Skip to main content

AR-Based Visual Aids for sUAS Operations in Security Sensitive Areas

  • Conference paper
  • First Online:
Book cover Augmented Reality, Virtual Reality, and Computer Graphics (AVR 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12242))

Abstract

The use of UAVs has recently been proposed for services in civil airports and other sensitive areas. Besides specific regulations from authorities, the situation awareness of the UAV operator is a key aspect for a safe coexistence between manned and unmanned traffic. The operator must be provided in real-time with contextually relevant information, in order to take the proper actions promptly based on the notified contingency. Augmented reality can be adopted to superimpose such additional information on the real-world scene. After the definition of an architecture for the integration of drone operations in the airspace, in this paper the interface and the layout of an augmented reality application for the situation awareness of the pilot are designed and discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Federal Aviation Administration: Operation and Certification of Small Unmanned Aircraft Systems. Technical report (2016)

    Google Scholar 

  2. Ren, L., et al.: Small unmanned aircraft system (sUAS) categorization framework for low altitude traffic services. In: Proceedings of the AIAA/IEEE Digital Avionics Systems Conference, pp. 1–10 (2017)

    Google Scholar 

  3. Giulietti, F., Pollini, L., Avanzini, G.: Visual AIDS for safe operation of remotely piloted vehicles in the controlled air space. Proc. Inst. Mech. Eng. Part G J. Aerosp. Eng. 230(9), 1641–1654 (2016)

    Article  Google Scholar 

  4. Kopardekar, P., et al.: Unmanned aircraft system traffic management (UTM) concept of operations. In: 16th AIAA Aviation Technology, Integration, and Operations Conference (2016)

    Google Scholar 

  5. Mattei, A.P., et al.: UAV in - flight awareness: a tool to improve safety. In: 5th European Conference for Aerospace Sciences (EUCASS), p. 15 (2013)

    Google Scholar 

  6. Templin, F.L., et al.: Requirements for an integrated UAS CNS architecture. In: Integrated Communications, Navigation and Surveillance Conference (ICNS), pp. 2E4-1-2E4-11 (2017)

    Google Scholar 

  7. Avanzini, G., Martínez, D.S.: Risk assessment in mission planning of uninhabited aerial vehicles. Proc. Inst. Mech. Eng. Part G J. Aerosp. Eng. 233(10), 3499–3518 (2019)

    Article  Google Scholar 

  8. Rebane, G.: EASA basic regulation: improving the performance of the european aviation safety system. Zeitschrift fur Luft- und Weltraumrecht - German J. Air Space Law 68, 51 (2019)

    Google Scholar 

  9. Endsley, M.R.: Toward a theory of situation awareness in dynamic systems (2017)

    Google Scholar 

  10. Endsley, M.R.: Designing for situation awareness in complex systems. In: Second International Workshop on Symbiosis of Humans, Artifacts and Environment, pp. 1–14 (2001)

    Google Scholar 

  11. Wither, J., DiVerdi, S., Höllerer, T.: Annotation in outdoor augmented reality. Comput. Graph. (Pergamon) 33(6), 679–689 (2009)

    Article  Google Scholar 

  12. Ruano, S., et al.: Augmented reality tool for the situational awareness improvement of UAV operators. Sensors (Switzerland) 17(2), 297 (2017)

    Article  MathSciNet  Google Scholar 

  13. Zollmann, S., et al.: Image-based X-ray visualization techniques for spatial understanding in outdoor augmented reality. In: Proceedings of the 26th Australian Computer-Human Interaction Conference, OzCHI 2014, Sydney, New South Wales, Australia, pp. 194–203 (2014)

    Google Scholar 

  14. Zollmann, S., et al.: FlyAR: augmented reality supported micro aerial vehicle navigation. IEEE Trans. Vis. Comput. Graph. 20(4), 560–568 (2014)

    Article  Google Scholar 

  15. Cai, Z., Chen, M., Yang, L.: Multi-source information fusion augmented reality benefited decision-making for unmanned aerial vehicles: a effective way for accurate operation. In: Proceedings of the 6th IEEE Conference on Industrial Electronics and Applications, ICIEA 2011, pp. 174–178 (2011)

    Google Scholar 

  16. Wu, H., Cai, Z., Wang, Y.: Vison-based auxiliary navigation method using augmented reality for unmanned aerial vehicles. In: IEEE 10th International Conference on Industrial Informatics (INDIN), pp. 520–525 (2012)

    Google Scholar 

  17. Iwaneczko, P., Jędrasiak, K., Nawrat, A.: Augmented reality in UAVs applications. In: Nawrat, A., Jędrasiak, K. (eds.) Innovative Simulation Systems. SSDC, vol. 33, pp. 77–86. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-21118-3_6

    Chapter  Google Scholar 

  18. ISO: Human-centred design for interactive systems. Ergonomics of human system interaction. Part 210. ISO 9241–210 (2010)

    Google Scholar 

  19. De Paolis, L.T., De Luca, V.: Augmented visualization with depth perception cues to improve the surgeon’s performance in minimally invasive surgery. Med. Biol. Eng. Comput. 57(5), 995–1013 (2018). https://doi.org/10.1007/s11517-018-1929-6

    Article  Google Scholar 

  20. Maiouak, M., Taleb, T.: Dynamic maps for automated driving and UAV geofencing. IEEE Wireless Commun. 26(4), 54–59 (2019)

    Article  Google Scholar 

  21. Zhu, G., Wei, P.: Low-altitude UAS traffic coordination with dynamic geofencing. In: 16th AIAA Aviation Technology, Integration, and Operations Conference (2016)

    Google Scholar 

  22. Epson Moverio BT-300 Drone FPV, Edition, June 2020. https://www.epson.eu/products/see-through-mobile-viewer/moverio-bt-300-drone-fpv-edition

  23. Unity3D, June 2020. https://unity3d.com/

  24. Razzanelli, M., et al.: A visual-haptic display for human and autonomous systems integration. In: Hodicky, J. (ed.) MESAS 2016. LNCS, vol. 9991, pp. 64–80. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47605-6_6

    Chapter  Google Scholar 

  25. Message Queuing Telemetry Transport, June 2020. http://mqtt.org/

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Valerio De Luca .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Avanzini, G., De Luca, V., Pascarelli, C. (2020). AR-Based Visual Aids for sUAS Operations in Security Sensitive Areas. In: De Paolis, L., Bourdot, P. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2020. Lecture Notes in Computer Science(), vol 12242. Springer, Cham. https://doi.org/10.1007/978-3-030-58465-8_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-58465-8_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58464-1

  • Online ISBN: 978-3-030-58465-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics