A developmental robot is one that learns and practices autonomously in the real physical world by interacting with the environment through sensors and effecters, probably under human supervision. The study of developmental robots is motivated by the autonomous developmental process of higher animals and humans from infancy to adulthood. Our goal is to enable a robot to learn autonomously from real-world experiences. The paper presents a case study of a developmental robot developing its auditory related behaviors to follow human trainers' voice commands. A learning architecture is proposed to resolve automatic representation generation and selective attention issues. Both simulation results and experiments on a real robot are reported to show the effectiveness.
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