Developing an effective algorithm for dynamic UAV path planning with incomplete threat information

Abstract

In this paper the problem of online dynamic UAV path planning is studied for the situation where a manoeuvring pop-up threat exists and information about this threat is incomplete. The problem is addressed by integrating a structure-varying discrete dynamic Bayesian network (SVDDBN) into the model prediction control (MPC) algorithm. The SVDDBN is used to construct online a dynamic threat assessment model by estimating and predicting the states of the manoeuvring pop-up threat. The output of this model is then fed into the MPC algorithm for effective path planning. The results obtained in the performed simulation studies demonstrate the excellent performance of the proposed algorithm.