@soldierofhell I agree there are definitely better and simpler ways to tackle collision avoidance but there’s also the matter of autonomous path planning to consider which can be a bit more complex. I think it would be interesting to see how a machine learned path planner would perform in particularly challenging environments (such as a massive pile of rubble where there is no clear optimal path) and it could make for some great discussion in my thesis.
I am also quite interested in the reinforcement learning topic itself and this project is a way to get some practice and set up the framework for a future project I am planning, which is to make a footstep/path planner for a legged robot like a hexapod, and make it navigate through a similar terrain environment.
Hopefully the sim2real issues aren’t too severe, the rover is quite solid and deterministic so it should be able to be modelled realistically in the simulation. At this point I’m not even sure how much simulation training will be done, as it might be easy enough to develop a good policy (or improve an initial policy from simulation) with some short real world training time.