Real-time route planning for UAV based on weather threat

UAVs may encouter execrable weather, terrain threat, firepower threat or task object changed while it was flying along the fixed route, a real-time route planning method was proposed. The mechanism how to solve these unexpected problems while flying was given. The rule of state conversion and pheromone updating were improved on the basis of traditional Ant Colony Algorithm(ACA). Some parameters were self-adaptive optimized, genetic operations and smoothness method were introduced in the Improved Ant Colony Algorithm(I-ACA). Two situations were simulated combined with real-time weather threat, in which target object was changed or not. Simulation results show that the real-time route planning strategy has strong ability to search real-time routes fast. It is able to solve abrupt problems well and offer real-time viable, safe and optimal routes for UAVs.