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In this paper, we describe a practically efficient methodology of improving the aerodynamic characteristics of an UAS's wing using a morphing approach. We have replaced a part of the original wings' upper and lower surfaces with a flexible, composite material skin whose shape can be modified, according to the variable airflow conditions, using internally placed actuators. The optimal displacements of the actuators, as functions of the external flow characteristics, are determined using a genetic algorithm based optimizer, coupled with a three - dimensional numerical extension of the classical lifting line model for estimating the modified wing aerodynamic coefficients. We have used the optimization tool to decrease the overall drag coefficient of a military grade UAS' wing equipped with the flexible skin. We have obtained good quality solutions for only a fraction of the computational cost needed when performing viscous flow field calculations.

The purpose of this work is to evaluate the efficiency of several calibration methods applied to a six-axis industrial (serial) robot. Specifically, the absolute position accuracy of a Fanuc LR Mate 200 iC industrial robot is improved using two calibration models. The first model is purely kinematic, and takes into account all geometric parameters. The second model considers, in addition, five compliance parameters related to the stiffness in joints 2, 3, 4, 5, and 6. For both models, the so-called calibration (or identification) robot configurations are selected based on an observability analysis. For each model, the efficiency of five different observability indices are compared. The parameter identification is based on the forward kinematic approach, where only the residual of the calibration positions is minimized.