Evolutionary route planner for unmanned air vehicles

Based on evolutionary computation, a novel real-timeroute planner for unmanned air vehicles is presented. In the evolutionary route planner, the individual candidates are evaluated with respect to the workspace so that the computation of the configuration space is not required. The planner incorporates domain-specific knowledge, can handle unforeseeable changes of the environment, and take into account different kinds of mission constraints such as minimum route leg length and flying altitude, maximum turning angle, and fixed approach vector to goal position. Furthermore, the novel planner can be used to plan routes both for a singled vehicle and for multiple ones. With Digital Terrain Elevation Data, the resultant routes can increase the surviving probability of the vehicles using the terrain masking effect.