For those interested in Reinforcement Learning, here’s some recent results obtained at at Erle.
This work presents an extension of the OpenAI Gym for robotics using the Robot Operating System (ROS) and the Gazebo simulator. The content discusses the software architecture proposed and the results obtained by using two Reinforcement Learning techniques: Q-Learning and Sarsa. Ultimately, the output of this work presents a benchmarking system for robotics that allows different techniques and algorithms to be compared using the same virtual conditions.
While the paper gets published in arXiv you can temporarily access a summary of this work at http://erlerobotics.com/whitepaper/robot_gym.pdf