Skip to main content
SpringerLink
Log in

System Architecture for Autonomous Drone-Based Remote Sensing

  • Conference paper
  • First Online:
Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous 2021)

  • 1489 Accesses

Abstract

Thanks to modern autopilot hardware and software, multi-rotor drones can fly and perform different maneuvers in a precise way, guided merely by high-level commands. This, in turn, opens the way towards fully automated drone-based systems whose operation can be driven by a computer program, without any human intervention. In this work, we present a modular architecture for such a system, which integrates a drone, a hangar, battery charger and a weather station with the necessary software components so as to provide an autonomous remote sensing service, which can operate at the edge while being interfaced as needed with external systems and applications. The proposed system architecture is described in detail, focusing on the core software components and the interaction between them. We also discuss the drone and ground station that is used to test our implementation in the field as well as a simulation environment which allows us to perform a wide range of experiments in a flexible and controlled way.

This research has been co-finance by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH - CREATE - INNOVATE, project PV-Auto-Scout, code T1EDK-02435.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
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. ArduPilot autopilot. http://ardupilot.org

  2. ArduPilot SITL. http://ardupilot.org/dev/docs/sitl-simulator-software-in-the-loop.html

  3. DroneKit. http://dronekit.io/

  4. Gazebo simulator. http://gazebosim.org/

  5. IRLock tracking system. https://irlock.com

  6. MAVProxy software. http://ardupilot.github.io/MAVProxy/html/index.html

  7. Picamera interface. https://github.com/waveform80/picamera

  8. Raspberry Pi 3. https://www.raspberrypi.org/products/raspberry-pi-3-model-b/

  9. Raspberry Pi camera. https://www.raspberrypi.org/products/camera-module-v2/

  10. V5 Nano. http://doc.cuav.net/flight-controller/v5-autopilot/en/v5-nano.html

  11. Boubin, J., Chumley, J., Stewart, C., Khanal, S.: Autonomic computing challenges in fully autonomous precision agriculture. In: IEEE International Conference on Autonomic Computing (ICAC), pp. 11–17 (2019)

    Google Scholar 

  12. Carroll, M., Namjoshi, K.S., Segall, I.: The Resh programming language for multirobot orchestration. arXiv preprint arXiv:2103.13921 (2021)

  13. Casadei, R., Aguzzi, G., Viroli, M.: A programming approach to collective autonomy. J. Sens. Actuator Netw. 10(2), 27 (2021)

    Article  Google Scholar 

  14. Ermacora, G., Rosa, S., Toma, A.: Fly4smartcity: a cloud robotics service for smart city applications. J. Ambient Intell. Smart Environ. 8(3), 347–358 (2016)

    Article  Google Scholar 

  15. Ferrer, A.J., Becker, S., Schmidt, F., Thamsen, L., Kao, O.: Towards a cognitive compute continuum: an architecture for ad-hoc self-managed swarms. arXiv preprint arXiv:2103.06026 (2021)

  16. Gerkey, B., Mataric, M.: Pusher-watcher: an approach to fault-tolerant tightly-coupled robot coordination. In: IEEE International Conference on Robotics and Automation, vol. 1, pp. 464–469 (2002)

    Google Scholar 

  17. Gill, S.S., Chana, I., Singh, M., Buyya, R.: Radar: self-configuring and self-healing in resource management for enhancing quality of cloud services. Concurrency Comput. Pract. Experience 31(1), e4834 (2019)

    Article  Google Scholar 

  18. Kalaitzakis, M., Kattil, S.R., Vitzilaios, N., Rizos, D., Sutton, M.: Dynamic structural health monitoring using a DIC-enabled drone. In: International Conference on Unmanned Aircraft Systems (ICUAS), pp. 321–327 (2019)

    Google Scholar 

  19. Kephart, J.O., Chess, D.M.: The vision of autonomic computing. Computer 36(1), 41–50 (2003)

    Article  MathSciNet  Google Scholar 

  20. Kim, G.H., Nam, J.C., Mahmud, I., Cho, Y.Z.: Multi-drone control and network self-recovery for flying ad hoc networks. In: International Conference on Ubiquitous and Future Networks (ICUFN), pp. 148–150 (2016)

    Google Scholar 

  21. Kosak, O., Huhn, L., Bohn, F., Wanninger, C., Hoffmann, A., Reif, W.: Maple-swarm: programming collective behavior for ensembles by extending HTN-planning. In: International Symposium on Leveraging Applications of Formal Methods, pp. 507–524 (2020)

    Google Scholar 

  22. Koubâa, A., et al.: Dronemap planner: a service-oriented cloud-based management system for the internet-of-drones. Ad Hoc Netw. 86(1), 46–62 (2019)

    Article  Google Scholar 

  23. Koutsoubelias, M., Lalis, S.: TeCoLa: a programming framework for dynamic and heterogeneous robotic teams. In: International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous), pp. 115–124 (2016)

    Google Scholar 

  24. Koutsoubelias, M., Lalis, S.: Fault-tolerance support for mobile robotic applications. In: IEEE International Symposium on Industrial Embedded Systems (SIES), pp. 1–10 (2018)

    Google Scholar 

  25. Kramer, J., Magee, J.: Self-managed systems: an architectural challenge. In: Future of Software Engineering (FOSE), pp. 259–268 (2007)

    Google Scholar 

  26. Lima, K., Marques, E.R., Pinto, J., Sousa, J.B.: Dolphin: a task orchestration language for autonomous vehicle networks. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 603–610 (2018)

    Google Scholar 

  27. Riley, G.F., Henderson, T.R.: The ns-3 network simulator. In: Wehrle, K., Güneş, M., Gross, J. (eds.) Modeling and Tools for Network Simulation, pp. 15–34. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-12331-3_2

  28. Smyczyński, P., Starzec, Ł., Granosik, G.: Autonomous drone control system for object tracking: flexible system design with implementation example. In: IEEE International Conference on Methods and Models in Automation and Robotics (MMAR), pp. 734–738 (2017)

    Google Scholar 

  29. Souli, N., et al.: Horizonblock: implementation of an autonomous counter-drone system. In: International Conference on Unmanned Aircraft Systems (ICUAS), pp. 398–404 (2020)

    Google Scholar 

  30. Toffetti, G., Brunner, S., Blöchlinger, M., Dudouet, F., Edmonds, A.: An architecture for self-managing microservices. In: International Workshop on Automated Incident Management in Cloud, pp. 19–24 (2015)

    Google Scholar 

  31. Yang, T., Foh, C.H., Heliot, F., Leow, C.Y., Chatzimisios, P.: Self-organization drone-based unmanned aerial vehicles (UAV) networks. In: IEEE International Conference on Communications (ICC), pp. 1–6 (2019)

    Google Scholar 

  32. Yapp, J., Seker, R., Babiceanu, R.: UAV as a service: enabling on-demand access and on-the-fly re-tasking of multi-tenant UAVs using cloud services. In: IEEE/AIAA Digital Avionics Systems Conference (DASC), pp. 1–8 (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical and Computer Engineering Department, University of Thessaly, Volos, Greece

    Manos Koutsoubelias, Nasos Grigoropoulos, Giorgos Polychronis, Giannis Badakis & Spyros Lalis

Authors
  1. Manos Koutsoubelias
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nasos Grigoropoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Giorgos Polychronis
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Giannis Badakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Spyros Lalis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Manos Koutsoubelias .

Editor information

Editors and Affiliations

  1. Osaka University, Osaka, Japan

    Takahiro Hara

  2. Osaka University, Osaka, Japan

    Hirozumi Yamaguchi

Rights and permissions

Reprints and permissions

Copyright information

© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Koutsoubelias, M., Grigoropoulos, N., Polychronis, G., Badakis, G., Lalis, S. (2022). System Architecture for Autonomous Drone-Based Remote Sensing. In: Hara, T., Yamaguchi, H. (eds) Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-030-94822-1_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-94822-1_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-94821-4

  • Online ISBN: 978-3-030-94822-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation