SHARON aims to develop human-centric Artificial Intelligence (AI) models, driven by principles from cognitive sciences and explainable, to enable symmetric and bidirectional interaction between humans and robots (physical AIs).
SHARON aims to develop human-centric Artificial
Intelligence (AI) models, driven by principles from cognitive sciences and
explainable, to enable symmetric and bidirectional interaction between humans
and robots (physical AIs).
The starting point of the project is the capability of
recipient design in human-human communication, which allows humans to take the
perspective of their interlocutors and shape their actions accordingly.
Transferring this capability to the scenario of Human-Robot Interaction (HRI)
is an open problem and requires that both agents build, maintain and
continuously update awareness models about their interlocutors, and use those
models to decide their next actions. SHARON will tackle this goal through novel
AI cognitive and interpretable models of human behavior, including capabilities
of encoding human intention, novel bidirectional communication interfaces and,
in summary, a more symmetric HRI. We have selected the domain of healthcare and
assistive robotics for patients with sensorimotor disabilities to assess the
how the developed technology meets our goals concerning interpretability,
symmetry, bidirectionality and trustworthiness in HRI.
We propose a transdisciplinary approach, in which
knowledge will transcend the boundaries of research disciplines to develop a
unified technology. Particularly, SHARON pivots around two research fields:
machine learning and computer vision, as supporting fields of artificial
intelligence, and robotics. However, it will also establish links to other
disciplines, such as cognitive sciences and medical sciences.
SHARON is aligned with the current vision of a more human-centric and trustworthy AI.
Although current AI technology shows impressive performance at solving many
tasks, even surpassing human capabilities, it remains far from achieving intelligent
machines that think, learn and behave as humans, what hinders its broad social