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An implementation of SLAM with extended Kalman filter

This paper discusses an implementation of Extended Kalman filter (EKF) in performing Simultaneous Localization and Mapping (SLAM). The implementation is divided into software and hardware phases. The software implementation applies EKF using Python on a library dataset to produce a map of the suppos...

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Main Authors: Saman, A.B.S.H.M., Lotfy, A.H.
Format: Article
Published: Institute of Electrical and Electronics Engineers Inc. 2017
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011977071&doi=10.1109%2fICIAS.2016.7824105&partnerID=40&md5=212572503d8af499d137e71d98366506
http://eprints.utp.edu.my/20172/
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spelling my.utp.eprints.201722018-04-22T14:44:19Z An implementation of SLAM with extended Kalman filter Saman, A.B.S.H.M. Lotfy, A.H. This paper discusses an implementation of Extended Kalman filter (EKF) in performing Simultaneous Localization and Mapping (SLAM). The implementation is divided into software and hardware phases. The software implementation applies EKF using Python on a library dataset to produce a map of the supposed environment. The result was verified against the original map and found to be relatively accurate with minor inaccuracies. In the hardware implementation stage, real life data was gathered from an indoor environment via a laser range finder and a pair of wheel encoders placed on a mobile robot. The resulting map shows at least five marked inaccuracies but the overall form is passable. © 2016 IEEE. Institute of Electrical and Electronics Engineers Inc. 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011977071&doi=10.1109%2fICIAS.2016.7824105&partnerID=40&md5=212572503d8af499d137e71d98366506 Saman, A.B.S.H.M. and Lotfy, A.H. (2017) An implementation of SLAM with extended Kalman filter. International Conference on Intelligent and Advanced Systems, ICIAS 2016 . http://eprints.utp.edu.my/20172/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description This paper discusses an implementation of Extended Kalman filter (EKF) in performing Simultaneous Localization and Mapping (SLAM). The implementation is divided into software and hardware phases. The software implementation applies EKF using Python on a library dataset to produce a map of the supposed environment. The result was verified against the original map and found to be relatively accurate with minor inaccuracies. In the hardware implementation stage, real life data was gathered from an indoor environment via a laser range finder and a pair of wheel encoders placed on a mobile robot. The resulting map shows at least five marked inaccuracies but the overall form is passable. © 2016 IEEE.
format Article
author Saman, A.B.S.H.M.
Lotfy, A.H.
spellingShingle Saman, A.B.S.H.M.
Lotfy, A.H.
An implementation of SLAM with extended Kalman filter
author_facet Saman, A.B.S.H.M.
Lotfy, A.H.
author_sort Saman, A.B.S.H.M.
title An implementation of SLAM with extended Kalman filter
title_short An implementation of SLAM with extended Kalman filter
title_full An implementation of SLAM with extended Kalman filter
title_fullStr An implementation of SLAM with extended Kalman filter
title_full_unstemmed An implementation of SLAM with extended Kalman filter
title_sort implementation of slam with extended kalman filter
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011977071&doi=10.1109%2fICIAS.2016.7824105&partnerID=40&md5=212572503d8af499d137e71d98366506
http://eprints.utp.edu.my/20172/
_version_ 1738656173906722816
score 13.187197

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