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Proceedings of the 16th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 25

UAV Mission Definition and Implementation for Visual Inspection

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DOI: http://dx.doi.org/10.15439/2021F24

Citation: Proceedings of the 16th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 25, pages 343346 ()

Full text

Abstract. This paper describes the architecture of a UAV-based flight mission-definition system. The primary objective aims at improving mission planning efficiency for conducting inspection activities using Unmanned Aerial Vehicles (UAV), concerning state-of-the-art waypoint-based techniques. During testing, the autonomous execution of the trajectory reduced the time required in all cases by almost a half while achieving the same output as a user-controlled manual flight. The proposed solution extends the possibilities of users in creating complex flight trajectories and significantly contributes to the higher time efficiency of recurrent flights.

References

  1. Xue, J., & Su, B. (2017). Significant remote sensing vegetation indices:A review of developments and applications. Journal of Sensors, 2017. https://doi.org/10.1155/2017/1353691
  2. Radoglou-Grammatikis, P., Sarigiannidis, P., Lagkas, T., & Moscholios, I. (2020). A compilation of UAV applications for precision agriculture. Computer Networks, 172(January), 107148. https://doi.org/10.1016/j.comnet.2020.107148
  3. Arenella, A.; Greco, A.; Saggese, A.; Vento, M., Real Time Fault Detection in Photovoltaic Cells by Cameras on Drones. In Image Analysis and Recognition, Proceedings ofthe 14th International Conference, ICIAR 2017, Montreal, QC, Canada, 5–7 July 2017; Karray, F., Campilho, A., Cheriet, F., Eds.; Springer International Publishing: Cham, Switzerland, 2017; pp. 617–625.
  4. Addabbo, P., Angrisano, A., Bernardi, M. L., Gagliarde, G., Mennella, A., Nisi, M., & Ullo, S. L. (2018). UAV system for photovoltaic plant inspection. IEEE Aerospace and Electronic Systems Magazine, 33(8), 58–67. https://doi.org/10.1109/MAES.2018.170145
  5. Hallermann, N., & Morgenthal, G. (2013). Unmanned aerial vehicles (UAV) for the assessment of existing structures. Long Span Bridges and Roofs - Development, Design and Implementation, September. https://doi.org/10.2749/222137813808627172
  6. Stokkeland, M., Klausen, K., & Johansen, T. A. (2015). Autonomous visual navigation of Unmanned Aerial Vehicle for wind turbine inspection. 2015 International Conference on Unmanned Aircraft Systems, ICUAS 2015, 998–1007. https://doi.org/10.1109/ICUAS.2015.7152389
  7. Tudevdagva, U., Battseren, B., Hardt, W., Blokzyl, S., & Lippmann, M. (2017). UAV-based Fully Automated Inspection System for High Voltage Transmission Lines Unmanned Aerial Vehicle-Based Fully Automated Inspection System for High Voltage Transmission Lines. Automation and software engineering , 1(19).
  8. Liu, X., Miao, X., Jiang, H., & Chen, J. (2020). Data analysis in visual power line inspection: An in-depth review of deep learning for component detection and fault diagnosis. Annual Reviews in Control, 50(June), 253–277. https://doi.org/10.1016/j.arcontrol.2020.09.002