Optimal Flight Path Planner for an Unmanned Helicopter by Evolutionary Algorithms
Lu‐Tao Zhao, V. R. Krishna Murthy · AIAA Guidance, Navigation, and Control Conference and Exhibit · 2007
This paper presents an evolutionary method to develop an optimal flight path planner for an unmanned helicopter with initial, fi nal states, and waypoint constraints under certain prescribed operational en vironment. The operational environment consists of concave and non-concave obstacles which are represented by different geometric shapes and their combinations. The minimum flight time is considered as the objective function in the optimiz ation process. The stochastic universal sampling selection technique, mutation and crossover operators are implemented in the evolutionary method. Finally, the method is validated by applying to optimal flight path problems in highly constrained operational environments.