Navigating a mobile service-robot in a natural environment using sensor-fusion techniques

The mobile service robots described are designed to operate in dynamics and changing environments together with human beings and other static or moving objects. Sensors that are capable of providing the quality of information that is required for the described scenario are optical sensors, like digital cameras and laser scanners. In this paper the sensor integration and fusion for such sensors is described. Complementary sensor information is transformed into a common representation in order to achieve a cooperating sensor system. Sensor fusion is performed by matching the local perception of the laser scanner and camera system with a global model that is being build incrementally. The Mahalanobis distance is used as matching criterion and a Kalman filter is used to fuse matching features. A common representation including the uncertainty and the confidence is used for all scene features. The system's performance is demonstrated for the task of exploring an unknown environment and incrementally building of the geometrical model.