15 search results - page 2 / 3 » Multi-task Gaussian Process Learning of Robot Inverse Dynami... |
IROS
2008
IEEE
13 years 11 months ago
2008
IEEE
— High performance and compliant robot control requires accurate dynamics models which cannot be obtained analytically for sufficiently complex robot systems. In such cases, mac...
ICRA
2009
IEEE
13 years 11 months ago
2009
IEEE
— In this paper, we present a novel approach to controlling a robotic system online from scratch based on the reinforcement learning principle. In contrast to other approaches, o...
IROS
2009
IEEE
13 years 11 months ago
2009
IEEE
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
IROS
2008
IEEE
13 years 11 months ago
2008
IEEE
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
AROBOTS
2011
12 years 12 months ago
2011
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...