DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self
Abstract
This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the-art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users.
Keywords
Cite
@article{arxiv.1706.03661,
title = {DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self},
author = {Clément Moulin-Frier and Tobias Fischer and Maxime Petit and Grégoire Pointeau and Jordi-Ysard Puigbo and Ugo Pattacini and Sock Ching Low and Daniel Camilleri and Phuong Nguyen and Matej Hoffmann and Hyung Jin Chang and Martina Zambelli and Anne-Laure Mealier and Andreas Damianou and Giorgio Metta and Tony J. Prescott and Yiannis Demiris and Peter Ford Dominey and Paul F. M. J. Verschure},
journal= {arXiv preprint arXiv:1706.03661},
year = {2021}
}
Comments
Preprint version; final version available at http://ieeexplore.ieee.org/ IEEE Transactions on Cognitive and Developmental Systems (Accepted) DOI: 10.1109/TCDS.2017.2754143