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An Unmanned Aircraft System for Automatic Forest Fire Monitoring and Measurement


The paper presents an Unmanned Aircraft System (UAS), consisting of several aerial vehicles and a central station, for forest fire monitoring. Fire monitoring is defined as the computation in real-time of the evolution of the fire front shape and potentially other parameters related to the fire propagation, and is very important for forest fire fighting. The paper shows how an UAS can automatically obtain this information by means of on-board infrared or visual cameras. Moreover, it is shown how multiple aerial vehicles can collaborate in this application, allowing to cover bigger areas or to obtain complementary views of a fire. The paper presents results obtained in experiments considering actual controlled forest fires in quasi-operational conditions, involving a fleet of three vehicles, two autonomous helicopters and one blimp.

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  1. Ambrosia, V.: Remotely piloted vehicles as fire imaging platforms: the future is here! Wildfire Magazine (2002)

  2. Ambrosia, V., Wegener, S., Sullivan, D., Buechel, S., Brass, S.D.J., Stoneburner, J., Schoenung, S.: Demonstrating UAV-aquired real-time thermal data over fires. Photogramm. Eng. Remote Sensing 69(4), 391–402 (2003)

    Google Scholar 

  3. Arrue, B., Ollero, A., Martínez de Dios, J.: An intelligent system for false alarm reduction in infrared forest-fire detection. IEEE Intell. Syst 15(3), 64–73 (2000)

    Article  Google Scholar 

  4. Campbell, D., Born, W.G., Beck, J., Bereska, B., Frederick, K., Hua, S.: Airborne wildfire intelligence system: a decision support tool for wildland fire managers in Alberta. In: Proc. SPIE, Thermosense XXIV, vol. 4710, pp. 159–170 (2002)

  5. Casbeer, D., Kingston, D., Bear, R., McLain, T., Li, S.: Cooperative forest fire surveillance using a team of small unmanned air vehicles. Int. J. Syst. Sci. 37(6), 351–360 (2006)

    Article  MATH  Google Scholar 

  6. Chuvieco, E., Martin, P.: A simple method for fire growth mapping using AVHRR channel 3 data. Int. J. Remote Sens. 15, 3141–3146 (1994)

    Article  Google Scholar 

  7. de Vries, J.S., Kemp, R.A.: Results with a multispectral autonomous wildfire detection system. In: Proc. SPIE Infrared Technology XX, vol. 2269, pp. 18–28 (1994)

  8. Den Breejen, E., Breuers, M., Cremer, F., Kemp, R., Roos, M., Schutte, K., De Vries, J.: Autonomous forest fire detection. In: Proc. 3rd Int. Conf. on Forest Fire Research, pp. 2003–2012 (1998)

  9. Dierre, D., Hoff, H., Bouchet, M.: RAPSODI: Rapid smoke detection and forest fire control. In: Int. Symposium on Forest Fire: Needs and Innovations, pp. 415–419 (1999)

  10. Ferruz, J., Ollero, A.: Real-time feature matching in image sequences for non-structured environments. Applications to vehicle guidance. J. Intell. Robot. Syst. 28, 85–123 (2000)

    Article  Google Scholar 

  11. Gancet, J., Hattenberger, G., Alami, R., Lacroix, S.: Task planning and control for a multi-UAV system: architecture and algorithms. In: Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1017–1022 (2005)

  12. Gómez Rodríguez, F., Pascual Peña, S., Arrue, B., Ollero, A.: Smoke detection using image processing. In: Proc. IV Intl. Congress on Forest Fire Research ICFFR (2002)

  13. Gonzalo, J.: Fuego: a low cost service for fire detection. In: Proc. 3rd Int. Conf. on Forest Fire Research, p. 2029 (1998)

  14. Hargrove, W., Gardner, R., Turner, M., Romme, W., Despain, D.: Simulating fire patterns in heterogeneous landscapes. Ecol. Model. 135, 243–263 (2000)

    Article  Google Scholar 

  15. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004)

    Book  MATH  Google Scholar 

  16. Hygounenc, E., Jung, I.K., Soueres, P., Lacroix, S.: The Autonomous Blimp Project of LAAS-CNRS: Achievements in Flight Control and Terrain Mapping. Int. J. Rob. Res. 23(4–5), 473–511 (2004)

    Article  Google Scholar 

  17. Julier, S., Uhlmann, J.: A new extension of the kalman filter to nonlinear systems. In: Proc. of the 11th Int. Symp. on Aerospace/Defence Sensing, Simulation and Controls (1997)

  18. Kelhä, V., Rauste, Y., Häme, T., Sephton, T., Buongiorno, A., Frauenberger, O., Soini, K., Venäläinen, A., San-Miguel-Ayanz, J., Vainio, T.: Combining AVHRR and ATSR satellite sensor data for operational boreal forest fire detection. Int. J. Remote Sens. 24(8), 1691–1708 (2003)

    Article  Google Scholar 

  19. Kontitsis, M., Valavanis, K., Tsourveloudis, N.: A UAV vision system for airborne surveillance. In: Proc. of the IEEE International Conference on Robotics and Automation, pp. 77–83 (2004)

  20. Lacroix, S., Alami, R., Lemaire, T., Hattenberger, G., Gancet, J.: Multiple Heterogeneous Unmanned Aerial Vehicles, chap. Decision making in multi-UAV systems: architecture and algorithms. Springer Tracks on Advanced Robotics. Springer (2007)

  21. Lemaire, T., Alami, R., Lacroix, S.: A distributed tasks allocation scheme in multi-UAV context. In: Proceedings of the IEEE International Conference on Robotics and Automation, vol. 4, pp. 3622–3627 (2004)

  22. Martínez de Dios, J., André, J., Gonçalves, J.C., Arrue, B., Ollero, A., Viegas, D.: Laboratory fire spread analysis using visual and infrared images. Int. J. Wildland Fire 15, 175–186 (2006)

    Article  Google Scholar 

  23. Martínez-de Dios, J., Merino, L., Ollero, A.: Fire detection using autonomous aerial vehicles with infrared and visual cameras. In: Proc. of the 16th IFAC World Congress. Prague, Czech Republic (2005)

  24. Martínez de Dios, J., Ollero, A.: A multiresolution threshold selection method based on training. Lect. Notes Comput. Sci. 3211, 90–97 (2004)

    Article  Google Scholar 

  25. Maza, I., Caballero, F., Capitan, J., de Dios, J.M., Ollero, A.: A distributed architecture for a robotic platform with aerial sensor transportation and self-deployment capabilities. J. Field Robot. 28(3), 303–328 (2011). doi:10.1002/rob.20383

    Article  Google Scholar 

  26. Maza, I., Caballero, F., Capitan, J., de Dios, J.M., Ollero, A.: Experimental results in multi-UAV coordination for disaster management and civil security applications. J. Intell. Robot. Syst. 61(1), 563–585 (2011). doi:10.1007/s10846-010-9497-5

    Article  Google Scholar 

  27. Merino, L., Caballero, F., Forssén, P., Wiklund, J., Ferruz, J., Martínez de Dios, J., Moe, A., Nordberg, K., Ollero, A.: Advances in Unmanned Aerial Vehicles. State of the Art and the Road to Autonomy, chap. Single and Multi-UAV Relative Position Estimation Based on Natural Landmarks. Springer Tracks on Advanced Robotics. Springer (2007)

  28. Merino, L., Caballero, F., Martínez de Dios, J., Ferruz, J., Ollero, A.: A cooperative perception system for multiple UAVs: application to automatic detection of forest fires. J. Field Robot. 23(3–4), 165–184 (2006)

    Article  Google Scholar 

  29. Ollero, A., Alcázar, J., Cuesta, F., López-Pichaco, F., Nogales, C.: Helicopter teleoperation for aerial monitoring in the COMETS multi-UAV system. In: 3rd IARP Workshop on Service, Assistive and Personal Robots (2003)

  30. Ollero, A., Ferruz, J., Caballero, F., Hurtado, S., Merino, L.: Motion compensation and object detection for autonomous helicopter visual navigation in the comets system. In: Proc. of the IEEE International Conference on Robotics and Automation, pp. 19–24 (2004)

  31. Ollero, A., Lacroix, S., Merino, L., Gancet, J., Wiklund, J., Remuss, V., Veiga, I., Gutiérrez, L.G., Viegas, D.X., González, M., Mallet, A., Alami, R., Chatila, R., Hommel, G., Colmenero, F., Arrue, B., Ferruz, J., Martínez de Dios, J., Caballero, F.: Multiple eyes in the sky: architecture and perception issues in the COMETS unmanned air vehicles project. IEEE Robot. Autom. Mag. 12(2), 46–57 (2005)

    Article  Google Scholar 

  32. Pastora, E., Águeda, A., Andrade-Cetto, J., Munoz, M., Pérez, Y., Planas, E.: Computing the rate of spread of linear flame fronts by thermal image processing. Fire Saf. J. 41, 569–579 (2006)

    Article  Google Scholar 

  33. Phillips, W., Shah, M., da Vitoria Lobo, N.: Flame recognition in video. Pattern Recogn. Lett. 23(1–3), 319–327 (2002). doi:10.1016/S0167-8655(01)00135-0

    Article  MATH  Google Scholar 

  34. Remuß, V., Musial, M., Hommel, G.: Marvin—an autonomous flying robot-bases on mass market. In: International Conference on Intelligent Robots and Systems, IROS. Proc. of the Workshop WS6 Aerial Robotics, pp. 23–28. IEEE/RSJ (2002)

  35. San Miguel Ayanz, J., Ravail, N., Kelha, V., Ollero, A.: Active fire detection for fire emergency management: potential and limitations for the operational use of remote sensing. Nat. Hazards 35(3), 361–376 (2005)

    Article  Google Scholar 

  36. Utkin, A., Fernandes, A., oes A.V. Lavrov, F.S., Vilar, R.: Feasibility of forest-fire smoke detection using lidar. Int. J. Wildland Fire 12(2), 159–166 (2003)

    Article  Google Scholar 

  37. Viegas, D.: Forest fire propagation. Philos. Trans. R. Soc. Lond. A 356, 2907–2928 (1998)

    Article  Google Scholar 

  38. Viegas, D.X., Cruz, M., Ribeiro, L., Silva, A., Ollero, A., Arrue, B., Martínez de Dios, J., Gmez-Rodrguez, F., Merino, L., Miranda, A., Santos, P.: Gestosa fire spread experiments. In: Proc. of the IV International Congress on Forest Fire Research (ICFFR), Coimbra, Portugal, pp. 1–13 (2002)

  39. Viguria, A., Maza, I., Ollero, A.: SET: an algorithm for distributed multirobot task allocation with dynamic negotiation based on task subsets. In: Proceedings of the IEEE International Conference on Robotics and Automation, Rome, Italy, pp. 3339–3344 (2007). doi:10.1109/ROBOT.2007.363988

  40. Viguria, A., Maza, I., Ollero, A.: S+T: an algorithm for distributed multirobot task allocation based on services for improving robot cooperation. In: Proceedings of the IEEE International Conference on Robotics and Automation, Pasadena, California, USA, pp. 3163–3168 (2008). doi:10.1109/ROBOT.2008.4543692

  41. Zhang, Z.: Parameters estimation techniques. A tutorial with application to conic fitting. Image Vis. Comput. 15(1), 59–76 (1997)

    Article  Google Scholar 

  42. Zhou, G., Li, C., Cheng, P.: Unmanned aerial vehicle (UAV) real-time video registration for forest fire monitoring. In: Proc. IEEE Intl. Geoscience and Remote Sensing Symposium IGARSS, vol. 3, pp. 25–29 (2005)

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Correspondence to Luis Merino.

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Merino, L., Caballero, F., Martínez-de-Dios, J.R. et al. An Unmanned Aircraft System for Automatic Forest Fire Monitoring and Measurement. J Intell Robot Syst 65, 533–548 (2012).

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