Demo: Towards 6G-Enabled Multi-Robot Process Orchestration in Complex Logistics Environments

Autonomous mobile robots increasingly rely on sensor-rich perception and compute-intensive processing, posing challenges for energy efficiency and latency in dynamic environments. In this work, we present a Kubernetes-based implementation of the Human-Enhanced Robot Orchestration (HERO) framework, enabling context-aware, real-time robot process orchestration across cloud-edge nodes. Computation-intensive processes such as visual and LiDAR Simultaneous Localization and Mapping (SLAM), radar-based collision avoidance with 6G-driven Joint-Communication and Sensing (JCAS) functionalities, and environment segmentation, are deployed dynamically based on environmental information, resource availability, network quality, and battery status of the robot systems. The framework is based on a microservice architecture that offers dynamic and adaptive workload placement and live migration of robotic containers across a 5G campus network. In this work, we demonstrate and evaluate the framework by comparing it to other process orchestration strategies. Our evaluation shows that the implemented framework offers longer process times without interruptions while maintaining efficiency in network usage and energy consumption. This is a first step towards enabling seamless dynamic and adaptive multi-robot process orchestration, exemplifying the future of cloud-native, AI-driven mobile networks and underlining its potential for intelligent fleet coordination and energy-efficient robot process execution.