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This paper presents a comparison of fuel-optimal and shortest paths of an unmanned combat aerial vehicle (UCAV) with obstacle avoidance. A nonlinear constrained optimization algorithm is applied to obtain the optimal paths. An initial value problem (IVP) and an inverse-dynamics approach are used separately to determine optimal paths for various scenarios and in order to reduce computation time. While inputs of the optimization algorithm are discrete control variables in the IVP method, discrete state variables are used as inputs in the inverse-dynamics method. The minimized path segments of the geometrical model provide an initial estimation of the heading angle for the aircraft flight mechanics model. The number of variables used by the optimization algorithm has a direct effect upon the optimal accuracy; however, the computation time is inversely proportional to the number of the variables. Simulation results demonstrate that the proposed IVP method effectively converges to optimal solutions.

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