Implementation of Robot Operating System in Raspberry Pi 4 for Autonomous Landing Quadrotor on ArUco Marker

General Information

ISSN: 2278-0149 (Online)
Abbreviated Title: Int. J. Mech. Eng. Robot. Res.
Frequency: Bimonthly
DOI: 10.18178/ijmerr
Managing Editor: Ms. Jennifer Zeng
Abstracting/Indexing: Scopus, CNKI, Google Scholar, Crossref, etc.
E-mail questions to IJMERR Editorial Office.
Acceptance Rate: 24%
APC: 450 USD
Average Days to Accept: 118 days
Journal Metrics:

1.8

2022CiteScore

36th percentile

Editor-in-Chief

Prof Richard (Chunhui) Yang

Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.

What's New

2024-04-30

Volume 13, No. 2 has been published online.

2024-02-24

Volume 13, No. 1 has been published online.

2024-01-04

IJMERR will adopt Article-by-Article Work Flow. For the Bimonthly journal, each issue will be released at the end of the issue month.

Home > Published Issues > 2023 > Volume 12, No. 4, July 2023 >

IJMERR 2023 Vol.12(4): 210-215
DOI: 10.18178/ijmerr.12.4.210-215

Atcha Daspan 1, Anukoon Nimsongprasert 1, Prathan Srichai 2, and Pijirawuch Wiengchanda 1*,

1. Marine Engineering Department, Academic Branch, Royal Thai Naval Academy, Samut Parkan, Thailand
2. Department of Mechanical Engineering, Faculty of Engineering, Princess of Naradhiwas University, Naradhiwas, Thailand
*Correspondence: pijirawuch.w@navy.mi.th (P.W.)

Manuscript received November 17, 2022; revised December 24, 2022; accepted February 7, 2023.

Abstract—This article describes the novel design and implementation of the Robot Operating System (ROS) for the autonomous quadrotor landing on ArUco marker application. On a Raspberry Pi 4 companion computer, the ROS was set up using Ubuntu Mate 18.04. Then, to create communication between program nodes, ROS was put into practice together with autonomous landing. In the control approach, the Visual Inertial Odometry (VIO) technique, which uses vision-based localization, is employed to estimate the 3D posture. For computing the command control to direct movement quadrotor to landing on ArUco marker, the autolanding application is built. In experimental, 25 landing experiment trials were completed. The distance between the Drone’s camera’s center and the ArUco marker's center was calculated. In the results, the average distance accuracy during experimental validation was 11.12 cm, with a standard deviation of 3.67 cm.

Keywords—quadrotor, raspberry pi, autonomous landing, robot operating system, ArUco marker

Cite: Atcha Daspan, Anukoon Nimsongprasert, Prathan Srichai, and Pijirawuch Wiengchand, "Implementation of Robot Operating System in Raspberry Pi 4 for Autonomous Landing Quadrotor on ArUco Marker," International Journal of Mechanical Engineering and Robotics Research, Vol. 12, No. 4, pp. 210-215, July 2023.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.