Realizing high performance of ordinary robots is one of the core problems in robotic
research. Improving the performance of ordinary robots usually relies on the collaborative …

During social interaction humans extract important information from tactile stimuli that
enriches their understanding of the interaction. This process depends, however, not only on …

Nonlinear dynamical systems have been used in many disciplines to model complex
behaviors, including biological motor control, robotics, perception, economics, traffic …

Presents an approach to movement planning, on-line trajectory modification, and imitation
learning by representing movement plans based on a set of nonlinear differential equations …

Cognitive developmental robotics (CDR) aims to provide new understanding of how
human's higher cognitive functions develop by means of a synthetic approach that …

Many control problems take place in continuous state-action spaces, eg, as in manipulator
robotics, where the control objective is often defined as finding a desired trajectory that …

Acquisition of new sensorimotor knowledge by imitation is a promising paradigm for robot
learning. To be effective, action learning should not be limited to direct replication of …

The study of social learning in robotics has been motivated by both scientific interest in the
learning process and practical desires to produce machines that are useful, flexible, and …

This paper discusses a comprehensive framework for modular motor control based on a
recently developed theory of dynamic movement primitives (DMP). DMPs are a formulation …

Initial investigations of the cerebellar microcircuit inspired the Marr–Albus theoretical
framework of cerebellar function. We review recent developments in the experimental …