RL-Glue for ROS

Sarah Osentoski of Brown's RLAB recently announced a beta version of a ROS to RL-Glue bridge for reinforcement learning

Brown is pleased to announce our beta version of rosglue. rosglue is a bridge between ROS and RL-Glue, a standard reinforcement learning (RL) framework.

rosglue is designed to enable RL researchers and roboticists work together rather than having to reimplement existing methods in both fields. A goal of rosglue is to allow ROS users to use RL algorithms provided by RL researchers and, likewise, to allow RL researchers to more easily use robots running ROS as a learning environment. rosglue allows a robot running ROS to become an RL-Glue environment allowing RL-Glue compatible agents to control the robot. A high level visualization of the framework can be seen here.

rosglue uses a yaml configuration file to specify the topics and services and the learning problem. rosglue automatically subscribes to the topics and services specified in the file. rosglue sends actions selected to the RL-Glue to the robot using the appropriate topic or service. It then creates observations from specified topics for the RL-Glue agent.

rosglue is currently available for download from the brown-ros-pkg repository via:

svn co https://brown-ros-pkg.googlecode.com/svn/trunk/experimental/rlrobot/rosglue rosglue

and preliminary documentation can be found here:

http://code.google.com/p/brown-ros-pkg/wiki/rosglue

Robot Learning and Autonomy @ Brown (RLAB)