This paper presents a global localization method based map matching. A local map is built by uccessive splitting and merging scan points. A global map is built by merging all local maps. Local and global map are represented line segments that are sorted counterclockwise. Complete line segments are selected to match between two maps. Matching is based on relative position relation complete line segment. Localization algorithm based ordinal map and based on relative position relation improves matching efficiency and lowers computational cost. All these techniques have been implemented on mobile robot ATRVII equipped with 2D laser scanner SICK.

Map matching is a type of popular localization approaches for mobile robot autonomous navigation in indoor environment. Global localization is to fmd the best correspondence between current local map and the global map. Local map and global map are represented with comer points that are sorted counterclockwise. Relative position relation of comer points is computed in local and global map and used to search matched pairs. Map matching based on ordinal map improves the searchmg efficiency. Map matching based on relative position relation avoids frequent coordinates transformation. All these techniques have been implemented on our mobile robot ATRVII equipped with 2D laser range scanner SICK.

The paper presents the improvement and enhancement to the existing video based traffic detecting system. The works are concentrated on the acquiring and update of background image, a new solution to segmentation of vehicles from the background and adding peripheral interfaces. The simulation and experimental results are effective.

In this paper, we present the Intelligcnt Freight Train ID Recognition Systein (IFTIRS), which is a kind of Intcliigent Transportation Systcin (ITS). It can be used at any place along the railway. Rccognizing the ID, including the scrial number and configuration paramcters of the carriages, enable convenient and autornatic managcmcnt of frcight train systcm. The systcm constinution and workflow are introduced, and the technique of image acquisition, charactcrs location, isotation of each character, character rccognition and database monagcment are also addresscd in details, At the end of this paper, capability under practical condition shows the effeetivcness of our IFTIRS.

method of map bullding for indoor envlronment is prescntcd. It is based on adaptive clustering and welghted averaging, Different threshold valuc Is sclccted to cluster these sompling points at different posltion. Clastering with varlant threshold is more reasonable than It with constant threshold. Line segments are extracted from these sampling polnts and are used to approximate the shape of environment, Parametcrs of llne segment are computed with a welght vector. Line segmcnts in envlronmental map are arrangcd according to their geometric posilion relation. This type of map is more accurate and more useful for mobile rohot navigation. All there technlques have been implemented on our mobllc robot ATRVII equipped with 2D laser range scanner SICK.