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ROS/Gazebo Based Simulation of Co-operative UAVs

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Modelling and Simulation for Autonomous Systems (MESAS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11472))

Abstract

UAVs can be assigned different tasks such as e.g., rendez-vous and space coverage, which require processing and communication capabilities. This work extends the architecture ROS/Gazebo with the possibility of simulation of co-operative UAVs. We assume UAV with the underlying attitude controller based on the open-source Ardupilot software. The integration of the co-ordination algorithm in Gazebo is implemented with software modules extending Ardupilot with the capability of sending/receiving messages to/from drones, and executing the co-ordination protocol. As far as it concerns the simulation environment, we have extended the world in Gazebo to hold more than one drone and to open a specific communication port per drone. In the paper, results on the simulation of a representative co-ordination algorithm are shown and discussed, in a scenario where a small number of Iris Quadcopters are deployed.

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References

  1. 3DRobotics: Dronekit-python’s documentation (2016). http://python.dronekit.io/

  2. Adams, S.M., Friedland, C.J.: A survey of unmanned aerial vehicle (UAV) usage for imagery collection in disaster research and management. In: 9th International Workshop on Remote Sensing for Disaster Response, p. 8 (2011)

    Google Scholar 

  3. ArduPilot-DevTeam: ArduPilot documentation (2016). http://ardupilot.org/ardupilot/

  4. Bernardeschi, C., Domenici, A., Masci, P.: A PVS-simulink integrated environment for model-based analysis of cyber-physical systems. IEEE Trans. Softw. Eng. 44(6), 512–533 (2018)

    Article  Google Scholar 

  5. Chandler, P.R., et al.: Complexity in UAV cooperative control. In: Proceedings of the 2002 American Control Conference (IEEE Cat. No. CH37301), vol. 3, pp. 1831–1836. IEEE (2002)

    Google Scholar 

  6. Dronecode-Project: MAVlink developer guide (2018). https://mavlink.io/en/

  7. Ham, Y., Han, K.K., Lin, J.J., Golparvar-Fard, M.: Visual monitoring of civil infrastructure systems via camera-equipped unmanned aerial vehicles (UAVs): a review of related works. Vis. Eng. 4(1) (2016)

    Google Scholar 

  8. Koenig, N.P., Howard, A.: Design and use paradigms for Gazebo, an open-source multi-robot simulator. In: IROS, vol. 4, pp. 2149–2154. Citeseer (2004)

    Google Scholar 

  9. Larsen, P.G., et al.: Integrated tool chain for model-based design of cyber-physical systems: the INTO-CPS project. In: 2016 2nd International Workshop on Modelling, Analysis, and Control of Complex CPS (CPS Data), pp. 1–6, April 2016

    Google Scholar 

  10. Lu, P., Geng, Q.: Real-time simulation system for UAV based on Matlab/Simulink. In: 2011 IEEE 2nd International Conference on Computing, Control and Industrial Engineering (CCIE), vol. 1, pp. 399–404. IEEE (2011)

    Google Scholar 

  11. Maza, I., Caballero, F., Capitán, J., Martínez-de Dios, J.R., Ollero, A.: Experimental results in multi-UAV coordination for disaster management and civil security applications. J. Intell. Robot. Syst. 61(1–4), 563–585 (2011)

    Article  Google Scholar 

  12. Meyer, Johannes, Sendobry, Alexander, Kohlbrecher, Stefan, Klingauf, Uwe, von Stryk, Oskar: Comprehensive Simulation of Quadrotor UAVs Using ROS and Gazebo. In: Noda, Itsuki, Ando, Noriaki, Brugali, Davide, Kuffner, James J. (eds.) SIMPAR 2012. LNCS, vol. 7628, pp. 400–411. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34327-8_36

    Chapter  Google Scholar 

  13. Olfati-Saber, R., Fax, J.A., Murray, R.M.: Consensus and cooperation in networked multi-agent systems. Proc. IEEE 95(1), 215–233 (2007)

    Article  Google Scholar 

  14. Ollero, A., et al.: AWARE: platform for autonomous self-deploying and operation of wireless sensor-actuator networks cooperating with unmanned aerial vehicles. In: 2007 IEEE International Workshop on Safety, Security and Rescue Robotics, SSRR 2007, pp. 1–6. IEEE (2007)

    Google Scholar 

  15. OSRF: Gazebo API reference (2017). http://osrf-distributions.s3.amazonaws.com/gazebo/api/8.2.0/index.html

  16. OSRF: ROS Wiki: documentation (2018). http://wiki.ros.org/

  17. PX4-DevTeam: Pixhawk series (2018). https://docs.px4.io/en/flight_controller/

  18. Quigley, M., et al.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software, Kobe, Japan, vol. 3, p. 5 (2009)

    Google Scholar 

  19. Quintero, S.A., Papi, F., Klein, D.J., Chisci, L., Hespanha, J.P.: Optimal UAV coordination for target tracking using dynamic programming. In: 2010 49th IEEE Conference on Decision and Control (CDC), pp. 4541–4546. IEEE (2010)

    Google Scholar 

  20. Rasmussen, S.J., Chandler, P.R.: MultiUAV: a multiple UAV simulation for investigation of cooperative control. In: 2002 Proceedings of the Winter Simulation Conference, vol. 1, pp. 869–877. IEEE (2002)

    Google Scholar 

  21. Remondino, F., Barazzetti, L., Nex, F., Scaioni, M., Sarazzi, D.: UAV photogrammetry for mapping and 3D modeling-current status and future perspectives. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 38(1), C22 (2011)

    Google Scholar 

  22. Robusto, C.C.: The cosine-haversine formula. Am. Math. Mon. 64(1), 38–40 (1957)

    Article  MathSciNet  Google Scholar 

  23. Rysdyk, R.: Unmanned aerial vehicle path following for target observation in wind. J. Guid. Control Dyn. 29(5), 1092–1100 (2006)

    Article  Google Scholar 

  24. Semsch, E., Jakob, M., Pavlicek, D., Pechoucek, M.: Autonomous UAV surveillance in complex urban environments. In: Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, vol. 02, pp. 82–85. IEEE Computer Society (2009)

    Google Scholar 

  25. Techy, L., Woolsey, C.A., Schmale, D.G.: Path planning for efficient UAV coordination in aerobiological sampling missions. In: 2008 47th IEEE Conference on Decision and Control, CDC 2008, pp. 2814–2819. IEEE (2008)

    Google Scholar 

  26. Tortonesi, M., Stefanelli, C., Benvegnu, E., Ford, K., Suri, N., Linderman, M.: Multiple-UAV coordination and communications in tactical edge networks. IEEE Commun. Mag. 50(10), 48–55 (2012)

    Article  Google Scholar 

  27. Wise, R., Rysdyk, R.: UAV coordination for autonomous target tracking. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, 6453 (2006)

    Google Scholar 

  28. Pyo, Y., Cho, H., Jung, L., Lim, D.: ROS Robot Programming (English). ROBOTIS, December 2017

    Google Scholar 

  29. Zhang, C., Kovacs, J.M.: The application of small unmanned aerial systems for precision agriculture: a review. Precis. Agric. 13(6), 693–712 (2012)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Information Engineering, University of Pisa, Pisa, Italy

    Cinzia Bernardeschi, Giulio Scrima & Fabio Sofia

  2. Department of Energy, Information Engineering and Mathematical Models, University of Palermo, Palermo, Italy

    Adriano Fagiolini

  3. Department of Information Engineering, University of Florence, Florence, Italy

    Maurizio Palmieri

Authors
  1. Cinzia Bernardeschi
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  2. Adriano Fagiolini
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  3. Maurizio Palmieri
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  4. Giulio Scrima
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  5. Fabio Sofia
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Corresponding author

Correspondence to Cinzia Bernardeschi .

Editor information

Editors and Affiliations

  1. NATO Modelling and Simulation Centre of Excellence, Rome, Italy

    Jan Mazal

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Bernardeschi, C., Fagiolini, A., Palmieri, M., Scrima, G., Sofia, F. (2019). ROS/Gazebo Based Simulation of Co-operative UAVs. In: Mazal, J. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2018. Lecture Notes in Computer Science(), vol 11472. Springer, Cham. https://doi.org/10.1007/978-3-030-14984-0_24

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  • DOI: https://doi.org/10.1007/978-3-030-14984-0_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14983-3

  • Online ISBN: 978-3-030-14984-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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