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This paper presents a novel approach which enables multiple UAVs to efficiently explore an unknown environment and incrementally build the map of the area and its complex shaped obstacles, represented here as concave and convex in shape. The task is achieved by a improved performance of sensor based searching, navigation and mapping of these complex shaped obstacles in an unknown environment. The improved performance is quantified by explicit bounds of navigating the UAVs using an extended Kalman filter and to build the map of the complex shaped obstacles using the 2-D Splinegon. The circle packing search algorithm is used for the completeness of coverage in searching the unknown obstacles regions and the UAVs trajectories are generated by the Dubins path planning algorithm. This novel proposed algorithm results in a robust approach to search and map the obstacles using multiple UAVs that is also computational attractive.

COOPERATIVE UAVS MAPPING COMPLEX ENVIRONMENT USING 2D SPLINEGON