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Attachment bonds for Human-like Robots

If robots are to be truly integrated in humans' everyday environment, they cannot be simply (pre-)designed and directly taken "off the shelf" and embedded into a real-life setting. Also, technical excellence and human-like appearance and "superficial" traits of their behavior are not enough to make social robots trusted, believable, and accepted. Fuller and deeper integration into human environments would require that, like children, robots develop embedded in the social environment in which they will fulfill their roles. An important element to bootstrap and guide this integration is the establishment of affective bonds between the "infant" robot and the adults among whom it develops, from whom it learns, and who it will later have to look after. In this paper, we present a Perception–Action architecture and experiments to simulate imprinting — the establishment of strong attachment links with a "caregiver" — in a robot. Following recent theories, we do not consider imprinting as rigidly timed and irreversible, but as a more flexible phenomenon that allows for further adaptation as a result of reward-based learning through experience. After the initial imprinting, adaptation is achieved in the context of a history of "affective" interactions between the robot and a human, driven by "distress" and "comfort" responses in the robot.