RBPF-MSIS: Toward Rao-Blackwellized Particle Filter SLAM for Autonomous Underwater Vehicle With Slow Mechanical Scanning Imaging Sonar
نویسندگان
چکیده
منابع مشابه
Multi-robot visual SLAM using a Rao-Blackwellized particle filter
This paper describes an approach to solve the Simultaneous Localization and Mapping (SLAM) problem with a team of cooperative autonomous vehicles. We consider that each robot is equipped with a stereo camera and is able to observe visual landmarks in the environment. The SLAM approach presented here is feature-based, thus the map is represented by a set of three dimensional landmarks each one d...
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Rao-Blackwellized particle filters have become a popular tool to solve the simultaneous localization and mapping problem. This technique applies a particle filter in which each particle carries an individual map of the environment. Accordingly, a key issue is to reduce the number of particles and/or to make use of compact map representations. This paper presents an approximative but highly effi...
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Simultaneous Localization And Mapping (SLAM) has been an important field of research in the robotics community in recent years. A successful class of SLAM algorithms are Rao-Blackwellized Particle Filters (RBPF), where the particles approximate the pose belief distribution, while each particle contains a separate map. So far, RBPF with landmark based environment representations as well as gridm...
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ژورنال
عنوان ژورنال: IEEE Systems Journal
سال: 2020
ISSN: 1932-8184,1937-9234,2373-7816
DOI: 10.1109/jsyst.2019.2938599