Reinforcement learning on bag files?
At my university, we've been setting up a new subject on intelligent robotics right now. We want to do all the labs in ROS and on real data from our robot.
Now I've been thinking about what would be the best task for the students to be solved in ROS to exercise reinforcement learning.
We've got a UGV, but we just can't make it available for all the 60 students. So we think about what task can be solved provided only a recorded bag file without any interaction with the robot.
We know this isn't the best setup for reinforcement learning; on the other hand, just learning a value/Q function from a recording seems also as a possibility. We also need the result of the learning to be verifiable without running the students' codes on the robot.
Do you have any ideas on what task do try?
Our ideas:
- Doing something with the camera data (some simple vision task)
- Taking odometry and accelerometer data as training and try to learn when it is not advisable to go straight forward
Thanks for your ideas.
