Biologically inspired intrinsically motivated learning for service robots based on novelty detection and habituation

Abstract

The effective operation of service robots relies on developmental programs that allow the robot to expand its knowledge about its dynamic operating environment. Motivation theories from neuroscience and neuropsychology study the underlying mechanisms that drive the engagement of biological creatures to certain activities, such as learning. This research uses a physical Willow Garage PR2 robot, which is equipped with a cumulative learning mechanism driven by the intrinsic motivation of novelty detection based on computational models of biological habituation. It cumulatively learns the 360° appearance of novel real-world objects by picking them up. This paper discusses the theoretical motivations and background information on intrinsic motivations as novelty detection. The results and conclusions from the experimental study are presented.