A two-layer optimization framework for UAV path planning with interval uncertainties

We propose a two-layer optimization framework for the unmanned aerial vehicle path planning problem to handle interval uncertainties that exist in the combat field. When evaluating a candidate flight path, we first calculate the interval response (i.e., the upper and lower bounds) of the candidate flight path within the inner layer of the framework using a collocation interval analysis method (CIAM). Then, in the outer layer, we introduce a novel criterion for interval response comparison. The artificial bee colony algorithm is used to search for the optimal flight path according to this new criterion. Our experimental results show that the CIAM adopted is a feasible option, which largely eases the computational burden. Moreover, our derived flight paths can effectively handle bounded uncertainties without knowing the corresponding uncertainty distributions