Autonomous Decisional High-level Planning for UAVs-based Forest-fire Localization

Assia Belbachir, Juan-Antonio Escareno

Abstract

This paper addresses the problem of forest-fire localization using unmanned aerial vehicles (UAVs). Due to the fast deployment of UAVs, it is practical to use them. In forest fires, usually the area to explore is unknown. Thus, existing studies use an automatic or semi-automatic exploration strategy following a zig-zag sweep pattern or expanding spiral search pattern. However, such an approach is not optimal in terms of exploration time since the mission execution and achievement in an unknown environment requires autonomous vehicle decision and control. This paper presents an enhanced approach for the fire localization mission via a decisional strategy considering a probabilistic model that uses the temperature to estimate the distance towards the forest fire. The UAV optimizes its trajectory according to the state of the forest-fire knowledge by using a map to represent its knowledge and updates it at each exploration step. We show in this paper that our planning and control methodology for forest-fire localization is efficient. Simulation results are carried out to evaluate the feasibility of the generated paths by the proposed methodology.

References

  1. Ambrosia, V., Wegener, S., Sullivan, D., Buechel, S., Dunagan, S. E., Brass, J. A., and Stoneburner, J. (2003).
  2. Demonstrating uav-acquired real-time thermal data over fires. Photogrammetric Engineering and Remote Sensing,, 69:391-402. Full text available.
  3. Beard, R. W., McLain, T. W., Goodrich, M. A., and Anderson, E. P. (2002). Coordinated target assignment and intercept for unmanned air vehicles. IEEE Transactions on Robotics and Automation, 18(6):911-922.
  4. Belbachir, A., Ingrand, F., and Lacroix, S. (2012). A cooperative architecture for target localization using multiple auvs. Intelligent Service Robotics, 5(2):119-132.
  5. Brescianini, D., Hehn, M., and D'Andrea, R. (2013). Quadrocopter pole acrobatics. In Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on, pages 3472-3479.
  6. Chen, X., Gao, W., and Wang, J. (2013). Robust allsource positioning of uavs based on belief propagation. EURASIP Journal on Advances in Signal Processing, 2013(1).
  7. Di Paola, D., Gasparri, A., Naso, D., and Lewis, F. (2015). Decentralized dynamic task planning for heterogeneous robotic networks. Autonomous Robots, 38(1):31-48.
  8. G. Loianno, J. T. and Kumar, V. (2015). Cooperative localization and mapping of mavs using rgb-d sensors. In IEEE International Conference on Robotics and Automation (ICRA), pages 4021 - 4028, Seattle, WA USA.
  9. Ingrand, F., Lacroix, S., Lemai-Chenevier, S., and Py, F. (2007). Decisional autonomy of planetary rovers. Journal of Field Robotics, 24(7):559-580.
  10. Low, K. H., Dolan, J. M., and Khosla, P. (2009). Information-theoretic approach to efficient adaptive path planning for mobile robotic environmental sensing. In Proceedings of the 19th International Conference on Automated Planning and Scheduling (ICAPS09).
  11. Maza, J. I., Caballero, F., Capitán, J., Martinez de Dios, J. R., and Ollero, A. (2011). Experimental results in multi-uav coordination for disaster management and civil security applications. Journal of Intelligent and Robotic Systems, 61(1-4):563-585.
  12. McGann, C., Py, F., Rajan, K., Thomas, H., et Henthorn, R., and et McEwen, R. (2007). T-rex: A deliberative system for auv control. ICAPS.
  13. Merino, L., and. J.R. Martinez-de Dios, F. C., Ferruz, J., and Ollero, A. (2006). A cooperative perception system for multiple UAVs: Application to automatic detection of forest fires. Journal of Field Robotics, 23:165- 184.
  14. Merino, L., Caballero, F., de Dios, J. M., , Maza, I., and Ollero, A. (2010). Automatic forest fire monitoring and measurement using unmanned aerial vehicles. In Proc. of the VI Intl. Congress on Forest Fire Research ICFFR.
  15. Moorehead, S., Simmons, R., and Whittaker, W. (2001). Autonomous exploration using multiple sources of information. In Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on, volume 3, pages 3098-3103 vol.3.
  16. Nikolos, I. and Brintaki, A. (2005). Coordinated uav path planning using differential evolution. In Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation, pages 549-556.
  17. Ollero, A., Lacroix, S., Merino, L., Gancet, J., Wiklund, J., Remuss, V., Veiga, I., Gutierrez, L. G., Viegas, D. X., A.Gonzalez, M., Mallet, A., Alami, R., Chatila, R., Hommel, G., Colmenero, F. J., Arrue, B., Ferruz, J., Martinez, J. R., and Caballero, F. (2005). Multiple eyes in the sky: Architecture and perception issues in the COMETS unmanned air vehicles project. IEEE Robotics and Automation Magazine, 12(2):46-57.
  18. Parra-Vega, V., Sanchez, A., Izaguirre, C., Garcia, O., and Ruiz-Sanchez, F. (2012). Toward aerial grasping and manipulation with multiple uavs. Journal of Intelligent & Robotic Systems, 70(1):575-593.
  19. Popa, D., Sanderson, A., Komerska, R., Mupparapu, S., Blidberg, R., and Chappel, S. (2004). Adaptive sampling algorithms for multiple autonomous underwater vehicles. Autonomous Underwater Vehicles IEEE/OES, pages 108-118.
  20. Schoellig, A., Wiltsche, C., and D'Andrea, R. (2012). Feedforward parameter identification for precise periodic quadrocopter motions. In American Control Conference (ACC), 2012, pages 4313-4318.
  21. Song, M., Tarn, T., and Xi, N. (2000). Integration of task scheduling, action planning, and control in robotic manufacturing systems. Proceedings of the IEEE, 88(7):1097-1107.
  22. Sujit, P., Sinha, A., and Ghose, D. (2005). Multi-uav task allocation using team theory. In Decision and Control, 2005 and 2005 European Control Conference. CDCECC 7805. 44th IEEE Conference on, pages 1497- 1502.
  23. Thrun, S. (2003). Exploring artificial intelligence in the new millennium. chapter Robotic Mapping: A Survey, pages 1-35. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.
  24. Valavanis, K. P. and Valavanis, K. P. (2007). Advances in Unmanned Aerial Vehicles: State of the Art and the Road to Autonomy. Springer Publishing Company, Incorporated, 1st edition.
  25. Zhang, B. and Sukhatme., G. S. (2008). Adaptive sampling with multiple mobile robots. In IEEE International Conference on Robotics and Automation.
Download


Paper Citation


in Harvard Style

Belbachir A. and Escareno J. (2016). Autonomous Decisional High-level Planning for UAVs-based Forest-fire Localization . In Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-198-4, pages 153-159. DOI: 10.5220/0005972501530159


in Bibtex Style

@conference{icinco16,
author={Assia Belbachir and Juan-Antonio Escareno},
title={Autonomous Decisional High-level Planning for UAVs-based Forest-fire Localization},
booktitle={Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2016},
pages={153-159},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005972501530159},
isbn={978-989-758-198-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Autonomous Decisional High-level Planning for UAVs-based Forest-fire Localization
SN - 978-989-758-198-4
AU - Belbachir A.
AU - Escareno J.
PY - 2016
SP - 153
EP - 159
DO - 10.5220/0005972501530159