Combining automated guided vehicles and autonomous mobile robots for flexible intralogistics

Abstract Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) represent two dominant paradigms among industrial mobile transport robots. While AGVs provide high reliability through infrastructure-based navigation and deterministic routing, AMRs offer greater flexibility by using perception-based localization and dynamic path planning. However, modern intralogistics environments often require both robustness and adaptability, creating a need for architectures that combine the strengths of both approaches.This study presents a structured architectural analysis of AGV and AMR systems using the interaction-based system architecture methodology proposed by Pimmler and Eppinger [1]. The analysis distinguishes between physical and functional system perspectives to identify architectural dependencies within mobile transport robots. Interactions between subsystems are analyzed using matrices that classify spatial, energy, information, and material dependencies. The results show that AGV and AMR platforms share largely identical physical subsystem architectures, including navigation hardware, motion systems, energy supply, load handling mechanisms, control units, and safety components. In contrast, significant differences emerge at the functional level, particularly in perception, localization, and path planning. AMR systems exhibit stronger information dependencies due to their reliance on dynamic environment perception and adaptive navigation. Based on these findings, a hybrid architecture is derived that combines the standardized hardware structure of AGVs with the adaptive navigation capabilities of AMRs. Although conceptual, the proposed architecture provides a structured framework for integrating flexible navigation capabilities into established industrial mobile transport robots.