An outdoor navigation system using GPS and inertial platform

The use of the Global Positioning System (GPS) in outdoor localization is a quite common solution in large environments where no other references are available and positioning requirements are not so pressing. Of course, fine motion without the use of an expensive differential device is not an easy task even now that available precision has been greatly improved as the military encoding has been removed. We present a localization algorithm based on Kalman filtering that tries to fuse information coming from an inexpensive single GPS with inertial and, sometimes uncertain, map based data. The algorithm is able to produce an estimated configuration for the robot that can be successfully fed back in a navigation system, leading to a motion whose precision is only related to current information quality. Some experiments show difficulties and possible solutions to this sensor fusion problem