A simple, cost-effective and practical implementation of SLAM using ROS and Arduino

Adrián Lendínez Ibáñez; Renxi Qiu; Dayou Li

doi:10.1109/iThings-GreenCom-CPSCom-SmartData.2017.128

A simple, cost-effective and practical implementation of SLAM using ROS and Arduino

Adrián Lendínez Ibáñez
, Renxi Qiu
, Dayou Li

Institute for Research in Applicable Computing (IRAC)

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

4 Citations (Scopus)

Abstract

This paper aims to introduce the reader to the Simultaneous Localization and Mapping (SLAM) problem in the context of robot mapping by providing a real, simple and powerful implementation using the Robot Operating System (ROS) framework and Arduino technology. In addition to this, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) used, is included. The creation of an inexpensive differential drive robot for this purpose is detailed along with the experiments conducted with the platform to map domestic environments. This work is targeted to students willing to get familiar with the presented subject by giving them the means to construct and code their own robot for 2D mapping.

Original language	English
Title of host publication	nan
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	835-840
ISBN (Print)	9781538630655
DOIs	https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2017.128
Publication status	Published - 1 Feb 2018
Event	2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) - Exeter Duration: 21 Jun 2017 → 23 Jun 2017

Conference

Conference	2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
City	Exeter
Period	21/06/17 → 23/06/17
Other	2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) (21/06/2017-23/06/2017, Exeter)

Keywords

SLAM
Particle filter
Kalman filter
ROS
Arduino

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10.1109/iThings-GreenCom-CPSCom-SmartData.2017.128

https://ieeexplore.ieee.org/document/8276847

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@inproceedings{de9420a68ffa42919ed13f62de3276c4,

title = "A simple, cost-effective and practical implementation of SLAM using ROS and Arduino",

abstract = "This paper aims to introduce the reader to the Simultaneous Localization and Mapping (SLAM) problem in the context of robot mapping by providing a real, simple and powerful implementation using the Robot Operating System (ROS) framework and Arduino technology. In addition to this, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) used, is included. The creation of an inexpensive differential drive robot for this purpose is detailed along with the experiments conducted with the platform to map domestic environments. This work is targeted to students willing to get familiar with the presented subject by giving them the means to construct and code their own robot for 2D mapping.",

keywords = "SLAM, Particle filter, Kalman filter, ROS, Arduino",

author = "Ib{\'a}{\~n}ez, \{Adri{\'a}n Lend{\'i}nez\} and Renxi Qiu and Dayou Li",

year = "2018",

month = feb,

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doi = "10.1109/iThings-GreenCom-CPSCom-SmartData.2017.128",

language = "English",

isbn = "9781538630655",

pages = "835--840",

booktitle = "nan",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) ; Conference date: 21-06-2017 Through 23-06-2017",

}

Ibáñez, AL, Qiu, R & Li, D 2018, A simple, cost-effective and practical implementation of SLAM using ROS and Arduino. in nan. Institute of Electrical and Electronics Engineers Inc., pp. 835-840, 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Exeter, 21/06/17. https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2017.128

TY - GEN

T1 - A simple, cost-effective and practical implementation of SLAM using ROS and Arduino

AU - Ibáñez, Adrián Lendínez

AU - Qiu, Renxi

AU - Li, Dayou

PY - 2018/2/1

Y1 - 2018/2/1

N2 - This paper aims to introduce the reader to the Simultaneous Localization and Mapping (SLAM) problem in the context of robot mapping by providing a real, simple and powerful implementation using the Robot Operating System (ROS) framework and Arduino technology. In addition to this, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) used, is included. The creation of an inexpensive differential drive robot for this purpose is detailed along with the experiments conducted with the platform to map domestic environments. This work is targeted to students willing to get familiar with the presented subject by giving them the means to construct and code their own robot for 2D mapping.

AB - This paper aims to introduce the reader to the Simultaneous Localization and Mapping (SLAM) problem in the context of robot mapping by providing a real, simple and powerful implementation using the Robot Operating System (ROS) framework and Arduino technology. In addition to this, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) used, is included. The creation of an inexpensive differential drive robot for this purpose is detailed along with the experiments conducted with the platform to map domestic environments. This work is targeted to students willing to get familiar with the presented subject by giving them the means to construct and code their own robot for 2D mapping.

KW - SLAM

KW - Particle filter

KW - Kalman filter

KW - ROS

KW - Arduino

U2 - 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.128

DO - 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.128

M3 - Conference contribution

SN - 9781538630655

SP - 835

EP - 840

BT - nan

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)

Y2 - 21 June 2017 through 23 June 2017

ER -

A simple, cost-effective and practical implementation of SLAM using ROS and Arduino

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