Now showing items 1-4 of 4
Reconstructing Null-space Policies Subject to Dynamic Task Constraints in Redundant Manipulators
We consider the problem of direct policy learning in situations where the policies are only observable through their projections into the null-space of a set of dynamic, non-linear task constraints. We tackle the issue ...
Value Function Approximation on Non-Linear Manifolds for Robot Motor Control
The least squares approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular and useful choice as a basis function. However, ...
Robustness of VOR and OKR adaptation under kinematics and dynamics transformations
Many computational models of vestibulo-ocular reflex (VOR) adaptation have been proposed, however none of these models have explicitly highlighted the distinction between adaptation to dynamics transformations, in which ...
Linear and Nonlinear Generative Probabilistic Class Models for Shape Contours
We introduce a robust probabilistic approach to modeling shape contours based on a low- dimensional, nonlinear latent variable model. In contrast to existing techniques that use objective functions in data space without ...