Real Time Map Building by Means of an Ellipse Spatial Criterion and Sensor-Based Localization for Mobile Robot

In the present paper, map building and localization problems are examined. A new algorithm is proposed for each task. The map building algorithm is based on measurements derived by ultrasonic sensors. It has small memory requirements and can distinguish between parallel edges and edges-corners. The discrimination between edges and corners is achieved based on the physical restrictions imposed by the ultrasonic sensors and the way they are fired. The parallel edges discrimination is carried out on the basis of an ellipse spatial criterion. It is of low computational complexity and, therefore, can be applied on line. The application of the proposed algorithm does not require tracking of a continuous path. The method is accurate. It converges to the existing map characteristics. The mean inclination error is equal to 0.78 degrees while the mean distance error of the mid point of the chartographed edges from the actual edges is equal to 4.11 cm. The robustness of the algorithm was verified by applying it in noisy environments. The localization algorithm reduces the accumulated odometry error by utilizing readings obtained from ultrasonic sensors. Its application does not require a priori knowledge of the statistical characteristics of the noise that affects the measurements, nor the exact robot starting position. It is of low computational complexity. The application of the method was tested on a track with length equal to 25.85 m. The experiment was repeated 50 times. The mean position error was equal to 26 cm, while a dramatic reduction of the mean position error was achieved in regions for which the detected obstacles were parallel to only one of the reference coordinate axes. The mean error in such regions was reduced to 30 cm from 48 cm. The mean heading error was equal to 6.8°.