Cooperative Aerial Coverage Path Planning for Visual Inspection of Complex Infrastructures

Abstract

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.