I want to implement deep reinforcement learning using a UR5 robot. A little research told me nowadays researchers are using openAI gym, Mujoco, rllab as their frameworks. The thing is, I want to train my UR5 robot in virtual environment and transfer the learning to my real robot. The task can be peg insertion. Previously I worked on a project using ROS with the UR5 robot and a Kinect. In that project, we are using MoveIt for motion planning. Everything has already been set up and I'm quite familiar with ROS and MoveIt. Do you think I should bother myself modeling the UR5 robot and adding RGBD camera using Mujoco (I am not sure if I can do this in Mujoco), and after that training it using openAI gym framework, and finally transferring learning to the real robot using ROS? Or should I stick with ROS and MoveIt while incorporating openAI gym only as my reinforcement learning framework? I just don't see why I need Mujoco if I can use MoveIt and gazebo for modeling, which is already done. Thanks for your advice on this.