Supervised Reinforcement Learning: Application to a Wall Following Behaviour in a Mobile Robot

In this work we describe the design of a control approach in which, by way of supervised reinforcement learning, the learning potential is combined with the previous knowledge of the task in question, obtaining as a result rapid convergence to the desired behaviour as well as an increase in the stability of the process. We have tested the application of our approach in the design of a basic behaviour pattern in mobile robotics, such as that of wall following. We have carried out several experiments obtaining goods results which confirm the utility and advantages derived from the use of our approach.