On the way to achieving higher degrees of autonomy for vehicles in complicated, ever changing scenarios, the localization problem poses a very important role. Especially the Simultaneous Localization and Mapping (SLAM) problem has been studied greatly in the past. For an autonomous system in the real world, we present a very cost-efficient, robust and very precise localization approach based on GraphSLAM and graph optimization using radar sensors. We are able to prove on a dynamically changing parking lot layout that both mapping and localization accuracy are very high. To evaluate the performance of the mapping algorithm, a highly accurate ground truth map generated from a total station was used. Localization results are compared to a high precision DGPS/INS system. Utilizing these methods, we can show the strong performance of our algorithm.


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    Title :

    Landmark based radar SLAM using graph optimization


    Contributors:
    Schuster, F. (author) / Keller, C. G. (author) / Rapp, M. (author) / Haueis, M. (author) / Curio, C. (author)


    Publication date :

    2016-11-01


    Size :

    2978181 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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