment, durable social interaction between human and robot is achievable. The reinforcement fusion paradigm is applicable to all sorts of systems with steerable sensors.
Effective start/end date01/08/201331/12/2017


  • 1 Organisation or participation in workshops, courses, or seminars
  • 1 Peer review of manuscripts

2016 First International Workshop on Sensing, Processing and Learning for Intelligent Machines

Evgenios Vlachos (Organizer)

Jan 2016Aug 2016

Activity: Attending an eventOrganisation or participation in workshops, courses, or seminars

Reviewer at the 11th International Conference on Human-Robot Interaction (HRI 2016) (Journal)

Evgenios Vlachos (Peer reviewer)


Activity: Editorial work and peer reviewPeer review of manuscriptsResearch

Research Output

  • 1 Article in proceeding
  • 1 Poster

Improving Robustness against Environmental Sounds for Directing Attention of Social Robots

Thomsen, N. B., Tan, Z-H., Lindberg, B. & Jensen, S. H., 2015, Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction. Springer Publishing Company, p. 25-34 10 p. (Lecture Notes in Computer Science).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

  • 2 Citations (Scopus)

    Robot Futures: Using Theatre to Influence Acceptance of Care Robots

    Christoffersen, A., Grindsted Nielsen, S., Jochum, E. A. & Tan, Z-H., 2015. 2 p.

    Research output: Contribution to conference without publisher/journalPosterResearchpeer-review

  • Press / Media

    Robotic Experiments at Fremtidens Plejehjem

    Evgenios Vlachos


    1 item of Media coverage

    Press/Media: Press / Media