Localization of Outdoor Mobile Robot with Multi-Path Bias Detection

In this paper, a localization method is provided using different-type sensors with bias data. In order to recognize the position of mobile robot for localization, two sensors are used. It is necessary data integration structure to integrate information from sensor data. The data is transformed to common global coordinate reference system before being fused. To take full advantage of two sensor data, an integration mechanism is implemented. This structure uses extended Kalman filter as integration filter with feedback structure. It is provided bias detection and estimation method for multi-path phenomena of DGPS sensor data in the surrounding of buildings. A performance evaluation is shown through an outdoor experiment data.