Abstract

Recent studies show that robots are still far from being long-term companions in our daily lives. With an interdisciplinary approach, this position paper structures around coping with this problem and suggests guidelines on how to develop a cognitive architecture for social robots assuring their long-term personal assistance at home. Following the guidelines, we offer a conceptual cognitive architecture enabling assistant robots to autonomously create cognitive representations of cared-for individuals. Our proposed architecture places Theory of Mind approach in a metacognitive process first to empathize and learn with humans, then to guide robot's high-level decision-making accordingly. These decisions evaluate, regulate and control robot's cognitive process towards understanding, validating and caring for interacted humans and serving them in a personalized way. Hence, robots deploying this architecture will be trustworthy, flexible and generic to any human type and needs; in the end, they will establish a secure attachment with interacted humans. Finally, we present a use-case for our novel cognitive architecture to better visualize our conceptual work.

@inproceedings{Gorur2016,
author = {G{"{o}}r{"{u}}r, Orhan Can and Albayrak, Sahin},
booktitle = {Workshop on Bio-inspired Social Robot Learning in Home Scenarios at IEEE/RSJ International Conference on Intelligent Robots and Systems 2016 (IROS'16)},
title = {{A Cognitive Architecture Incorporating Theory of Mind in Social Robots towards Their Personal Assistance at Home}},
year = {2016}
}