Biological systems, including human beings, have the innate ability to perform complex
tasks in a versatile and agile manner. Researchers in sensorimotor control have aimed to …

Imitation learning is the process by which one agent tries to learn how to perform a certain
task using information generated by another, often more-expert agent performing that same …

In robotics, the ultimate goal of reinforcement learning is to endow robots with the ability to
learn, improve, adapt and reproduce tasks with dynamically changing constraints based on …

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 …

We presented and evaluated an approach based on HMM, GMR, and dynamical systems to
allow robots to acquire new skills by imitation. Using HMM allowed us to get rid of the explicit …

Manipulation skill learning and generalisation have gained increasing attention due to the
wide applications of robot manipulators and the spurt of robot learning techniques …

A method to learn and reproduce robot force interactions in a human–robot interaction
setting is proposed. The method allows a robotic manipulator to learn to perform tasks that …

We present an approach allowing a robot to acquire new motor skills by learning the
couplings across motor control variables. The demonstrated skill is first encoded in a …

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 …

In the past, computational motor control has been approached from at least two major
frameworks: the dynamic systems approach and the viewpoint of optimal control. The …