Objects Localization and Differentiation Using Ultrasonic Sensors 521 Objects Localization and Differentiation Using Ultrasonic Sensors

The most crucial problem for the mobile robot navigation is obstacles detection and their localization. The determination of obstacle position should be as accurate as possible in order to support robot self-localization procedures. In order to increase its efficiency the recognition of some feature of obstacles shapes should be done. The most advanced systems use laser range-finder and vision to solve this task. They allow to obtain a lot of data of a robot environment and the delivered information is quite precise. Unfortunately these devices have some important drawbacks. Laser scanning range-finders are still expensive. Their another drawback is that they scan only in a single plain. It causes that some obstacle cannot be detected. There are also available 3D laser range-finders. But measurements performed by them are time consuming. Therefore it is rather difficult to use them for on-line mobile robot navigation when a robot moves during a measurement execution. Considering vision systems the main disadvantages are computation consuming methods and a price of the system. In this sense ultrasonic range-finders seems still to be very useful equipment for a mobile robot. Their important advantage is low price and simplicity. Considering robotics applications they seem to be very attractive comparing especially with laser range-finders and vision systems. But in current mobile robots the ultrasonic sensors are rather used as an auxiliary equipment allowing to obtain rough information of the environment. The main reason of this situation is that the obtained data from commercial ultrasonic range-finders are very difficult to interprete. In this chapter two methods are presented which makes possible to overcome some difficulties combined with ultrasonic sensing. The first one is dedicated to the problem of object differentiation. The second method addresses the problem of an object localization and simplification of necessary computations.