Mobile robot localization using multiple observations based on place recognition and GPS

In this paper, we propose a mobile robot localization system using multiple observations, which show the robot´s global position. One of observations is GPS observation, the other is utilized an appearance based place recognition. Using GPS observations has still some challenging problems such as multipath and signal lost under the environments there is tall buildings nearby. It affects a significant error on localization. On the other hand, appearance based place recognition methods are efficient to recognize the robot´s global position. It becomes possible to use a scene database with global position information. However, it could fail to function properly in natural environments like a lawn grass or trees in a park. We solve these demerits of each observations by using these multiple observations. Our system uses not only multiple observations but also dead reckoning with Gyrodometry model. As a result, the proposed localization system have achieved robust localization. To verify the validity of proposed method, our experiments using 1600m outdoor course in different seasons were conducted.