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This paper presents an advanced pulse pattern for saliencies based self sensing control of induction motors for electric vehicle drives. This allows a direct, accurate and parameter independent detection of the rotor flux position at standstill and low speed. The innovation of the proposed method is the reduction of the stator current to zero before each sequence of test pulses. This leads to a commutation of the magnetising current into the rotor leakage inductance and consequently to a saturation of this inductance in the same direction. Finally measurement results with the proposed injection sequence are shown and compared with state of the art methods.

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Planning the right grasp pose and motion into it has been a problem in the robotic community for more than 20 years. This paper presents a model-based approach for a Pick action of a robot that increases the automation of FDM based additive manufacturing by removing a produced object from the build plate. We treat grasp pose planning, motion planning and simulation-based verification as separate components to allow a high exchangeability. When testing a variety of different object geometries, feasible grasps and motions were obtained for all objects. We also found that the computation time is highly dependent on the random seed, leading us to employ a system of budgeted runs for which we report the estimated success probability and expected running time. Within the budget, some objects never found feasible picks. Thus, we rotated these objects by 90 • which lead to a substantial improvement in success probabilities.