The coordinated route-planning problem for multiple unmanned air vehicles (UAVs), a cooperative optimization problem, also a non-cooperative game, is addressed in the framework of game theory. A Nash equilibrium based route planner is proposed. The rational is that the structure of UAV sub-team usually provides some inherent and implicit preference information, which help to find the optimum coordinated routes and the optimum combination of the various objective functions. The route planner combines the concepts of evolutionary computation with problem-specific chromosome structures and evolutionary operators and handles different kinds of mission constraints in hierarchical style. Cooperation and competition among UAVs are reflected by the definition of fitness function. Simulations validate the feasibility and superiority of the game-theoretic coordinated routes planner.
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