Abstract
Quadrotors and UAVs in general are becoming as attractive instruments to safely and efficiently perform environmental monitoring missions. In professional use, quadrotors are manually controlled by expert operators via a remote controller. In research, several projects provide various degrees of automation for the execution of the mission; however, those projects are based on the use of programming languages which are too distant from the background of the stakeholders operating in the field (e.g., fire fighters, policemen, etc.).
In this paper we propose FLYAQ, a platform enabling to (i) graphically define monitoring missions via a web interface, (ii) decompose the mission according to the number and nature of available quadrotors, and (iii) generate the implementation code orchestrating all the quadrotors of the swarm to fulfil the common goal of the mission. The FLYAQ platform enables operators to focus on the mission itself, rather than on technical concerns arising from the use of quadrotors.
A reconfiguration engine is specifically designed to make the swarm resilient to faults and external events that may compromise the mission. Moreover, under some limitations explained in the paper, the reconfiguration engine permits to change the mission at run-time. The FLYAQ platform will be distributed as an open-source product.
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References
Kendoul, F.: Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems. J. Field Robot. 29(2), 315–378 (2012)
Nathan, P., Almurib, H., Kumar, T.: A review of autonomous multi-agent quad-rotor control techniques and applications. In: 2011 4th International Conference on Mechatronics (ICOM), pp. 1–7 (2011)
Martinelli, A.: Vision and imu data fusion: Closed-form solutions for attitude, speed, absolute scale, and bias determination. IEEE Transactions on Robotics 28(1), 44–60 (2012)
Likhachev, M., Ferguson, D.: Planning long dynamically feasible maneuvers for autonomous vehicles. Int. J. Rob. Res. 28(8), 933–945 (2009)
Achtelik, M., Weiss, S., Chli, M., Siegwart, R.: Path planning for motion dependent state estimation on micro aerial vehicles. In: Proc. of the IEEE International Conference on Robotics and Automation (ICRA) (May 2013)
Schmidt, D.C.: Guest Editor’s Introduction: Model-Driven Engineering. Computer 39(2), 25–31 (2006)
Czarnecki, K., Helsen, S.: Feature-based survey of model transformation approaches. IBM Syst. J. 45, 621–645 (2006)
Bettini, C., Brdiczka, O., Henricksen, K., Indulska, J., Nicklas, D., Ranganathan, A., Riboni, D.: A survey of context modelling and reasoning techniques. Pervasive and Mobile Computing 6(2), 161–180 (2010)
Hehn, M., D’Andrea, R.: Quadrocopter trajectory generation and control. In: IFAC World Congress, pp. 1485–1491 (2011)
Augugliaro, F., Schoellig, A.P., D’Andrea, R.: Generation of collision-free trajectories for a quadrocopter fleet: A sequential convex programming approach. In: IEEE/RSJ International Conf. on Intelligent Robots and Systems (IROS), pp. 1917–1922 (2012)
Leonard, J., Savvaris, A., Tsourdos, A.: Towards a fully autonomous swarm of unmanned aerial vehicles. In: 2012 UKACC International Conf. on Control (CONTROL), pp. 286–291 (September 2012)
Andert, F., Adolf, F., Goormann, L., Dittrich, J.: Mapping and path planning in complex environments: An obstacle avoidance approach for an unmanned helicopter. In: Intl. Conf. on Robotics and Automation (ICRA), pp. 745–750 (May 2011)
Merz, T., Kendoul, F.: Beyond visual range obstacle avoidance and infrastructure inspection by an autonomous helicopter. In: Intl. Conf. on Intelligent Robots and Systems (IROS), pp. 4953–4960 (September 2011)
Zhang, T., Li, W., Achtelik, M., Kühnlenz, K., Buss, M.: Multi-sensory motion estimation and control of a mini-quadrotor in an air-ground multi-robot system. In: Intl. Conf. on Robotics and Biomimetics, ROBIO 2009, pp. 45–50. IEEE Press (2009)
Bouabdallah, S., Siegwart, R.: Full control of a quadrotor. In: Intl. Conf. on Intelligent Robots and Systems, pp. 153–158 (2007)
Kendoul, F., Zhenyu, Y., Nonami, K.: Embedded autopilot for accurate waypoint navigation and trajectory tracking: Application to miniature rotorcraft uavs. In: Intl. Conf. on Robotics and Automation, pp. 2884–2890 (May 2009)
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Di Ruscio, D., Malavolta, I., Pelliccione, P. (2013). Engineering a Platform for Mission Planning of Autonomous and Resilient Quadrotors. In: Gorbenko, A., Romanovsky, A., Kharchenko, V. (eds) Software Engineering for Resilient Systems. SERENE 2013. Lecture Notes in Computer Science, vol 8166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40894-6_3
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DOI: https://doi.org/10.1007/978-3-642-40894-6_3
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