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Integrated Framework for Fast Prototyping and Testing of Autonomous Systems

  • Luigi PannocchiEmail author
  • Carmelo Di Franco
  • Mauro Marinoni
  • Giorgio Buttazzo
Article
  • 17 Downloads

Abstract

Validating the behavior of a complex system is a fundamental step in the development process to avoid costly damages and dangerous circumstances. Such a phase requires a realistic simulation of the system and the reproduction of the full operative scenario, including the environment with all the possible events and situations in which the system could get into. Although several tools exist to design, simulate and validate specific functions, checking the overall system behavior in an operative scenario usually requires the development of custom simulation frameworks. These are often tailored to the specific system under study, with the consequence that they are either incomplete or not fully reusable for other projects. This paper presents a modular hardware-in-the-loop development simulation framework that allows realistic simulation, supporting multi-vehicle scenario and comprehending tools for reproducing realistic testing environments with advanced sensors. A case of study is presented to show the employment of the proposed framework for testing the behavior of unmanned vehicles, focusing on the timing properties of the system. Category (2).

Keywords

Simulation Hardware-in-the-loop Multi-robot 

Mathematics Subject Classification (2010)

68-04 

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References

  1. 1.
    Ali, K.S., Shumaker, J.L.: Hardware in the loop simulator for multi agent unmanned aerial vehicles environment. Amer. J. Eng. Appl. Sci. 6, 172–177 (2013)CrossRefGoogle Scholar
  2. 2.
    Birk, A., Poppinga, J., Stoyanov, T., Nevatia, Y.: Planetary Exploration in USARsim: A Case Study Including Real World Data from Mars, pp. 463–472. Springer, Berlin (2009)Google Scholar
  3. 3.
    Bryson, M., Reid, A., Ramos, F., Sukkarieh, S.: Airborne vision-based mapping and classification of large farmland environments. J. Field Robot. 27(5), 632–655 (2010)CrossRefGoogle Scholar
  4. 4.
    Carpin, S., Lewis, M., Wang, J., Balakirsky, S., Scrapper, C.: Usarsim: a robot simulator for research and education. In: Proceedings 2007 IEEE International Conference on Robotics and Automation, pp. 1400–1405 (2007)Google Scholar
  5. 5.
    Castillo-Pizarro, P., Arredondo, T.V., Torres-Torriti, M.: Introductory Survey to Open-Source Mobile Robot Simulation Software. In: 2010 Latin American Robotics Symposium and Intelligent Robotics Meeting, pp. 150–155.  https://doi.org/10.1109/LARS.2010.19 (2010)
  6. 6.
    Cook, D., Vardy, A., Lewis, R.: A Survey of Auv and Robot Simulators for Multi-Vehicle Operations. In: 2014 IEEE/OES Autonomous Underwater Vehicles (AUV), pp. 1–8.  https://doi.org/10.1109/AUV.2014.7054411 (2014)
  7. 7.
    Echeverria, G., Lassabe, N., Degroote, A., Lemaignan, S.: Modular Open Robots Simulation Engine: Morse. In: 2011 IEEE International Conference on Robotics and Automation, pp. 46–51.  https://doi.org/10.1109/ICRA.2011.5980252 (2011)
  8. 8.
    Ganoni, O., Mukundan, R.: A framework for visually realistic multi-robot simulation in natural environment. CoRR arXiv:1708.01938 (2017)
  9. 9.
    Kamali, C., Jain, S.: Hardware in the Loop Simulation for a Mini Uav. In: 4Th IFAC Conference on Advances in Control and Optimization of Dynamical Systems ACODS 2016, Vol 49, pp. 700–705. Tiruchirappalli, India (2016)Google Scholar
  10. 10.
    Lange, S., Sunderhauf, N., Protzel, P.: A Vision Based Onboard Approach for Landing and Position Control of an Autonomous Multirotor Uav in Gps-Denied Environments. In: 2009 International Conference on Advanced Robotics, pp. 1–6 (2009)Google Scholar
  11. 11.
    Lugo-Cardenas, I., Salazar, S., Lozano, R.: The Mav3dsim Hardware in the Loop Simulation Platform for Research and Validation of Uav Controllers. In: 2016 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1335–1341 (2016)Google Scholar
  12. 12.
    Lum, C., Rowland, M., Rysdyk, R.: chap. Human-in-the-Loop Distributed Simulation and Validation of Strategic Autonomous Algorithms. Fluid Dynamics and Co-located Conferences. American Institute of Aeronautics and Astronautics.  https://doi.org/10.2514/6.2008-4366.0 (2008)
  13. 13.
    Meier, L., Honegger, D., Pollefeys, M.: Px4: a node-based multithreaded open source robotics framework for deeply embedded platforms. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 6235–6240 (2015)Google Scholar
  14. 14.
    Merino, L., Caballero, F., Martinez-de Dios, J., Maza, I., Ollero, A.: An unmanned aircraft system for automatic forest fire monitoring and measurement. J. Intell. Robot. Syst. 65, 533–548 (2012)CrossRefGoogle Scholar
  15. 15.
    Mueller, E.R.: Hardware-in-the-loop simulation design for evaluation of unmanned aerial vehicle control systems. In: Proceedings of the AIAA Modeling and Simulation Technologies Conference and Exhibit (2007)Google Scholar
  16. 16.
    Odelga, M., Stegagno, P., Bülthoff, H.H., Ahmad, A.: A Setup for Multi-Uav Hardware-In-The-Loop Simulations. In: 2015 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), pp. 204–210.  https://doi.org/10.1109/RED-UAS.2015.7441008 (2015)
  17. 17.
    Pannocchi, L., Marinoni, M., Buttazzo, G.: Hardware-In-The-Loop Development Framework for Multi-Vehicle Autonomous Systems. In: 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), pp. 17–22.  https://doi.org/10.1109/ICARSC.2017.7964046 (2017)
  18. 18.
    Parodi, O., Lapierre, L., Jouvencel, B.: Hardware-in-the-loop simulators for multi-vehicles scenarios: survey on existing solutions and proposal of a new architecture. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 225–230 (2009)Google Scholar
  19. 19.
    Pollini, L., Parnenzini, V., Innocenti, M.: Distributed Real-Time Hardware- and Man-In-The-Loop Simulation for the Icaro Ii Unmanned Systems Autopilot. In: Latest Trends in Information Technology/Recent Advances in Computer Engineering Series 7, pp. 420–427 (2012)Google Scholar
  20. 20.
    Posch, A., Sukkarieh, S.: Uav Based Search for a Radio Tagged Animal Using Particle Filters. In: Australasian Conference on Robotics and Automation (ACRA). Sydney, Australia (2009)Google Scholar
  21. 21.
    Barros dos Santos, S.R., Givigi, S., Nascimento, C.L.J., Oliveira, N.: Modeling of a hardware-in-the-loop simulator for uav autopilot controllers. In: Proceedings of the 21th Brazilian Congress of Mechanical Engineering (COBEM 2011), Natal, Brazil (2011)Google Scholar
  22. 22.
    Sehgal, A., Cernea, D.: A Multi-Auv Missions Simulation Framework for the Usarsim Robotics Simulator. In: 2010 18Th Mediterranean Conference On Control Automation (MED), pp. 1188–1193.  https://doi.org/10.1109/MED.2010.5547632 (2010)
  23. 23.
    Shah, S., Dey, D., Lovett, C., Kapoor, A.: Airsim: High-fidelity visual and physical simulation for autonomous vehicles. In: Field and Service Robotics. arXiv:1705.05065 (2017)
  24. 24.
    Takaya, K., Asai, T., Kroumov, V., Smarandache, F.: Simulation Environment for Mobile Robots Testing Using Ros and Gazebo. In: 2016 20Th International Conference on System Theory, Control and Computing (ICSTCC), pp. 96–101.  https://doi.org/10.1109/ICSTCC.2016.7790647 (2016)

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© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Scuola Superiore Sant’AnnaPisaItaly

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