Master in Artificial Intelligence, Facultat d’Informàtica de Barcelona (FIB), Facultat de Matemàtiques (UB), Escola Tècnica Superior d’Enginyeria (URV), Universitat Politècnica de Catalunya (UPC), Universitat de Barcelona (UB), Universitat Rovira i Virgili (URV). ; This dissertation outlines the benefits that sensor fusion brings in the mobile robotics problem of incrementally constructing a consistent map of an unknown environment with a moving robot, while simultaneously determining its location within this map. The work of this Master’s Thesis focuses on outdoor localization of autonomous vehicles, and aims to use raw GPS pseudorange data to establish geometric constraints to be added in the localization problem. This localization problem will solve for the optimal vehicle localization state, satisfying these pseudorange constraints, but also other geometric constraints imposed by other sensor measurements.We developed a software able to establish geometric constraints for a localization problem from raw GPS measurements. Then we integrated it in Wolf, a software framework for managing SLAM, enriching its sensor fusion capabilities. In the end we tested the sensor fusion between raw GPS and odometry. ; This project has been developed in the context of the European project Cargo-ANTS, devoted to investigate and develop novel techniques for autonomous navigation of wheeled vehicles in port terminal areas. ; Peer Reviewed


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    Title :

    Sensor fusion of raw GPS measurements for autonomous vehicle localization



    Publication date :

    2016-01-01



    Type of media :

    Miscellaneous


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    DDC:    629



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