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Aircraft optimal trajectory planning in the presence of wind is a critical issue for airlines to save fuel. Planning is difficult due to the uncertainties linked to wind. Based on wind predictions, airlines have to compute trajectory planning for their aircraft in an efficient way. Such planning has to propose robust solutions which take into account wind variability. In this paper, we propose a robust wind optimal trajectory design algorithm based on two phases. The first phase considers the wind map predictions and computes for each of them the associated wind optimal trajectory also called geodesic. Such geodesics are computed with a Bellman algorithm on a grid covering an elliptical shape projected on the sphere. The second phase of the algorithm extract the most robust geodesic trajectories by the mean of a new trajectory clustering algorithm. This clustering algorithm is based on a new mathematical distance involving continuous deformation approach applied to north Atlantic flights 1 .

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