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In the presented work unmanned vehicles are used for an extra-terrestrial exploration mission. In this scenario a high factor of redundancy\udfor all systems has to be considered. Defective sensors for instance cannot be repaired and any damage has to be compensated\udthrough an intelligent use of the remaining sensors and a robust data fusion. Therefore this work proposes the utilization of a singlelayer\udlaser scanner, which is used for Simultaneous Localization And Mapping (SLAM) for the compensation of a defective relative\udpositioning system. An Extended Kalman-Filter (EKF) with error states is used to perform the loosely coupled integration of the estimated\udstates and the measured relative position in discrete updates. Subsequently the improvement of the navigation solution onboard\udan Unmanned Aerial Vehicles (UAV) can be estimated. The outcomes of a specifically developed simulation will be shown, delivering\udtheoretic results for the proposed method. A flight test is done finally in order to prove the capability of the laser scanner to detect and\udlocate an UAV

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

SINGLE-LAYER LASER SCANNER FOR DETECTION AND LOCALIZATION OF UNMANNED SWARM MEMBERS