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A Methodological Survey of Autonomous Mobile Robots and Automated Guided Vehicles in Industrial Logistics ^†

Automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) are among the key enabling technologies driving intelligent logistics and industrial automation. Despite their widespread adoption and rapid technological evolution, the literature often addresses AGV and AMR systems in a fragmented manner, lacking a structured methodological perspective that highlights their architectural foundations, levels of autonomy, and technological maturity. This paper presents a methodological survey of AGV and AMR technologies, focusing on system-level architectures and core functional components rather than isolated algorithms. The survey systematically analyzes key technological dimensions, including sensing and perception, localization and positioning strategies, navigation and path-planning approaches, communication infrastructures, and multi-robot coordination mechanisms. A clear distinction is drawn between classical AGV systems, which rely on fixed infrastructure and predefined routes, and AMR systems, which exhibit adaptive, perception-driven, and self-configuring behaviors enabled by artificial intelligence techniques. Rather than proposing new algorithms, this paper organizes existing approaches into a coherent framework that highlights technological transitions from infrastructure-dependent guidance to autonomous, data-driven navigation. Recent trends such as cloud–edge integration, learning-based navigation, scalable fleet management architectures, and cooperative multi-robot systems are reviewed and discussed from a methodological standpoint, emphasizing their role in increasing flexibility, robustness, and operational efficiency in industrial and logistics environments. The survey also addresses cross-cutting challenges, including system transparency, safety and certification, interoperability, and sustainability. Finally, this paper outlines research directions aligned with the principles of Industry 5.0, highlighting the need for human-centered, resilient, and scalable AMR and AGV systems capable of safe and explainable operation in complex industrial contexts.

57
17 Sep 2026

Topic Review

Green Engineering

Green engineering is an environmental-focused branch of engineering that investigates the design, commercialization, and operation of processes, products, and systems with the primary objective of minimizing risks to human health and the environment from the earliest stages of conception through to eventual decommissioning [1][2][3]. It prioritizes pollution and waste prevention over end-of-pipe treatment, recognizing that avoiding the generation of hazardous byproducts is fundamentally more effective and cost-efficient than managing them after they have been created. This approach places strong emphasis on inherently safe material selection, reaction pathways, and process optimization that collectively reduce environmental burdens without compromising economic viability or technical performance criteria [2][3]. The discipline employs a cradle-to-grave life cycle framework to systematically assess and mitigate environmental impacts across all developmental stages—from raw material extraction and manufacturing through use, transportation, and end-of-life recovery or disposal—while maintaining that ecological considerations must be structurally integrated into engineering decision-making rather than applied as retrofitted controls after design completion [1][4][5]. As such, the term “green engineering” denotes a safety-by-design and inherently safer methodology applied to macro‑level engineering systems, which is conceptually and methodologically distinct from green chemistry—which focuses on molecular‑level innovations for safer chemicals and reactions—and also distinct from general corporate environmental compliance, which typically addresses regulatory conformance rather than proactive systemic redesign [6][7].

32
11 Sep 2026

Topic Review

Supply Chain Management

Supply chain management refers to the integrated planning, coordination, execution, and control of all business activities associated with the flow of goods, services, information, and financial resources from raw-material sourcing through production, distribution, and final-product delivery to end customers across participating organisations within a supply-chain network [1]. It encompasses cross-organisational coordination among suppliers, manufacturers, logistics providers, distributors, and end-users, aiming to align material and information flows under defined operational, cost, and service-level objectives [2]. Unlike isolated intra-enterprise functional management, SCM emphasises end-to-end governance of the entire network boundary rather than optimisation of any single firm's internal departments in isolation. It covers both forward physical-product flow and reverse-logistics product returns, and it integrates demand forecasting, inventory planning, transportation scheduling, procurement decision-making, warehouse management, and customer-service fulfilment as interconnected components. The discipline treats the supply chain as an interdependent system in which local decisions by one member propagate effects throughout the network, and it seeks to balance total system cost against required service levels rather than minimising any single node's cost independently [3].

8
20 Sep 2026

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