The Landmark Detection Method using Reinforcement Learning for an Autonomous Mobile Robot

Abstract

Multi-agent systems have characteristics of autonomy, cooperation and so on. In addition, they have ability to solve problems flexibly. One of the Multi-agent systems application is following behavior. In a factory, following type mobile robot using the localization method by the landmark can carry many things together without wasting time and labor. The landmark detection method using features have been proposed. However, the detection methods using features cannot detect the landmark from many features similar to the landmark in an actual environment yet. Therefore, in this study, we propose the landmark detection method that selects the optimum detector based on SURF in real time by reinforcement learning for an autonomous mobile robot in an actual environment. The result of verification experiments shows that the proposed method is the better detection precision than single detector