Study on Motion Forms of a Two-dimensional Mobile Robot by Using Reinforcement Learning

Abstract

The main advantage of reinforcement learning is that it provides unexpected solutions for a designer. This study shows how a mobile robot can obtain unexpected motion forms by using reinforcement learning. Results show that the mobile robot with two-dimensional mobile ability can obtain unexpected motion forms for both advance motion and rotation motion. The mechanisms for these motions were investigated in order to understand how to obtain these motions. Moreover, since this system has a two-dimensional factor, this study examines the learning characteristic for the oblivion of the learning knowledge. In addition, this study examines the learning of the knowledge manipulation method to obtain new learning results with respect to the two-dimensional factor