Model based localization and estimation of an ellipsoidal object using artificial electric sense

Abstract : The aim of this thesis is to contribute to the underwater perception for robotics applications using an electric field. We propose new methods for the inspection, the localization and the shape estimation of an ellipsoidal object using a sensor inspired by the weakly electric fish. Firstly, we show that the object can be detected and its material and position relative to the sensor axis discriminated, using simple threshold detections on the measured currents. Then, we propose the successive implementations of three reactive control laws allowing the sensor to head for the object and revolve around it by following its boundaries. After that, we use the MUSIC algorithm in order to localize the object’s center. Finally, the geometrical parameters of the object and its orientation are estimated thanks to an optimization algorithm based on the least squares method and the inversion of the analytical model of the polarization tensor of an ellipsoidal object. We show that these algorithms can be experimentally implemented. For the localization and the shape estimation algorithms, some additional techniques involving sensor movements are proposed in order to significantly reduce the imprecisions due to the gap between the model and the actual currents’ measurements.
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Sylvain Lanneau. Model based localization and estimation of an ellipsoidal object using artificial electric sense. Robotics [cs.RO]. Ecole nationale supérieure Mines-Télécom Atlantique, 2017. English. ⟨NNT : 2017IMTA0030⟩. ⟨tel-01713048⟩

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