Abstract

Integrating robots into our daily lives, once a distant dream, is gradually becoming a reality, surpassing our initial expectations. Today, we aspire for these robots to not only perform rudimentary tasks but to emulate human behavior, and in some aspects, even exceed it. The realm of research dedicated to achieving human-like competencies in robots has given rise to the fields of Developmental and Cognitive Robotics. These domains find their foundation in cognitive architectures and insights from human development. Despite the substantial progress in these fields, a conspicuous gap exists in the literature related to the evaluation of cognitive architectures and the advanced capabilities exhibited by robots. Recognizing this void, we aim at establishing a bridge between the insights gleaned from human developmental theories and the potential applications in robotics. Central to our investigation is the notion that learning follows a cumulative trajectory of escalating complexity. Consequently, our focus centers on the early stages of human development, particularly within the realm of children aged 0 to 2 years. Drawing inspiration from Piaget’s constructivist theory aligned with empirical studies in the Developmental Robotics domain, we unveil a framework that facilitates the classification of these studies. In light of this, we curate a series of progressive experiments, mirroring the motor and cognitive growth exhibited by children from birth to two years of age, to be conducted with robots. We also described a methodology for designing these experiments considering the robotics aspects.

Full Text
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