Localization independent of location based on place recognition and GPS observations

In this research, we propose a mobile robot localization system using multiple observations, which show the robot's global position. One of observations is GPS observations, another is utilized an appearance based place recognition. Using GPS observations faces still some challenging problems such as multipath and signal lost under the environments there is tall buildings nearby. These are critical issues for achieving a high accuracy and stable 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 appearance based place recognition methods could fail to function properly in natural environments like a lawn grass or trees in a park. We solve these disadvantages of each observations by using these multiple observations. Our system uses not only multiple observations but also dead reckoning with Gyrodometry model. Therefore, proposed method localize a robot position robustly indoors or not. To verify the validity of proposed method, our experiments are conducted about 1600m outdoor course in different seasons and course through an indoor.