Volume 37, Issue 3 (IJIEPR- In Progress 2026)                   IJIEPR 2026, 37(3): 88-107 | Back to browse issues page

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Guimarães A, Carolina Silva A, Teixeira J P, Gomes F, Martins S. Simulation and Implementation of Autonomous Mobile Robots in Intralogistics. IJIEPR 2026; 37 (3) :88-107
URL: http://ijiepr.iust.ac.ir/article-1-2245-en.html
Simulation and Implementation of Autonomous Mobile Robots in Intralogistics
André Guimarães1 , Ana Carolina Silva2 , João Pedro Teixeira2 , Filipe Gomes2 , Samuel Martins2
1- University of Beira Interior, Portugal , andre.m.guimaraes@ubi.pt
2- School Of Engineering of Polytechnic University of Porto
Abstract:   (33 Views)
In the evolving landscape of Industry 4.0, Autonomous Mobile Robots (AMRs) are emerging as key enablers of innovation in intralogistics, particularly in material transport operations. These systems operate within innovative production environments where a central controller oversees high-level planning, while AMRs act with autonomy, interacting directly with equipment and systems to support decentralized operations. This shift challenges traditional planning and control practices by introducing new dynamics in decision-making. The present study investigates the implementation potential of AMRs for supplying assembly lines at the XYZ factory through simulation-based analysis. Rather than solely benchmarking against existing methods, the research aims to validate the efficiency and practicality of AMRs in this context. Several simulation models were built and iteratively refined using the SIMIO platform to examine different logistics configurations and scenarios. The insights derived from these simulations offer valuable support for decision-makers, helping to identify optimal setups and assess how AMR deployment compares to conventional intralogistics approaches regarding performance and flexibility.
Keywords: Logistics Operations, Industrial Digitalization, Intelligent Automation, Logistics Simulation, AMR Technology, AGV Technology.
Full-Text [PDF 2364 kb]   (23 Downloads)    
Type of Study: Research | Subject: Optimization Techniques
Received: 2024/12/30 | Accepted: 2026/07/11 | Published: 2026/09/8
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