  This article addresses the problem of Cooperative Coverage Path Planning
(C-CPP) for the inspection of complex infrastructures (offline 3D
reconstruction) by utilizing multiple Unmanned Autonomous Vehicles (UAVs). The
proposed scheme, based on a priori 3D model of the infrastructure under
inspection, is able to generate multiple paths for UAVs in order to achieve a
complete cooperative coverage in a short time. Initially the infrastructure
under inspection is being sliced by horizontal planes, which has the capability
of recognizing the branches of the structure and these branches will be handled
as breaking points for the path planning of the UAVs to collaboratively execute
the coverage task in less time and more realistically, based on the current
flying times of the UAVs. The multiple data sets collected from the coverage
are merged for the offline sparse and dense 3D reconstruction of the
infrastructure by utilizing SLAM and Structure from Motion approaches, with
either monocular or stereo sensors. The performance of the proposed C-CPP has
been experimentally evaluated in multiple indoor and realistic outdoor
infrastructure inspection experiments.
