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 human and 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.
DOI
10.1109/tcds.2017.2754143
Publication Date
2018-12-01
Publication Title
IEEE Transactions on Cognitive and Developmental Systems
Volume
10
Issue
4
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
ISSN
2379-8939
Embargo Period
2024-11-22
First Page
1005
Last Page
1022
Recommended Citation
Moulin-Frier, C., Fischer, T., Petit, M., Pointeau, G., & et al. (2018) 'DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self', IEEE Transactions on Cognitive and Developmental Systems, 10(4), pp. 1005-1022. Institute of Electrical and Electronics Engineers (IEEE): Available at: https://doi.org/10.1109/tcds.2017.2754143
