Embodiment and Manipulation Learning Process for a Humanoid Hand

Babies are born with simple manipulation capabilities such as reflexes to perceived stimuli. Initial discoveries by babies are accidental until they become coordinated and curious enough to actively investigate their surroundings. This thesis explores the development of such primitive learning systems using an embodied light-weight hand with three fingers and a thumb. It is self-contained having four motors and 36 exteroceptor and proprioceptor sensors controlled by an on-palm microcontroller. Primitive manipulation is learned from sensory inputs using competitive learning, back-propagation algorithm and reinforcement learning strategies. This hand will be used for a humanoid being developed at the MIT Artificial Ingelligence Laboratory. Thesis Supervisor: Rodney A. Brooks Title: Professor, Department of Electrical Engineering and Computer Science 5 Acknowledgments Shhhh, don't wake me up yet. I am still dreaming about writing a 90 page thesis. Before this whole thesis evaporate,..

Summary

This review investigates two recent developments in artificial intelligence and neural computation: learning from imitation and the development of humanoid robots. It will be postulated that the study of imitation learning offers a promising route to gain new insights into mechanisms of perceptual motor control that could ultimately lead to the creation of autonomous humanoid robots. Imitation learning focuses on three important issues: efficient motor learning, the connection between action and perception, and modular motor control in form of movement primitives. It will be reviewed how research on representations of, and functional connections between action and perception have contributed to our understanding of motor acts of other beings. The recent discovery that some areas in the primate brain are active during both movement perception and execution has provided a hypothetical neural basis of imitation. Computational approaches to imitation learning will also be described, initially from the perspective of traditional AI and robotics, but also from the perspective of neural network models and statistical learning research. Parallels and differences between biological and computational approaches to imitation will be highlighted and an overview of current project

Games Children with Autism Can Play With

This paper discusses the potential use of a small, humanoid robotic doll called Robota in autism therapy. Robota was specifically designed for engaging children in imitative interaction games. This work is associated to the Aurora project where we study the potential therapeutic role of robots in autism therapy. This section provides the necessary background information on autism (18.1.1), and motivates the application of interactive technology in autism therapy (18.1.2). Section 18.1.3 discusses the important role of imitation and interaction games in the development of social skills. Section 18.2 introduces the Aurora project. Sections 18.3 and 18.4 briefly describe the humanoid doll Robota and its potential use in autism therapy. Observations from preliminary trials are discussed in section 18.5 before section 18.6 concludes this chapter. 18.1.1 Autism The autistic disorder is defined by specific diagnostic criteria, specified in DSM-I