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Reliable robot localization: a constraint programming approach over dynamical systems

Abstract : The localization of underwater robots remains a challenging issue. Usual sensors, such as Global Navigation Satellite System (GNSS) receivers, cannot be used under the surface and other inertial systems suffer from a strong integration drift. On top of that, the seabed is generally uniform and unstructured, making it difficult to apply usual Simultaneous Localization and Mapping (SLAM) methods to perform a localization. Hence, innovative approaches have to be explored. The presented method can be characterized as a raw-data SLAM approach, but we propose a temporal resolution — which differs from usual methods — by considering time as a standard variable to be estimated. This concept raises new opportunities for state estimation, under-exploited so far. However, such temporal resolution is not straightforward and requires a set of theoretical tools in order to achieve the main purpose of localization. This thesis is thus not only a contribution in the field of mobile robotics, it also offers new perspectives in the areas of constraint programming and set-membership approaches. We provide a reliable contractor programming framework in order to build solvers for dynamical systems. This set of tools is illustrated along this work with realistic robotics applications.
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Contributor : Simon Rohou Connect in order to contact the contributor
Submitted on : Tuesday, November 17, 2020 - 3:32:41 PM
Last modification on : Monday, March 14, 2022 - 11:08:09 AM
Long-term archiving on: : Thursday, February 18, 2021 - 7:48:16 PM


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  • HAL Id : tel-03010085, version 1


Simon Rohou. Reliable robot localization: a constraint programming approach over dynamical systems. Robotics [cs.RO]. Lab-STICC; UBO Brest; ENSTA Bretagne; University of Sheffield, 2017. English. ⟨NNT : ⟩. ⟨tel-03010085⟩



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