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      Indoor Path-Planning Algorithm for UAV-Based Contact Inspection

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          Abstract

          Nowadays, unmanned aerial vehicles (UAVs) are extensively used for multiple purposes, such as infrastructure inspections or surveillance. This paper presents a real-time path planning algorithm in indoor environments designed to perform contact inspection tasks using UAVs. The only input used by this algorithm is the point cloud of the building where the UAV is going to navigate. The algorithm is divided into two main parts. The first one is the pre-processing algorithm that processes the point cloud, segmenting it into rooms and discretizing each room. The second part is the path planning algorithm that has to be executed in real time. In this way, all the computational load is in the first step, which is pre-processed, making the path calculation algorithm faster. The method has been tested in different buildings, measuring the execution time for different paths calculations. As can be seen in the results section, the developed algorithm is able to calculate a new path in 8–9 milliseconds. The developed algorithm fulfils the execution time restrictions, and it has proven to be reliable for route calculation.

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          A note on two problems in connexion with graphs

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            Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

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              UAV PHOTOGRAMMETRY FOR MAPPING AND 3D MODELING – CURRENT STATUS AND FUTURE PERSPECTIVES

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                18 January 2021
                January 2021
                : 21
                : 2
                : 642
                Affiliations
                [1 ]CINTECX, GeoTECH Group, Campus Universitario de Vigo, University of Vigo, As Lagoas, Marcosende, 36310 Vigo, Spain; efrias@ 123456uvigo.es
                [2 ]GeoTECH Group, Department Natural Resources and Environmental Engineering, Campus Lagoas, School of Aerospace Engineering, University of Vigo, 32004 Ourense, Spain; higiniog@ 123456uvigo.es
                Author notes
                [* ]Correspondence: luismgonzalez@ 123456uvigo.es (L.M.G.d.S.); joaquin.martinez@ 123456uvigo.es (J.M.S.)
                Author information
                https://orcid.org/0000-0002-3898-7854
                https://orcid.org/0000-0002-8626-0545
                https://orcid.org/0000-0003-0320-4191
                https://orcid.org/0000-0002-0195-8849
                Article
                sensors-21-00642
                10.3390/s21020642
                7831516
                33477623
                6593973a-f372-4485-8dbe-75b700177eb7
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 10 December 2020
                : 14 January 2021
                Categories
                Article

                Biomedical engineering
                autonomous navigation,contact inspection,ndt,uav,payload,industrial inspection
                Biomedical engineering
                autonomous navigation, contact inspection, ndt, uav, payload, industrial inspection

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