Dynamic multiresolution route optimization for autonomous aircraft

We describe an approach for dynamic route optimization for autonomous high-performance aircraft. A multiresolution representation scheme is presented that uses B-spline basis functions of different support and at different locations along the trajectory, parametrized by a dimensionless parameter. A multirate receding horizon problem is formulated as an example of online multiresolution optimization under feedback. The underlying optimization problem is solved with an anytime evolutionary computing algorithm. By selecting particular basis function coefficients as the optimization variables, computing resources can flexibly be devoted to those regions of the trajectory requiring most attention. A simulation scenario is presented