skip to main content
10.1145/3610419.3610501acmotherconferencesArticle/Chapter ViewAbstractPublication PagesairConference Proceedingsconference-collections
research-article

Autonomous Mobile Robot Base: Cost effective solution for research and education applications

Published: 02 November 2023 Publication History

Abstract

This paper demonstrates the development, implementation, and applications of Autonomous mobile robots (AMRs). AMRs are becoming increasingly popular as they offer precise and efficient movement of payloads and can perform various tasks, potentially reducing the need for humans to engage in repetitive and arduous work. The AMR is designed with the view that it can potentially be used for educational, research, and development purposes. While there are many mobile robots available on the market, they are often expensive and come with proprietary hardware and software, which impacts the flexibility needed for research and development. To address these issues, we propose an affordable design for AMRs that utilizes ROS and advanced sensors, including LiDAR, Tracking Camera, Depth Camera, and IMU, for simultaneous localization and mapping (SLAM) and autonomous navigation. The proposed design can assist researchers by offering a low-cost solution for developing and testing mobile robots with advanced capabilities. The actuator selection and design of robot electronics are also demonstrated. Finally, several applications are shown by incorporating different hardware based on the problem statement.

References

[1]
[n. d.]. Arduino - home. https://www.arduino.cc/en/Guide
[2]
2018. rosserial - ROS Wiki. http://wiki.ros.org/rosserial
[3]
Fitria Romadhona Quratul Aini, Agung Nugroho Jati, and Unang Sunarya. 2017. A study of Monte Carlo localization on robot operating system. In 2016 International Conference on Information Technology Systems and Innovation (ICITSI). IEEE, 1–6. https://doi.org/10.1109/icitsi.2016.7858235
[4]
Mary B Alatise and Gerhard P Hancke. 2020. A review on challenges of autonomous mobile robot and sensor fusion methods. IEEE Access 8 (2020), 39830–39846.
[5]
João Fabro, Rodrigo Guimarães, André Oliveira, Thiago Becker, and Vinícius Brenner. 2016. ROS Navigation: concepts and tutorial. Vol. 625. 121–160. https://doi.org/10.1007/978-3-319-26054-9_6
[6]
Nima Fatehi, Mohammad Teshnehlab, and Sadaf Shariati. 2007. Intelligent real time control of mobile robot based on image processing. In 2007 IEEE Intelligent Vehicles Symposium. IEEE, 410–415.
[7]
Robokits India. 2018. RoboKits India - Rhino 200RPM 15Kgcm 12V DC Planetary Geared Quad Encoder Servo Motor. https://robokits.co.in/motors/rhino-ig32-12v-20w-dc-motors/dc-servo-encoder-12v-motor/rhino-200rpm-15kgcm-12v-dc-planetary-geared-quad-encoder-servo-motor
[8]
Alif Ridzuan Khairuddin, Mohamad Shukor Talib, and Habibollah Haron. 2015. Review on simultaneous localization and mapping (SLAM). 2015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE) (2015), 85–90. https://api.semanticscholar.org/CorpusID:8561576
[9]
Pablo Marin-Plaza, Ahmed Hussein, David Martin, and Arturo de la Escalera. 2018. Global and local path planning study in a ROS-based research platform for autonomous vehicles. Journal of Advanced Transportation 2018 (2018), 1–10.
[10]
Fauzi Othman, MA Bahrin, N Azli, 2016. Industry 4.0: A review on industrial automation and robotic. J Teknol 78, 6-13 (2016), 137–143.
[11]
Intel RealSense. 2022. Tracking camera T265; Intel RealSense Depth and Tracking Cameras. https://www.intelrealsense.com/tracking-camera-t265/
[12]
Nils Rottmann, Nico Studt, Floris Ernst, and Elmar Rueckert. 2020. Ros-mobile: An android application for the robot operating system. arXiv preprint arXiv:2011.02781 (2020).
[13]
Hartmut Surmann, Andreas Nüchter, and Joachim Hertzberg. 2003. An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments. Robotics and Autonomous Systems 45, 3-4 (2003), 181–198. https://doi.org/10.1016/j.robot.2003.09.004
[14]
Li Zhi and Mei Xuesong. 2018. Navigation and control system of mobile robot based on ROS. In 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE, 368–372.

Cited By

View all
  • (2024)An assessment of a ROS class using an educational mobile robot2024 9th International Engineering, Sciences and Technology Conference (IESTEC)10.1109/IESTEC62784.2024.10820208(325-329)Online publication date: 23-Oct-2024

Index Terms

  1. Autonomous Mobile Robot Base: Cost effective solution for research and education applications

        Recommendations

        Comments

        Information & Contributors

        Information

        Published In

        cover image ACM Other conferences
        AIR '23: Proceedings of the 2023 6th International Conference on Advances in Robotics
        July 2023
        583 pages
        ISBN:9781450399807
        DOI:10.1145/3610419
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 02 November 2023

        Permissions

        Request permissions for this article.

        Check for updates

        Author Tags

        1. Autonomous Mobile Robot
        2. Embedded Systems.
        3. Hardware Designing
        4. LiDAR
        5. ROS
        6. SLAM

        Qualifiers

        • Research-article
        • Research
        • Refereed limited

        Conference

        AIR 2023

        Acceptance Rates

        Overall Acceptance Rate 69 of 140 submissions, 49%

        Contributors

        Other Metrics

        Bibliometrics & Citations

        Bibliometrics

        Article Metrics

        • Downloads (Last 12 months)25
        • Downloads (Last 6 weeks)4
        Reflects downloads up to 15 Jan 2025

        Other Metrics

        Citations

        Cited By

        View all
        • (2024)An assessment of a ROS class using an educational mobile robot2024 9th International Engineering, Sciences and Technology Conference (IESTEC)10.1109/IESTEC62784.2024.10820208(325-329)Online publication date: 23-Oct-2024

        View Options

        Login options

        View options

        PDF

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        HTML Format

        View this article in HTML Format.

        HTML Format

        Media

        Figures

        Other

        Tables

        Share

        Share

        Share this Publication link

        Share on social media