Three-dimensional path planning for unmanned aerial vehicles based on fluid flow

Using the principles of fluid mechanics for flow around objects, a three dimensional (3D) path planning method for unmanned aerial vehicles (UAVs) in complex environments is studied. As a potential field method, it theoretically guarantees to avoid local minima with smooth paths and the modeling of environment is simple. First, an analytical solution is derived to determine the steady 3D fluid flow acting on a single spherical obstacle. Subsequently, an interpolation function is introduced to multiple obstacles avoidance. Finally, the maneuverability constraints of the UAV are imposed and flight paths are obtained. Added the effect of human factors, a Generalized Fuzzy Competitive Neural Network (G-FCNN) is proposed to evaluate the flight paths. In simulation, the path is smoother and more reasonable. In terms of evaluation, G-FCNN could considerate multiple factors and the result is satisfied.

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