In this paper, we present an approach to imitation learning of arm movements in humanoid
robots. Continuous hidden Markov models (HMMs) are used to generalize movements …

This paper addresses the problems of what to imitate and how to imitate in simple uni and bi-
manual manipulatory tasks. To solve the what to imitate issue, we use a probabilistic …

This paper describes a new approach on how to teach everyday manipulation tasks to a
robot under the" Learning from Observation" framework. In our previous work, to acquire low …

This paper evaluates a model of human imitation of abstract, two-arm movements. The
model consists of a hierarchy of artificial neural networks, which are abstractions of brain …

Behavior imitation ability will be a key technology for future human friendly robots. In order to
understand the principles and mechanisms of imitation, we take a synthetic cognitive …

Teaching a robot to learn new knowledge is a repetitive and tedious process. In order to
accelerate the process, we propose a novel template-based approach for robot arm …

We present a psychophysical study of human arm movement imitation, and an approach to
analyzing the resulting data, which is general enough to be applied to human or humanoid …

We present a programming-by-demonstration framework for generically extracting the
relevant features of a given task and for addressing the problem of generalizing the acquired …

Mimesis is the theory that human intelligence originated in the interactive communication of
motion recognition and generation through imitation. A mimesis model has been proposed …

This paper deals with the imitation of human motions by a humanoid robot based on marker
point measurements from a 3D motion capture system. For imitating the humanpsilas …