Simultaneous Localization and Mapping (SLAM) is an essential navigation tool for unmanned aircraft systems (UAS) operating in “GNSS denied” locations. In order to assess the performance of various sensing and SLAM algorithm combinations, clear and well-defined metrics are required. Currently, only one metric has been proposed, based on SLAM simulations, the Santos Metric. This metric has limitation in terms of low map noise sensitivity, and the use of insignificant data points. As a result, two new metrics have been proposed, and compared to the Santos Metric. All three metrics were found to identify poor performing sensors; however, the three metrics disagreed in terms of the best sensor.


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    Title :

    Comparative Performance of Simultaneous Localization and Mapping Algorithms for Unmanned Aircraft Based Navigation Systems


    Contributors:


    Publication date :

    2018-06-01


    Size :

    2011342 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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