From Brown University Robotics
Revision as of 20:45, 3 June 2010 by Jbutterf
This project exists to turn Sparse Online Gaussian Processes (SOGP) into a ROS node, in order to provide fast approximate Gaussian Process regression in ROS. The basis of this work is Dan Grollman's implementation of Csato's thesis on SOGP. Our hope is that ROS users will use this code to do robot learning from demonstration or other types of function regression.
Point of Contact
Alex Tarvo did the original documentation. Jesse has cleaned up the code, added compatibility with rosparam, and included the ability to save and load learned controllers. However, the codes need significantly better documentation and improved exception handling. Also eventually, we would like to be able to automatically detect the dimensionality of the input and output and provide a measure of the confidence.