Extended Kalman Filter Based 3D Localization Method for Outdoor Mobile Robots

This paper proposes a 3D localization method for an outdoor mobile robot. This method assesses the 3D position including the altitude information, which is impossible in the existing 2D localization method. In this method, the 3D position of the robot is predicted using an encoder and an inclination sensor. The predicted position is fused with the position information obtained from the DGPS and the digital compass using extended kalman filter to evaluate the 3D position of the robot. The experimental results showed that the proposed method can effectively evaluate the 3D position of the robot in a sloping environment. Moreover, this method was found to be more effective than the conventional 2D localization method even in the evaluation of the plane position where altitude information is unnecessary.