A UAV PATH PLANNING WITH PARALLEL ACO ALGORITHM ON CUDA PLATFORM


Cekmez U. , ÖZSIĞINAN M., ŞAHİNGÖZ O. K.

International Conference on Unmanned Aircraft Systems (ICUAS), Florida, United States Of America, 27 - 30 May 2014, pp.347-354 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icuas.2014.6842273
  • City: Florida
  • Country: United States Of America
  • Page Numbers: pp.347-354

Abstract

Solving the path planning problem of a UAV is a challenging issue especially if there are too many checkpoints to visit. Mainly, the brute force approach is used to find the shortest path in the mission area, which requires too many times to find a solution. Therefore, evolutionary algorithms and swarm intelligence techniques are used to find a feasible solution in an acceptable time. In this study, path planning problem of a UAV is solved by using a highly parallelized Ant Colony Optimization (ACO) algorithm on CUDA platform. The UAV path is constructed for disseminating keys and collecting data from a Wireless Sensor Network, which is previously defined.