Title :
Fuzzy ant colony algorithm for terrain following optimization
Author :
Taylor, B. ; Choi, Anthony
Author_Institution :
iAccess Technol., Inc., Warner Robins, GA, USA
Abstract :
Ant colony optimization is a class of swarm intelligence algorithms used to solve combinatorial optimization problems. Fuzzy ant colony optimization adds fuzzy logic to combine heuristic data used in the algorithm. In this paper, a fuzzy ant colony algorithm is applied to a class of path planning known as terrain following optimization. Terrain following optimization attempts to find paths through which terrain can be used to avoid line of sight based detection. The algorithm is tested against both controlled test cases and real world terrain. The results show the algorithm effectively balances terrain masking and path length to create flyable terrain masking paths.
Keywords :
aircraft control; ant colony optimisation; fuzzy logic; fuzzy set theory; path planning; ant colony optimization; combinatorial optimization problems; flyable terrain masking paths; fuzzy ant colony algorithm; fuzzy logic; heuristic data; path length; path planning; sight based detection; swarm intelligence algorithms; terrain following optimization; Aircraft; Algorithm design and analysis; Fuzzy logic; Heuristic algorithms; Optimization; Path planning; Radar; ant colony; fuzzy logic; terrain following optimization; terrain masking;
Conference_Titel :
Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
Conference_Location :
San Diego, CA
DOI :
10.1109/SMC.2014.6974528