Real-time route planning for unmanned air vehicle with an evolutionary algorithm

Based on evolutionary computation, a new 3D route planner for unmanned air vehicles is presented. In our evolutionary route planner, the individual candidates are evaluated with respect to the workspace. Therefore a computation of the configuration space is avoided. With Digital Terrain Elevation Data, our approach can find a near-optimal route that can increase the surviving probability efficiently. By using a problem-specific representation of candidate solutions and genetic operators, the routes are generated in real-time and are able to 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, etc.