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This article addresses the problem of Cooperative Coverage Path Planning(C-CPP) for the inspection of complex infrastructures (offline 3Dreconstruction) by utilizing multiple Unmanned Autonomous Vehicles (UAVs). Theproposed scheme, based on a priori 3D model of the infrastructure underinspection, is able to generate multiple paths for UAVs in order to achieve acomplete cooperative coverage in a short time. Initially the infrastructureunder inspection is being sliced by horizontal planes, which has the capabilityof recognizing the branches of the structure and these branches will be handledas breaking points for the path planning of the UAVs to collaboratively executethe coverage task in less time and more realistically, based on the currentflying times of the UAVs. The multiple data sets collected from the coverageare merged for the offline sparse and dense 3D reconstruction of theinfrastructure by utilizing SLAM and Structure from Motion approaches, witheither monocular or stereo sensors. The performance of the proposed C-CPP hasbeen experimentally evaluated in multiple indoor and realistic outdoorinfrastructure inspection experiments.

Cooperative Aerial Coverage Path Planning for Visual Inspection of Complex Infrastructures