2D path planning of UAVs with genetic algorithm in a constrained environment

Path planning of an Unmanned Aerial Vehicle (UAV) for avoiding obstacles can be accomplished by finding a solution to an optimization problem. It is a hard problem to solve, especially when the number of control points is high. Evolutionary algorithms have emerged as a choice for this type of NP-Hard problems. The Genetic Algorithm may be good for solving the optimization problems for path planning of UAV, and this algorithm may achieve an acceptable solution in an acceptable time. In this paper, it is tried to give an answer about that how an appropriate path planning for a UAV can be done in the 2-dimensional environment by avoiding Forbidden Zones such as NOTAM areas, radar sites, buildings, etc. Usage of genetic algorithm is presented as TSP problem domain. For this target, the theoretical structure about the UAV path planning is also presented in the paper. The results showed that, the proposed idea can supply safe paths for autonomous single UAVs.