A comparison of three uncertainty calculus techniques for ultrasonic map building

Consider the problem of building the map of an unknown environment by using range readings obtained through ultrasonic sensors, and assume that a bitmap representation is adopted for compactness. In an ideal map, each cell of the bitmap is either empty or occupied by an obstacle. Because of the uncertainty introduced by sonar sensing, it is necessary to process appropriately the measures in order to classify each cell with a reasonable degree of accuracy. We compare three different algorithms for ultrasonic map building that are based respectively on probability theory, fuzzy logic and fuzzy measures. Simulation results in a one- dimensional case and experimental results for an office-like environment are presented to perform a comparison among the presented approaches.