Comparative analysis of unmanned aerial vehicles used in photogrammetric surveys

Specht, M.; Widźgowski, S.; Stateczny, A.; Specht, C.; Lewicka, O.

doi:10.12716/1001.17.02.21

Artykuł - szczegóły

Tytuł artykułu

Comparative analysis of unmanned aerial vehicles used in photogrammetric surveys

Autorzy

Specht M. , Widźgowski S. , Stateczny A. , Specht C. , Lewicka O.

Treść / Zawartość

Pełne teksty:

Pobierz

Identyfikatory

DOI

10.12716/1001.17.02.21

Warianty tytułu

Języki publikacji

Abstrakty

There are many manufacturers on the market offering various types of Unmanned Aerial Vehicles (UAV). The multitude of drones available on the market means that the choice of a UAV for a specific application appears to be a decision problem to be solved. The aim of this article is a comparative analysis of drones used in photogrammetric surveys. The criteria for evaluating the UAVs were: availability and product support, payload (min. 5 kg), price (PLN 100,000), as well as space available for measurement modules. These are the requirements that must be met for the implementation of the INNOBAT project, the aim of which is to develop an integrated system using autonomous unmanned aerial and surface vehicles, intended for bathymetric monitoring in the coastal zone. The comparative analysis of drones was based on 27 companies producing UAV. Based on the analysis, 6 drones that met the project requirements were selected. They were: Aurelia X6 Pro, Aurelia X8 Standard LE, DroneHexa AG, FOX-C8 XT, Hercules 10 and Zoe X4. Selected UAVs differ from each other, among others, in the number of rotors, flight duration and resistance to weather conditions. Individual characteristics of drones may have a different rank depending on their application, therefore the selection of UAVs should be made after prioritisation criteria of a given project.

Słowa kluczowe

unmanned aerial vehicle unmanned vehicles photogrammetry drone inertial navigation system hydrography Global Navigation Satellite System LiDAR

Wydawca

Faculty of Navigation, Gdynia Maritime University

Czasopismo

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

Rocznik

2023

Tom

Vol. 17 No. 2

Strony

433--443

Opis fizyczny

Bibliogr. 57 poz., rys., tab.

Twórcy

autor

Specht M.

Gdynia Maritime University, Gdynia, Poland
Marine Technology Ltd., Gdynia, Poland

autor

Widźgowski S.

Marine Technology Ltd., Gdynia, Poland

autor

Stateczny A.

Gdańsk University of Technology, Gdańsk, Poland

autor

Specht C.

Gdynia Maritime University, Gdynia, Poland

autor

Lewicka O.

Gdańsk University of Technology, Gdańsk, Poland

Bibliografia

1. Lewicka, O.; Specht, M.; Specht, C. Assessment of the Steering Precision of a UAV along the Flight Profiles Using a GNSS RTK Receiver. Remote Sens. 2022, 14, 6127.
2. Merkisz, J.; Nykaza, A. Risk Estimation and Risk Evaluation on Examination Flight Unmanned Aerial Vehicle Operator on Visual Line of Sight. Buses: Technique, Exploitation, Transport Systems 2016, 6, 297– 307. (In Polish).
3. Chamola, V.; Kotesh, P.; Agarwal, A.; Naren; Gupta, N.;Guizani, M. A Comprehensive Review of Unmanned Aerial Vehicle Attacks and Neutralization Techniques.Ad Hoc Netw. 2021, 111, 102324.
4. Nex, F.; Remondino, F. UAV for 3D Mapping Applications: A Review. Appl. Geomat. 2014, 6, 1–15.
5. Burdziakowski, P. Increasing the Geometrical and Interpretation Quality of Unmanned Aerial Vehicle Photogrammetry Products Using Super‐resolution Algorithms. Remote Sens. 2020, 12, 810.
6. Frankenberger, J.R.; Huang, C.; Nouwakpo, K. Lowaltitude Digital Photogrammetry Technique to Assess Ephemeral Gully Erosion. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2008 (IGARSS 2008), Boston, MA, USA, 6–11 July 2008.
7. Hashim, K.A.; Ahmad, A.; Samad, A.M.; NizamTahar, K.; Udin, W.S. Integration of Low Altitude Aerial Terrestrial Photogrammetry Data in 3D Heritage Building Modeling. In Proceedings of the IEEE Control and System Graduate Research Colloquium 2012 (ICSGRC 2012), Shah Alam, Malaysia, 16–17 July 2012.
8. Jizhou, W.; Zongjian, L.; Chengming, L. Reconstruction of Buildings from a Single UAV Image. In Proceedings of the International Society for Photogrammetry and Remote Sensing Congress 2004 (ISPRS 2004), Zurich, Switzerland, 6–12 September 2004.
9. Saleri, R.; Cappellini, V.; Nony, N.; de Luca, L.; Pierrot‐Deseilligny, M.; Bardiere, E.; Campi, M. UAV Photogrammetry for Archaeological Survey: The Theaters Area of Pompeii. In Proceedings of the Digital Heritage International Congress 2013 (Digital Heritage 2013), Marseille, France, 28 October–1 November 2013.
10. Tariq, A.; Gillani, S.M.O.A.; Qureshi, H.K.; Haneef, I. Heritage Preservation Using Aerial Imagery from Light Weight Low Cost Unmanned Aerial Vehicle (UAV). In Proceedings of the International Conference on Communication Technologies 2017 (ICCT 2017), Guayaquil, Ecuador, 6–9 November 2017.
11. Fernández, T.; Pérez, J.L.; Cardenal, J.; Gómez, J.M.; Colomo, C.; Delgado, J. Analysis of Landslide Evolution Affecting Olive Groves Using UAV and Photogrammetric Techniques. Remote Sens. 2016, 8, 837.
12. Mansoori, S.A.; Al‐Ruzouq, R.; Dogom, D.A.; al Shamsi, M.; Mazzm, A.A.; Aburaed, N. Photogrammetric Techniques and UAV for Drainage Pattern and Overflow Assessment in Mountainous Terrains—Hatta/UAE. In Proceedings of the IEEE InternationalGeoscience and Remote Sensing Symposium 2019 (IGARSS 2019), Yokohama, Japan, 28 July–2 August 2019.
13. Nevalainen, O.; Honkavaara, E.; Tuominen, S.; Viljanen, N.; Hakala, T.; Yu, X.; Hyyppä, J.; Saari, H.; Pölönen, I.; Imai, N.N.; et al. Individual Tree Detection and Classification with UAV‐based Photogrammetric Point Clouds and Hyperspectral Imaging. Remote Sens. 2017, 9, 185.
14. Song, Y.; Wang, J.; Shan, B. An Effective Leaf Area Index Estimation Method for Wheat from UAV‐based Point Cloud Data. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2019 (IGARSS 2019), Yokohama, Japan, 28 July–2 August 2019.
15. Tariq, A.; Osama, S.M.; Gillani, A. Development of Low Cost and Light Weight UAV for Photogrammetry and Precision Land Mapping Using Aerial Imagery. In Proceedings of the International Conference on Frontiers of Information Technology 2016 (FIT 2016), Islamabad, Pakistan, 19–21 December 2016.
16. Chou, T.‐Y.; Yeh, M.‐L.; Chen, Y.‐C.; Chen, Y.‐H. Disaster Monitoring and Management by the Unmanned Aerial Vehicle Technology. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS Arch. 2010, 38, 137–142.
17. Haarbrink, R.B.; Koers, E. Helicopter UAV for Photogrammetry and Rapid Response. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS Arch. 2006, XXXVI‐1/W44, 1–4.
18. Mohd Daud, S.M.S.; Mohd Yusof, M.Y.P.; Heo, C.C.; Khoo, L.S.; Chainchel Singh, M.K.; Mahmood, M.S.; Nawawi, H. Applications of Drone in Disaster Management: A Scoping Review. Sci. Justice 2022, 62, 30–42.
19. Molina, P.; Colomina, I.; Vitoria, T.; Silva, P.F.; Skaloud, J.; Kornus, W.; Prades, R.; Aguilera, C. Searching Lost People with UAVs: The System and Results of the Closesearch Project. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS Arch. 2012, 39, 441–446.
20. Półka, M.; Ptak, S.; Kuziora, Ł. The Use of UAV’s for Search and Rescue Operations. Procedia Eng. 2017, 192, 748–752.
21. Hartmann, W.; Tilch, S.; Eisenbeiss, H.; Schindler, K. Determination of the UAV Position by Automatic Processing of Thermal Images. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2012, 39, 111–116.
22. Manyoky, M.; Theiler, P.; Steudler, D.; Eisenbeiss, H. Unmanned Aerial Vehicle in Cadastral Applications. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2011, 38, 57–62.
23. Agrafiotis, P.; Skarlatos, D.; Georgopoulos, A.;Karantzalos, K. Shallow Water Bathymetry Mapping from UAV Imagery Based on Machine Learning. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2019, XLII‐2/W10, 9–16.
24. Burdziakowski, P.; Specht, C.; Dabrowski, P.S.; Specht, M.; Lewicka, O.; Makar, A. Using UAV Photogrammetry to Analyse Changes in the Coastal Zone Based on the Sopot Tombolo (Salient) Measurement Project. Sensors 2020, 20, 4000.
25. Nikolakopoulos, K.G.; Lampropoulou, P.; Fakiris, E.; Sardelianos, D.; Papatheodorou, G. Synergistic Use of UAV and USV Data and Petrographic Analyses for the Investigation of Beachrock Formations: A Case Study from Syros Island, Aegean Sea, Greece. Minerals 2018, 8,534.
26. Zhang, C. An UAV‐based Photogrammetric Mapping System for Road Condition Assessment. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2008, 37, 627–632.
27. Berni, J.A.J.; Zarco‐Tejada, P.J.; Suárez, L.; Fereres, E. Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring from an Unmanned Aerial Vehicle. Trans. Geosci. Remote Sens. 2009, 47, 722–738.
28. Feng, Q.; Liu, J.; Gong, J. UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis. Remote Sens. 2015, 7, 1074–1094.
29. Grenzdörffer, G.J.; Engel, A.; Teichert, B. The Photogrammetric Potential of Low‐cost UAVs in Forestry and Agriculture. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS Arch. 2008, 37, 1207– 1213.
30. Torresan, C.; Berton, A.; Carotenuto, F.; di Gennaro, S.F.; Gioli, B.; Matese, A.; Miglietta, F.; Vagnoli, C.; Zaldei, A.; Wallace, L. Forestry Applications of UAVs in Europe: A Review. Int. J. Remote Sens. 2017, 38, 2427–2447.
31. Zhang, Y.; Wu, H.; Yang, W. Forests Growth Monitoring Based on Tree Canopy 3D Reconstruction Using UAV Aerial Photogrammetry. Forests 2019, 10, 1052.
32. Alioua, A.; Djeghri, H.‐E.; Cherif, M.E.T.; Senouci, S.‐M.; Sedjelmaci, H. UAVs for Traffic Monitoring: A Sequential Game‐based Computation Offloading/Sharing Approach. Comput. Netw. 2020, 177, 107273.
33. Puri, A.; Valavanis, K.P.; Kontitsis, M. Statistical Profile Generation for Traffic Monitoring Using Real‐time UAV Based Video Data. In Proceedings of the 15th Mediterranean Conference on Control & Automation (MED 2007), Athens, Greece, 27–29 June 2007.
34. Ro, K.; Oh, J.‐S.; Dong, L. Lessons Learned: Application of Small UAV for Urban Highway Traffic Monitoring. In Proceedings of the 45th AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, USA, 8–11 November 2007.
35. Semsch, E.; Jakob, M.; Pavlicek, D.; Pechoucek, M. Autonomous UAV Surveillance in Complex Urban Environments. In Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology 2009 (WI‐IAT 2009), Washington, DC, USA, 15–18 September 2009.
36. Tan, Y.; Li, Y. UAV Photogrammetry‐based 3D Road Distress Detection. ISPRS Int. J. Geo. Inf. 2019, 8, 409.
37. Kubat, M.; Smyczyński, P.; Granosik, G. Unmanned Air Vehicle Selection Criteria for Inspection and Transport Tasks. Measurement Automation Robotics 2018, 22, 23– 32. (In Polish).
38. European Commission. Commission Delegated Regulation (EU) 2019/945 of 12 March 2019 on Unmanned Aircraft Systems and on Third‐country Operators of Unmanned Aircraft Systems; European Commission: Brussels, Belgium, 2019.
39. Eisenbeiss, H. A Mini Unmanned Aerial Vehicle (UAV): System Overview and Image Acquisition. In Proceedings of the International Workshop on Processing and Visualization Using High Resolution Imagery, Pitsanulok, Thailand, 18–20 November 2004.
40. Amin, R.; Aijun, L.; Shamshirband, S. A Review of Quadrotor UAV: Control Methodologies and Performance Evaluation. Int. J. Autom. Control. 2016, 10, 87–103.
41. Connect ESCs and Motors. Available online: https://ardupilot.org/copter/docs/connect‐escs‐andmotors. html (accessed on 24 December 2022).
42. Drone Types: Multi‐rotor vs Fixed‐wing vs Single Rotor vs Hybrid VTOL. Available online: https://www.auav.com.au/articles/drone‐types/ (accessed on 24 December 2022).
43. Hong, Y.; Fang, J.; Tao, Y. Ground Control Station Development for Autonomous UAV. In Intelligent Robotics and Applications; Xiong C., Liu H., Huang Y., Xiong Y.; Springer, Berlin, Heidelberg, Germany, 2008; Volume 5315, pp. 36–44.
44. Yin, N.; Liu, R.; Zeng, B.; Liu, N. A Review: UAV‐based Remote Sensing. IOP Conf. Ser.: Mater. Sci. Eng. 2019, 490, 062014.
45. Drummond, C.D.; Harley, M.D.; Turner, I.L.; Matheen, N.; Glamore, W.C. UAV Applications to Coastal Engineering. In Proceedings of the Australasian Coasts & Ports Conference 2015, Auckland, New Zealand, 15– 18 September 2015.
46. Siebert, S.; Teizer, J. Mobile 3D Mapping for Surveying Earthwork Projects Using an Unmanned Aerial Vehicle (UAV) System. Autom. Constr. 2014, 41, 1–14.
47. NEXUS 800 Powered by HYPACK. Available online: https://www.hypack.com/File%20Library/Resource%20L ibrary/Brochures%20and%20Catalogs/Nexus‐800‐ Brochure.pdf (accessed on 24 December 2022).
48. Lewicka, O.; Specht, M.; Stateczny, A.; Specht, C.; Dardanelli, G.; Brčić, D.; Szostak, B.; Halicki, A.; Stateczny, M.; Widźgowski, S. Integration Data Model of the Bathymetric Monitoring System for Shallow Waterbodies Using UAV and USV Platforms. Remote Sens. 2022, 14, 4075.
49. Specht, M.; Stateczny, A.; Specht, C.; Widźgowski, S.; Lewicka, O.; Wiśniewska, M. Concept of an Innovative Autonomous Unmanned System for Bathymetric Monitoring of Shallow Waterbodies (INNOBAT System). Energies 2021, 14, 5370.
50. Specht, M.; Wiśniewska, M.; Stateczny, A.; Specht, C.; Szostak, B.; Lewicka, O.; Stateczny, M.; Widźgowski, S.; Halicki, A. Analysis of Methods for Determining Shallow Waterbody Depths Based on Images Taken by Unmanned Aerial Vehicles. Sensors 2022, 22, 1844.
51. Tuśnio, N.; Krzysztofik, I.; Tuśnio, J. Application of Unmanned Aerial Vehicles as a Mobile Monitoring of Fire Hazard. Problems of Mechatronics. Armament, Aviation and Safety Engineering 2014, 5, 101–114. (In Polish).
52. Explore DJI Products in Different Fields. Available online: https://www.dji.com/ (accessed on 24 December 2022).
53. Hercules 10. Available online: https://www.dronevolt.com/en/expertsolutions/ hercules‐10/ (accessed on 24 December 2022).
54. Zoe Portable Versality. Available online: https://acecoretechnologies.com/zoe/ (accessed on 24 December 2022).
55. DroneHexa AG. Available online: https://www.dronetools.es/index.php/dronehexa‐ag (accessed on 24 December 2022).
56. FOX‐C8 XT. Available online: https://www.onyxstar.net/fox‐c8‐xt/ (accessed on 24 December 2022).
57. UAV Systems International. Available online: https://uavsystemsinternational.com/ (accessed on 24 December 2022).

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-5c827863-c9c1-4e32-b760-f7bdecaeea94