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 the ability of the robot to adapt to the users’ behaviour and needs as well. 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 and to modify and adapt their behaviors accordingly. Indeed, for improved and natural human-robot cooperation, human users will learn how to interact with the robot but, at the time, the robotic systems should adapt to the users. This adaptation requires learning a model of human behavior and integrating this model into the decision-making algorithm of the robot. 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 robotics and when working with vulnerable user populations.
The topics of interest include, but are not limited to:
· Assistive Robotics
· HRI and Cognitive Impairments
· User Profiling
· Adaptive Behavior
· Activity Recognition
· Intention Recognition
· Multi-sensor fusion
· Ambient Assisted Living
· HRI and Personalization
· Robot Learning
· Adaptive Planning
· User Experience
· User-centred Design
Adriana Tapus, Robotics and Computer Vision Lab, ENSTA-ParisTech (France)
We welcome prospective participants to submit either full papers (up to 6 pages) or extended abstracts (up to 2 pages). Papers can be on research that the authors have already conducted, but we especially encourage papers on new ideas or research that the authors plan to conduct.
The manuscripts should use the IEEE RO-MAN two-column format. Please submit a PDF copy of your manuscript through EasyChair.