Exploiting Evolution on UAV Control Rules for Spraying Pesticides on Crop Fields
The application of chemicals in agricultural areas is of crucial importance for crop production. The use of aircrafts is becoming increasingly common in carrying out this task mainly because of their speed and effectiveness. Nonetheless, some factors may reduce the yield, or even cause damage, like areas not covered in the spraying process or overlapped spraying areas. Weather conditions add further complexity to the problem. Sets of control rules, to be employed in an autonomous Unmanned Aerial Vehicles (UAV), are very hard to develop and harder to fine-tune to each environment characteristics. Hence, a fine-tuning phase must involves the parameters of the algorithm, due to the mechanical characteristics of each UAV and also must take into account the type of crop being handled and the type of pesticide to be used. In this paper we present an evolutionary algorithm to fine-tune sets of control rules, to be employed in a simulated autonomous UAV. We describe the proposed architecture and investigations about changing in the evolutionary parameters. The results show that the proposed evolutionary method can fine-tune the parameters of the UAV control rules to support environment and weather changes in the simulated environment, encouraging the deployment of the system with real hardware.
KeywordsGenetic Algorithm Sensor Node Wireless Sensor Network Control Rule Real Hardware
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- 1.Bergamini, L., Crociani, C.: Vitaletti: Simulation vs real testbeds: a validation of wsn simulators. Technical report n. 3, Sapienza Universita di Roma (2009)Google Scholar
- 2.Branco, K.R., Pelizzoni, J.M., Neris, L.O., Junior, O.T., Osorio, F.S., Wolf, D.F.: Tiriba - a new approach of uav based on model driven development and multiprocessors (2011)Google Scholar
- 3.Chen, H., Chang, K., Agate, C.S.: A dynamic path planning algorithm for uav tracking. In: SPIE Defense, Security, and Sensing (2009)Google Scholar
- 5.Faical, B.S., Costa, F.G., Pessin, G., Ueyama, J., Freitas, H., Colombo, A., Fini, P.H., Villas, L., Osorio, F.S., Vargas, P.A., Braun, T.: The use of unmanned aerial vehicles and wireless sensor networks for spraying pesticides. Journal of Systems Architecture 60(4), 393–404 (2014)CrossRefGoogle Scholar
- 7.Li, B., Liu, R., Liu, S., Liu, Q., Liu, F., Zhou, G.: Monitoring vegetation coverage variation of winter wheat by low-altitude uav remote sensing system. Trans. of the Chinese Society of Agricultural Engineering 28(13), 160–165 (2012)Google Scholar
- 8.Malekzadeh, M., Ghani, A.A.A., Subramaniam, S., Desa, J.: Validating reliability of omnet++ in wireless networks dos attacks: Simulation vs. testbed. International Journal of Network Security 12(3), 193–201 (2011)Google Scholar
- 9.Ouyang, J., Zhuang, Y., Xue, Y., Wang, Z.: Uav relay transmission scheme and its performance analysis over asymmetric fading channels. Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica 34(1), 130–140 (2013)Google Scholar
- 11.Price, K.V., Storn, R.M., Lampinen, J.A.: Differential evolution a practical approach to global optimization (2005)Google Scholar