Development of Self-Localization Method Using the Kalman Filter

Abstract

In the field of RoboCup Middle Size League, self-localization is important to estimate own position including goal and robot positions and to decide strategy. The self-localization method uses the internal information, such as revolution counted by encoder and direction detected by electric compass, and surround information such as camera image. In this paper, we construct basic self-localization method, and verify it in RoboCup MSL soccer field.