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Visual Servoing Using Model Predictive Control to Assist Multiple Trajectory Tracking

Nicolas Cazy 1 Pierre-Brice Wieber 2 Paolo Robuffo Giordano 1 François Chaumette 1
1 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
2 BIPOP - Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems
Inria Grenoble - Rhône-Alpes, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann
Abstract : We propose in this paper a new active perception scheme based on Model Predictive Control under constraints for generating a sequence of visual servoing tasks. The proposed control scheme is used to compute the motion of a camera whose task is to successively observe a set of robots for measuring their position and improving the accuracy of their localization. This method is based on the prediction of an uncertainty model (due to actuation and measurement noise) for determining which robot has to be observed by the camera. Simulation results are presented for validating the approach.
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Nicolas Cazy, Pierre-Brice Wieber, Paolo Robuffo Giordano, François Chaumette. Visual Servoing Using Model Predictive Control to Assist Multiple Trajectory Tracking. IEEE International Conference on Robotics and Automation (ICRA), May 2017, Singapore, Singapore. pp.2057-2064, ⟨10.1109/ICRA.2017.7989237⟩. ⟨hal-01482878⟩

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