@article { author = {Abbaspour, R.Ali and Heidari, A.A.}, title = {Optimal Flight Trajectory Planning using Improved Evolutionary Method for UCAV Navigation in 3D Constrained Environments}, journal = {Journal of Aerospace Science and Technology}, volume = {13}, number = {1}, pages = {83-89}, year = {2020}, publisher = {Iranian Aerospace Society}, issn = {1735-2134}, eissn = {2345-3648}, doi = {10.22034/jast.2020.120342}, abstract = {This article addresses a new approach to 3D path planning of UCAVs. To solve this NP-hard problem, imperialist competitive algorithm (ICA) was extended for path planning problem. This research is related to finding optimal trajectories before UCAV missions. Developed planner provides 3D optimal paths for UCAV flight with real DTM of Tehran environment. In UCAV mission, final computed paths should be smooth that made the path planning problems constrained. This planner can offer flyable 3D paths based on mission requirements. It’s a comprehensive study for efficiency evaluation of EA planners, and then novel approach will be proposed and compared to ICA, GA, ABC and PSO algorithms. Then path planning task of UCAV is performed. Simulations show advantage of proposed methodology.}, keywords = {: Unmanned combat aerial vehicle (UCAV),Flight simulation,3D Trajectory Planning,Imperialist Competitive Algorithm}, url = {https://jast.ias.ir/article_120342.html}, eprint = {https://jast.ias.ir/article_120342_3e04750ee0e37754f9e8331c873a8ff8.pdf} }