Unmanned aerial vehicles (UAV) are becoming more autonomous, rapidly sophisticated and intelligent due to the large on-board computer power, control algorithms and sensor systems. In the research literature there is a plethora of work, which addresses systematically among other issues the UAV path planning process. Very little work however, addresses the complementary step for satisfying the on-board UAV energy constraints. In this paper, the path planning has been considered as a priori, and therefore results in a choice of optimum paths to be utilised. These optimum paths correspond to the minimum travelling ranges. In practice, aerodynamic effects such as wind disturbances on the UAV, can alter the corresponding energies of these paths. Hence in this paper the Euclidean paths are mapped to energy costs. The proposed problem setting, is solved together with the 4-zone strategy using Dijkstra's Algorithm. The effectiveness for the proposed methodology is shown by a multi-scenario approach.
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