From Packets to Tasks: Rethinking 6G for Robotics

Abstract

Large-scale, safety-critical, and autonomous robotic systems are emerging as demanding 6G use-cases that expose the limits of connectivity-centric network design. While 5G introduced relevant capabilities such as ultra-reliable low-latency communication (uRLLC), integration with time-sensitive networking (TSN), private networks, network slicing, positioning, and edge computing, next-generation robotic deployments require tasklevel assurance, closed-loop coordination, and outcome-oriented service delivery. This (short) paper argues that robotics can help redefine 6G by shifting the design focus from packetand flow-level quality-of-service toward task completion, deadline compliance, safety assurance, and operational value. We classify robotic systems according to where 5G is sufficient, strained, or inadequate, identify key 5G gaps, and discuss the implications of physical and embodied AI for future network design. A simulation-based techno-economic evaluation shows that task-centric 6G improves robotic service quality and enables clearer monetization through outcome-based models. These findings motivate task and business KPIs as essential metrics for evaluating 6G-enabled robotics.