Title:
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H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
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Author:
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Vallicrosa Massaguer, Guillem; Ridao Rodríguez, Pere
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Other authors:
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Ministerio de Economía y Competitividad (Espanya) |
Abstract:
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Occupancy Grid maps provide a probabilistic representation of space which is important for a variety of robotic applications like path planning and autonomous manipulation. In this paper, a SLAM (Simultaneous Localization and Mapping) framework capable of obtaining this representation online is presented. The H-SLAM (Hilbert Maps SLAM) is based on Hilbert Map representation and uses a Particle Filter to represent the robot state. Hilbert Maps offer a continuous probabilistic representation with a small memory footprint. We present a series of experimental results carried both in simulation and with real AUVs (Autonomous Underwater Vehicles). These results demonstrate that our approach is able to represent the environment more consistently while capable of running online |
Abstract:
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Research funded by Ministerio de Educación, Cultura y Deporte (PhD grant ref. FPU12/05384 and ARCHROV project ref. DPI2014-57746-C3-3-R), and by the European Comission (EUMR project ref. H2020- INFRAIA-2017-1-twostage-731103) |
Subject(s):
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-Vehicles submergibles -Submersibles -Vehicles autònoms -Autonomous vehicles -Robots mòbils -Mobile robots -Fons marins -- Mapes -Ocean bottom -- Maps -Algorismes computacionals -Computer algorithms |
Rights:
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Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/ |
Document type:
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Article Article - Published version peer-reviewed |
Published by:
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MDPI (Multidisciplinary Digital Publishing Institute)
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