Edin DOLICANIN1, Irfan FETAHOVIC1, Eva TUBA2, Romana CAPOR-HROSIK3, Milan TUBA4*
1 Dept. of Technical Sciences, State University of Novi Pazar, Vuka Karadzica bb, Novi Pazar, 36300, Serbia
2 Faculty of Informatics and Computing, Singidunum University, Danijelova 32, Belgrade, 11000, Serbia
3 Inst. for Marine and Coastal Res., Univ. of Dubrovnik, Kneza Damjana Jude 12, Dubrovnik, 20000, Croatia
4 Dept. of Mathematical Sci., State University of Novi Pazar, Vuka Karadzica bb, Novi Pazar, 36300, Serbia
firstname.lastname@example.org (* Corresponding author)
ABSTRACT: The use of the unmanned aerial vehicles is rapidly growing in ever wider range of applications where military use is among the oldest ones. One of the fundamental problems in the unmanned combat aerial vehicles control is the path planning problem that refers to establish the optimal route from the start position to the target, where optimality can be defined in numerous ways. Path planning represents a multi-objective constrained hard optimization problem. In this paper, we adjusted a recent swarm intelligence brain storm optimization algorithm for finding the unmanned combat aerial vehicle optimal path considering fuel consumption and safety degree. The proposed method was tested and compared to eleven different methods from literature. Based on the simulation results, it can be concluded that our proposed approach is robust, exhibits better performance in almost all cases and has potential for further improvements.
KEYWORDS: Unmanned combat aerial vehicle, Path planning, Swarm intelligence, Brain storm optimization.
>>FULL TEXT: PDF
CITE THIS PAPER AS:
Edin DOLICANIN, Irfan FETAHOVIC, Eva TUBA, Romana CAPOR-HROSIK, Milan TUBA*, Unmanned Combat Aerial Vehicle Path Planning by Brain Storm Optimization Algorithm, Studies in Informatics and Control, ISSN 1220-1766, vol. 27(1), pp. 15-24, 2018.