Mobile robot rbpf-slam with lms sensor in indoor environments application on robuTER robot

Abdelfetah Hentout; Abdelkader Beghni; Abdelkader Benahmed Nourine; Abderraouf Maoudj; Brahim Bouzouia

doi:10.1109/ICEE-B.2017.8192121

Mobile robot rbpf-slam with lms sensor in indoor environments application on robuTER robot

Abdelfetah Hentout
, Abdelkader Beghni
, Abdelkader Benahmed Nourine
, Abderraouf Maoudj
, Brahim Bouzouia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Recently, Simultaneous Localization And Mapping (SLAM) problem becomes an active research field in mobile robotics. In addition, Rao-Blackwellized Particle Filter (RBPF) has been introduced as an effective means to solve this problem. This paper describes the implementation of a RBPF-SLAM to estimate the mobile robot pose while building the map of its surrounding indoor environment. In this approach, each particle in RBPF represents an individual map of the environment and a possible trajectory of the robot. This method is implemented and tested on the RobuTER mobile robot while exploiting the data delivered by the LMS sensor equipping it. The experimental results show the effectiveness of the proposed RBPF-SLAM in terms of (i) accuracy of the generated maps and (ii) the calculation of the actual robot pose.

Original language	English
Title of host publication	2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781538606865
DOIs	https://doi.org/10.1109/ICEE-B.2017.8192121
State	Published - 12 Dec 2017
Externally published	Yes

Publication series

Name	2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017
Volume	2017-January

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

Mobile Robot
Rao-Blackwellized Particle Filter
RobuTER
Simultaneous Localization And Mapping

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Science Applications
Electrical and Electronic Engineering
Instrumentation
Control and Optimization

Access to Document

10.1109/ICEE-B.2017.8192121

Cite this

Hentout, A., Beghni, A., Benahmed Nourine, A., Maoudj, A., & Bouzouia, B. (2017). Mobile robot rbpf-slam with lms sensor in indoor environments application on robuTER robot. In 2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017 (pp. 1-6). (2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICEE-B.2017.8192121

Hentout, Abdelfetah ; Beghni, Abdelkader ; Benahmed Nourine, Abdelkader et al. / Mobile robot rbpf-slam with lms sensor in indoor environments application on robuTER robot. 2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-6 (2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017).

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title = "Mobile robot rbpf-slam with lms sensor in indoor environments application on robuTER robot",

abstract = "Recently, Simultaneous Localization And Mapping (SLAM) problem becomes an active research field in mobile robotics. In addition, Rao-Blackwellized Particle Filter (RBPF) has been introduced as an effective means to solve this problem. This paper describes the implementation of a RBPF-SLAM to estimate the mobile robot pose while building the map of its surrounding indoor environment. In this approach, each particle in RBPF represents an individual map of the environment and a possible trajectory of the robot. This method is implemented and tested on the RobuTER mobile robot while exploiting the data delivered by the LMS sensor equipping it. The experimental results show the effectiveness of the proposed RBPF-SLAM in terms of (i) accuracy of the generated maps and (ii) the calculation of the actual robot pose.",

keywords = "Mobile Robot, Rao-Blackwellized Particle Filter, RobuTER, Simultaneous Localization And Mapping",

author = "Abdelfetah Hentout and Abdelkader Beghni and \{Benahmed Nourine\}, Abdelkader and Abderraouf Maoudj and Brahim Bouzouia",

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year = "2017",

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doi = "10.1109/ICEE-B.2017.8192121",

language = "English",

series = "2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017",

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Hentout, A, Beghni, A, Benahmed Nourine, A, Maoudj, A & Bouzouia, B 2017, Mobile robot rbpf-slam with lms sensor in indoor environments application on robuTER robot. in 2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017. 2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-6. https://doi.org/10.1109/ICEE-B.2017.8192121

Mobile robot rbpf-slam with lms sensor in indoor environments application on robuTER robot. / Hentout, Abdelfetah; Beghni, Abdelkader; Benahmed Nourine, Abdelkader et al.
2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-6 (2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hentout, Abdelfetah

AU - Beghni, Abdelkader

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AU - Maoudj, Abderraouf

AU - Bouzouia, Brahim

PY - 2017/12/12

Y1 - 2017/12/12

N2 - Recently, Simultaneous Localization And Mapping (SLAM) problem becomes an active research field in mobile robotics. In addition, Rao-Blackwellized Particle Filter (RBPF) has been introduced as an effective means to solve this problem. This paper describes the implementation of a RBPF-SLAM to estimate the mobile robot pose while building the map of its surrounding indoor environment. In this approach, each particle in RBPF represents an individual map of the environment and a possible trajectory of the robot. This method is implemented and tested on the RobuTER mobile robot while exploiting the data delivered by the LMS sensor equipping it. The experimental results show the effectiveness of the proposed RBPF-SLAM in terms of (i) accuracy of the generated maps and (ii) the calculation of the actual robot pose.

AB - Recently, Simultaneous Localization And Mapping (SLAM) problem becomes an active research field in mobile robotics. In addition, Rao-Blackwellized Particle Filter (RBPF) has been introduced as an effective means to solve this problem. This paper describes the implementation of a RBPF-SLAM to estimate the mobile robot pose while building the map of its surrounding indoor environment. In this approach, each particle in RBPF represents an individual map of the environment and a possible trajectory of the robot. This method is implemented and tested on the RobuTER mobile robot while exploiting the data delivered by the LMS sensor equipping it. The experimental results show the effectiveness of the proposed RBPF-SLAM in terms of (i) accuracy of the generated maps and (ii) the calculation of the actual robot pose.

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Hentout A, Beghni A, Benahmed Nourine A, Maoudj A, Bouzouia B. Mobile robot rbpf-slam with lms sensor in indoor environments application on robuTER robot. In 2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-6. (2017 5th International Conference on Electrical Engineering - Boumerdes, ICEE-B 2017). doi: 10.1109/ICEE-B.2017.8192121

Mobile robot rbpf-slam with lms sensor in indoor environments application on robuTER robot

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this