Evolution of Industry 5.0 Using AI-Based AMRs in Industrial Private 5G Network
TL;DR
This comparative analysis establishes AMRs’ performance advantages over AGVs and Private 5G’s operational superiority versus alternative connectivity approaches, and examines the computing architectures supporting AMR systems, each with distinct implications for safety-critical industrial deployments.
Abstract
Artificial Intelligence (AI)-enabled Autonomous Mobile Robots (AMRs) are transforming industrial operations across manufacturing and logistics - accounting for 65% of new deployments in 2025 and displacing traditional Automated Guided Vehicles (AGVs) through superior navigation, flexibility, and autonomous decision-making. This paper examines the evolution and integration of AMRs with Private 5G networks in industrial applications. Traditional connectivity options, namely: wired networks, Wi-Fi, and public cellular, cannot meet the mobility, reliability, and latency requirements of industrial AMR deployments. Private 5G networks address these limitations through deterministic performance, dedicated spectrum, and enterprise-grade security. Our comparative analysis establishes AMRs’ performance advantages over AGVs and Private 5G’s operational superiority versus alternative connectivity approaches. In this work, we examine the computing architectures supporting AMR systems (local, edge, centralized, and hybrid), each with distinct implications for safety-critical industrial deployments. The integration of AI/ML with distributed intelligence and human-robot collaboration requires consistent, low-latency communication, particularly for safety-critical and shared workflows. This AMR-Private 5G integration positions industrial operations at the threshold of Industry 5.0, enabling autonomous, adaptive systems that enhance operational flexibility, safety, and productivity.