Akademik Veri Yönetim Sistemi
International Journal of Applied Engineering Research, cilt.11, sa.15, ss.8397-8401, 2016 (Scopus)
© Research India Publications.Due to its low cost, small size, autonomous structure and high mobility, usage of the Unmanned Aerial Vehicles (UAVs) has been increasing over the last two decades. To construct an autonomous UAV, path planning is a crucial task to meet the objectives specified for the mission. Mainly, the purpose of path planning can be described as find the optimal path from a start point to the destination point to check necessary control points (CPs) while taking into consideration different operational constraints. While the number of CPs increases, constructing an optimal path is getting trivial, most of the researchers used evolutionary algorithms and/or swarm algorithms to reach a near optimal solution in an acceptable time. In this study, it is aimed to solve the UAV Path Planning problem with a swarm intelligence algorithm as Ant Colony Optimization Algorithm. To implement this algorithm with similar to the real world, each ant is aimed to implement as an autonomous agent, and the proposed system is implemented on NetLogo, which is a multi-agent programmable modeling environment for simulating real World problems. The experimental results showed that the proposed system produces an acceptable solution in a limited time.