About: An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping

Not logged in : Login

(Sponging disallowed)

Facets (new session)
Description
Metadata
Settings
- Rule:
- Inverse Functional Properties:
- "Same As":

About: An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping Goto Sponge NotDistinct Permalink

An Entity of Type : bibo:AcademicArticle, within Data Space : demo.openlinksw.com associated with source document(s)

Attributes	Values
type	http://eprints.org/ontology/ConferenceItemEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #90193 An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping
Title	An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping
described by	https://demo.openlinksw.com/about/id/entity/https/www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3 https://demo.openlinksw.com/about/id/entity/https/raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
Date	2019-10-26
Creator	Muhammad Aurangzeb Angelov Xiaowei Gu
status	peer reviewed published
abstract	Simultaneous localization and mapping (SLAM) in unknown GPS-denied environments is a very challenging problem due to the complex environment factors and the lack of prior knowledge of such environments. The performance of standard SLAM methods is dependent on odometer measurements, which, however, are unlikely to be reliable in a challenging operating environment. In this paper, a novel odometer-free approach is introduced for unmanned ground-based vehicle (UGV) to perform SLAM using only LIDAR/SONAR scans in the form of discrete point clouds. The proposed odometer-free SLAM (OF-SLAM) approach can precisely align successive sensor scans without involving other auxiliary information, e.g., odometer readings. By converting the accurately aligned point clouds into continuous local grid maps using kernel tricks, OF-SLAM creates a dynamically updating global map of the surrounding environment and further accurately localizes the UGV on the map. Simulation experiments verify the validity and effectiveness of OF-SLAM and demonstrate the proposed approach as an attractive alternative for UGV to perform SLAM and explore complex unknown environments.
Is Part Of	https://kar.kent.ac.uk/id/repository
Subject	QA 75 Electronic computers. Computer science
list of authors	https://kar.kent.ac.uk/id/eprint/90193#authors
presented at	IEEE Nuclear Science Symposium and Medical Imaging Conference 2019
is topic of	https://www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3 https://raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #90193 An Odometer-Free Approach for Unmanned Ground-Based Vehicle Simultaneous Localization and Mapping

Faceted Search & Find service v1.17_git144 as of Jul 26 2024

Alternative Linked Data Documents: iSPARQL | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 08.03.3331 as of Aug 25 2024, on Linux (x86_64-ubuntu_noble-linux-glibc2.38-64), Single-Server Edition (378 GB total memory, 54 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software