DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self

Clément Moulin-Frier, Tobias Fischer, Maxime Peti, Grégoire Pointea, Jordi-Ysard Puigb, Ugo Pattacin, Sock Ching Lo, Daniel Camiller, Phuong Nguye, Matej Hoffmann, Hyung Jin Chan, Martina Zambelli, Anne-Laure Mealie, Andreas Damiano, Giorgio Metta, Tony J. Prescot, Yiannis Demiris, Peter Ford Domine, Paul F. M. J. Verschure


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.


Moulin-Frier, C., Fischer, T., Petit, M., Pointeau, G., Puigbo, J., Pattacini, U., Low, S. C., Camilleri, D., Nguyen, P., Hoffmann, M., Chang, H. J., Zambelli, M., Mealier, A., Damianou, A., Metta, G., Prescott, T. J., Demiris, Y., Dominey, P. F., Verschure, P. F. M. J., (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, Early Access