Multi-Stage Decision-Making Skill Learning for Soccer Robot

The application scenarios of robots are becoming more and more complex, leading to higher and higher demand on skills for robots. This paper proposes a method to learn complex skill by decomposing it into basic skills, then train them respectively as well as combination into a whole, where reinforcement learning are used both in basic skill learning and in the integration. The method proposed is validated on the RoboCup small soccer robot platform via the skill of chasing and shooting ball and tested in both simulation environment and real world. It is verified our method has achieved a higher success rate comparing with traditional methods. Code is available here.