Design, Implementation, and Performance Optimization of a ROS Based Autonomous Mobile Robot for Intralogistics in Manufacturing Facilities

Neslihan Demir; Pinar Demircioglu; Ismail Bogrekci

doi:10.14313/jamris-2026-010

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Design, Implementation, and Performance Optimization of a ROS Based Autonomous Mobile Robot for Intralogistics in Manufacturing Facilities

Journal of Automation, Mobile Robotics and Intelligent Systems

Volume 20 (2026): Issue 1 (March 2026)

By: Neslihan Demir, Pinar Demircioglu and Ismail Bogrekci

Open Access

|Mar 2026

Abstract

This study deals with the development and optimization of an ROS-based Autonomous Mobile Robot (AMR) for intralogistics in production environments. With a robust mechanical design, high-level sensor fusion, and Hybrid A* path planning, this AMR offers considerable flexibility, safety, and efficiency gains over traditional automated guided vehicles (AGVs). The proposed AMR system allows for dynamic, autonomous locomotion in intricate industrial settings, with adaptive obstacle response and variable payloads. Verification in both virtual and real-life settings demonstrate the system’s effectiveness in navigation precision, energy efficiency, and load-carrying capacity, highlighting its potential to improve logistics operations and reduce operational costs in the Industry 4.0 context.

References

J. Smit et al., “Industry 4.0: Policy Department A - Economic and Scientific Policy,” European Parliament, Directorate-General for Internal Policies, February 2016.
Search in Google Scholar Back to article
M.B. Alatise and G.P. Hancke, “A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods,” IEEE Access, vol. 8, 2020, pp. 39830–39846. doi: 10.1109/ACCESS.2020.2975643.
Open DOI Search in Google Scholar Back to article
G. Fragapane et al., “Planning and Control of Autonomous Mobile Robots for Intralogistics: Literature Review and Research Agenda,” European Journal of Operational Research, vol. 294, no. 2, 2021, pp. 405–426. doi: 10.1016/j.ejor.2021.01.019.
Open DOI Search in Google Scholar Back to article
K. Katona, H.A. Neamah, and P. Korondi, “Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot,” Sensors, vol. 24, no. 11, 2024, 3573. doi: 10.3390/s24113573.
Open DOI Search in Google Scholar Back to article
J. Morgenstern and H. Zadek, “AMR: Influencing Factors and Potentials of Cloud-Robotics,” Proc. 16th International Doctoral Students Workshops on Logistics, Supply Chain and Production Management, 2023, pp. 81–88.
Search in Google Scholar Back to article
J.R. Sanchez-Ibanez, C.J. Perez-del-Pulgar, and A. Garcla-Cerezo, “Path Planning for Autonomous Mobile Robots: A Review,” Sensors, vol. 21, no. 23, 2021, 7898. doi: 10.3390/s21237898.
Open DOI Search in Google Scholar Back to article
S. Santoro, “Design and Implementation of a Sensory System for an Autonomous Mobile Robot in a Connected Industrial Environment,” master’s thesis, Dept. Mechatronic Engineering, Politecnico di Torino, 2021.
Search in Google Scholar Back to article
GeekPlus Technologies, “Autonomous Mobile Robot Solutions,” Available: https://www.geekplus.com/en/(accessed Sep. 2024).
Search in Google Scholar Back to article
Clearpath Robotics, “Autonomous Mobile Robots and Robotics Platforms,” Available: https://clearpathrobotics.com/(accessed Sep. 2024).
Search in Google Scholar Back to article
ROBOTS (IEEE Spectrum), “Proteus – Autonomous Mobile Robot,” 2022. Available: https://robotsguide.com/robots/proteus (accessed Sep. 2024).
Search in Google Scholar Back to article
M. Quigley et al., “ROS: An Open-Source Robot Operating System,” Proc. IEEE International Conference on Robotics and Engineering, 2009.
Search in Google Scholar Back to article
A. Alessandro, “Robotic Arm Pick-and-Place Tasks: Implementation and Comparison of Approaches with and without Machine Learning Techniques,” master’s thesis, Dept. Mechatronic Engineering, Politecnico di Torino, 2020.
Search in Google Scholar Back to article
D. Taranta et al., “An Autonomous Mobile Robot Navigation Architecture for Dynamic Intralogistics,” Proc. 2021 IEEE 19th International Conference on Industrial Informatics (INDIN), 2021, pp. 1–6.
Search in Google Scholar Back to article
B. Hichri et al., “Lifting Mechanism for Payload Transport by Collaborative Mobile Robots,” New Trends in Mechanism and Machine Science, vol. 24, P. Flores, F. Viadero, eds., Springer, Cham, 2015, pp. 157–165.
Search in Google Scholar Back to article
D. Heath, “Design of a Competition Capable Hobby Rocket,” Oxford Brookes University, 2018.
Search in Google Scholar Back to article
D.P. Sichkar et al., “Moving Elements of Mobile Robots Stabilization Modelling,” Proc. 2019 Systems of Signals Generating and Processing in the Field of on Board Communications, 2019, pp. 1–5.
Search in Google Scholar Back to article
C. Wang et al., “Autonomous Mobile Robot Navigation in Uneven and Unstructured Indoor Environments,” Proc. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017, pp. 109–116.
Search in Google Scholar Back to article
A.K. Grover and M. H. Ashraf, “Leveraging Autonomous Mobile Robots for Industry 4.0 Warehouses: A Multiple Case Study Analysis,” International Journal Logistics Management, vol. 35, no. 4, 2024, pp. 1168–1199. doi: 10.1108/IJLM-09-2022-0362.
Open DOI Search in Google Scholar Back to article
R. Bostelman et al., “3D Range Imaging for Urban Search and Rescue Robotics Research,” Proc. IEEE International Safety, Security and Rescue Robotics Workshop, 2005, pp. 145–150.
Search in Google Scholar Back to article
A. Vemula, K. Muelling, and J. Oh, “Path Planning in Dynamic Environments with Adaptive Dimensionality,” arXiv preprint, 22 May 2016.
Search in Google Scholar Back to article
M. Zeng, “PI(t)D(t) Control and Motion Profiling for Omnidirectional Mobile Robots,” arXiv preprint, 19 Oct. 2021.
Search in Google Scholar Back to article
P. Hart, N. Nilsson, and B. Raphael, “A Formal Basis for the Heuristic Determination of Minimum Cost Paths,” IEEE Transactions on Systems Science and Cybernetics, vol. 4, no. 2, pp. 100–107, 1968. doi: 10.1109/TSSC.1968.300136.
Open DOI Search in Google Scholar Back to article
J. Petereit et al., “Application of Hybrid A* to an Autonomous Mobile Robot for Path Planning in Unstructured Outdoor Environments,” Proc. 7^th German Conference on Robotics (ROBOTIK 2012), 2012.
Search in Google Scholar Back to article

Articles in this issue

DOI: https://doi.org/10.14313/jamris-2026-010 | Journal eISSN: 2080-2145 | Journal ISSN: 1897-8649

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Language: English

Page range: 93 - 102

Submitted on: Nov 6, 2024

Accepted on: Feb 24, 2025

Published on: Mar 31, 2026

Published by: Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

Autonomous Mobile Robots (AMR),

Robot Operating System (ROS),

Intralogistics,

Hybrid A* Algorithm

Related subjects:

Computer sciences,

Artificial intelligence,

Engineering,

Electrical engineering,

Control engineering, metrology and testing,

Mechanical engineering,

Fundamentals of mechanical engineering

© 2026 Neslihan Demir, Pinar Demircioglu, Ismail Bogrekci, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 20 (2026): Issue 1 (March 2026)