A simultaneous localization and mapping algorithm based on Kalman filtering

For automatic navigation of autonomous vehicles, localization in real time is a key issue. In this article, a simultaneous localization and mapping algorithm is proposed for an autonomous vehicle. We use a laser detection and ranging sensor to detect the operating environment. An environment map is plot out using the sensor output data. Then, with an odometer, the vehicle position is located on this map. Finally, these two sensor outputs are merged using a Kalman filter to correct the map as well as the vehicle position.