An implementation of SLAM using ROS and Arduino

Adrián Lendínez Ibáñez; Renxi Qiu; Dayou Li

doi:10.1109/3M-NANO.2017.8286298

An 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

Abstract

This paper aims to explore the Simultaneous Localization and Mapping (SLAM) problem in the context of implementation using the Robot Operating System (ROS) framework and the Arduino technology. The implementation of an inexpensive differential drive robot for SLAM is detailed and verified by mapping experiments conducted within domestic environments. Furthermore, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) behind the platform is also presented. Overall, this report leads to a simple and cost effective way - including a code base and guidelines - to create robots for 2D mapping using modern technologies such as ROS.

Original language	English
Title of host publication	nan
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-6
ISBN (Print)	9781538610817
DOIs	https://doi.org/10.1109/3M-NANO.2017.8286298
Publication status	Published - 8 Feb 2018
Event	2017 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO) - Shanghai Duration: 7 Aug 2017 → 11 Aug 2017

Conference

Conference	2017 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO)
City	Shanghai
Period	7/08/17 → 11/08/17
Other	2017 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO) (07/08/2017-11/08/2017, Shanghai)

Keywords

Particle filter
SLAM
Kalman filter
ROS
Arduino

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https://ieeexplore.ieee.org/document/8286298

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@inproceedings{63298fd1de65467aa74e5d59d8cb43dc,

title = "An implementation of SLAM using ROS and Arduino",

abstract = "This paper aims to explore the Simultaneous Localization and Mapping (SLAM) problem in the context of implementation using the Robot Operating System (ROS) framework and the Arduino technology. The implementation of an inexpensive differential drive robot for SLAM is detailed and verified by mapping experiments conducted within domestic environments. Furthermore, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) behind the platform is also presented. Overall, this report leads to a simple and cost effective way - including a code base and guidelines - to create robots for 2D mapping using modern technologies such as ROS.",

keywords = "Particle filter, SLAM, 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,

day = "8",

doi = "10.1109/3M-NANO.2017.8286298",

language = "English",

isbn = "9781538610817",

pages = "1--6",

booktitle = "nan",

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

address = "United States",

note = "2017 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO) ; Conference date: 07-08-2017 Through 11-08-2017",

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TY - GEN

T1 - An implementation of SLAM using ROS and Arduino

AU - Ibáñez, Adrián Lendínez

AU - Qiu, Renxi

AU - Li, Dayou

PY - 2018/2/8

Y1 - 2018/2/8

N2 - This paper aims to explore the Simultaneous Localization and Mapping (SLAM) problem in the context of implementation using the Robot Operating System (ROS) framework and the Arduino technology. The implementation of an inexpensive differential drive robot for SLAM is detailed and verified by mapping experiments conducted within domestic environments. Furthermore, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) behind the platform is also presented. Overall, this report leads to a simple and cost effective way - including a code base and guidelines - to create robots for 2D mapping using modern technologies such as ROS.

AB - This paper aims to explore the Simultaneous Localization and Mapping (SLAM) problem in the context of implementation using the Robot Operating System (ROS) framework and the Arduino technology. The implementation of an inexpensive differential drive robot for SLAM is detailed and verified by mapping experiments conducted within domestic environments. Furthermore, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) behind the platform is also presented. Overall, this report leads to a simple and cost effective way - including a code base and guidelines - to create robots for 2D mapping using modern technologies such as ROS.

KW - Particle filter

KW - SLAM

KW - Kalman filter

KW - ROS

KW - Arduino

U2 - 10.1109/3M-NANO.2017.8286298

DO - 10.1109/3M-NANO.2017.8286298

M3 - Conference contribution

SN - 9781538610817

SP - 1

EP - 6

BT - nan

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO)

Y2 - 7 August 2017 through 11 August 2017

ER -

An implementation of SLAM using ROS and Arduino

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