Infant-like Social Interactions between a Robot and a Human Caregiver

TLDR

Human infants learn through social interactions with caregivers, requiring balanced interaction levels that are neither overwhelming nor under‑stimulating. The study proposes a mechanism enabling an autonomous robot to regulate the intensity of its social interactions with a human. The mechanism uses expressive displays to modulate interaction intensity, integrated into a framework combining perception, attention, drives, emotions, behavior selection, and motor acts, allowing the robot to respond to social and non‑social stimuli while maintaining appropriate intensity. Results from face‑to‑face and toy‑mediated interactions demonstrate the robot’s ability to regulate interaction intensity. The paper was submitted in June 1998.

Abstract

From birth, human infants are immersed in a social environment that allows them to learn by leveraging the skills and capabilities of their caregivers. A critical pre-cursor to this type of social learning is the ability to maintain interaction levels that are neither overwhelming nor under-stim ulating. In this paper, we present a mechanism for an autonomous robot to regulate the intensity of its social interactions with a human. Similar to the feedback from infant to caregiver, the robot uses expressive displays to modulate the interaction intensity. This mechanism is integrated within a general framework that combines perception, attention, drives, emotions, behavior selection, and motor acts. We present a specific implementation of this architecture that enables the robot to react appropriately to both social stimuli (faces) and non-social stimuli (moving toys) while maintaining a suitable interaction intensity. We present results from both face-to-face interactions and interactions mediated through a toy. Note: This paper was submitted in June, 1998.