A new motor control approach for a mobile robot

Q-learning in the reinforcement learning (RL) field is a powerful and attractive tool to make robots generate autonomous behaviour. To generate a smooth trajectory with less computational cost, we propose two ingredients for Q-learning. We applied Q-learning to a simulated two-wheeled robot in order to generate trajectory for goal scoring task in robot soccer.