Online UAV path planning in uncertain and hostile environments
2017
Taking uncertainties of threats and vehicles’ motions and observations into account, the challenge we have to face is how to plan a safe path online in uncertain and dynamic environments. We construct the static threat (ST) model based on an intuitionistic fuzzy set (A-IFS) to deal with the uncertainty of a environmental threat. The problem of avoiding a dynamic threat (DT) is formulated as a pursuit-evasion game. A reachability set (RS) estimator of an uncertain DT is constructed by combining the motion prediction with a RRT-based method. An online path planning framework is proposed by integrating a sub goal selector, a sub tasks allocator and a local path planner. The selector and allocator are presented to accelerate the path searching process. Dynamic domain rapidly-exploring random tree (DDRRT) is combined with the linear quadratic Gaussian motion planning (LQG-MP) method when searching local paths under threats and uncertainties. The path that has been searched is further improved by using a safety adjustment method and the RRT* method in the planning system. The results of Mont Carlo simulations indicate that the proposed algorithm behaves well in planning safe paths online in uncertain and hostile environments.
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