3rd Workshop on Behavior Adaptation, Interaction and Learning for Assistive Robotics

Full-day Workshop hosted at IEEE-Ro-MAN 2018, Nanjing, China

With robots getting out of the cages, Human-Robot Interaction applications’ effectiveness has not only to rely on the skills of trained users, but also on robots’ ability to adapt on the fly to the users’ behaviour, needs and motivations. In particular, the development of personal robots, as assistive technological tools, challenges researchers to develop socially intelligent and adaptive robots that can collaborate with people.

Personal robots are expected to incrementally learn user preferences, to learn categories of user preferences experienced during past interactions (so that they do not start each new interaction from scratch), and to modify and adapt their behaviors accordingly. This adaptation requires learning a model of human behavior and integrating this model into the decision-making algorithm of the robot. Efficient on the fly adaptation also requires model-free learning abilities to cope with local uncertainties of the environment, variations of the human’s desires and motivations, and volatilities of the interaction itself. Thus creating robotic systems capable of correctly modeling and recognizing the human behavior and of adapting their behavior to the user is a very critical task, especially in the domain of assistive and social robotics and when working with vulnerable user populations.

Robots should also be able to consider psychological aspects, for instance performing a cognitive assessment via human-robot interaction, to better adapt the robot behavior to the person mental status. This is particularly relevant for assisting the elderly and children with developmental disabilities.

Additionally, this workshop aims at examining and promoting recent developments in the robotics field and future directions including the related challenges and how these can be overcome with particular focus on computational intelligence methodologies.

Intended Audience

This Special Session is intended as a forum for a broad audience, which spans from social robotics, adaptive behaviour, learning algorithms to user profiling and robot behavior control, and it is a place to exchange opinions, to discuss innovative ideas and to get hints and suggestions on ongoing researches.

Invited Speakers Announced:

  • Rachid Alami, CNRS (France) Cancelled
  • Tom Ziemke, University of Skövde (Sweden) Cancelled
  • Mark Neerincx, Delft University of Technology (Netherlands)
  • Ben Robins , University of Hertfordshire (United Kingdom)


    Selected papers will be invited to submit an extended/revised version of the papers to the Special Issue: Behavior Adaptation and Artificial Perception in Assistive Robotics on the International Journal of Social Robotics