Now showing items 1-6 of 6
Behaviour Generation in Humanoids by Learning Potential-based Policies from Constrained Motion
(Taylor and Francis, 2008-12)
Movement generation that is consistent with observed or demonstrated behaviour is an efficient way to seed movement planning in complex, high-dimensionalmovement systems like humanoid robots.We present a method for learning ...
Optimal control with adaptive internal dynamics models
Optimal feedback control has been proposed as an attractive movement generation strategy in goal reaching tasks for anthropomorphic manipulator systems. The optimal feedback control law for systems with non-linear dynamics ...
Learning Potential-based Policies from Constrained Motion
We present a method for learning potential-based policies from constrained motion data. In contrast to previous approaches to direct policy learning, our method can combine observations from a variety of contexts where ...
Adaptive Optimal Control for Redundantly Actuated Arms
Optimal feedback control has been proposed as an attractive movement generation strategy in goal reaching tasks for anthropomorphic manipulator systems. Recent developments, such as the iterative Linear Quadratic Gaussian ...
Multi-task Gaussian Process Learning of Robot Inverse Dynamics
The inverse dynamics problem for a robotic manipulator is to compute the torques needed at the joints to drive it along a given trajectory; it is beneficial to be able to learn this function for adaptive control. A robotic ...
A Library for Locally Weighted Projection Regression
In this paper we introduce an improved implementation of locally weighted projection regression (LWPR), a supervised learning algorithm that is capable of handling high-dimensional input data. As the key features, our ...