UAV path planning based on adaptive genetic algorithm

With the development of the warfare, it becomes more and more difficult for the military aircraft to attack the target. Path planning is one of the available methods to increase the survival probability. In recent years, genetic algorithm (GA) has been successfully applied to path planning problems for unmanned aerial vehicle (UAV) systems, including single- and multi-vehicle systems. A new encoding method was designed by using bilinear-chain node and the mutation operator with combined operator with reconstruction operator and disturbance operator was improved. An adaptive genetic algorithm (ADGA), which determined the optimal path between the nodes with respect to a set of cost factors and constraints, was applied to the optimal path planning. Example simulation shows that the new algorithm satisfies the requirements in the computation efficiency and the precision of the solution. The algorithm is easy to be realized. Its practicability is improved.