Project DMAP

Abstract

The DMAP project (5G-Powered Collaborative Dynamic Mapping for Smart Logistics) aims to revolutionize industrial intralogistics by evolving autonomous navigation from isolated, static-map reliance to a 5G-enabled, collaborative spatial intelligence framework. Current Level 4 industrial Autonomous Mobile Robots (AMRs) used in heavy-duty vehicle logistics, operate using pre-defined static maps. This creates significant operational bottlenecks when faced with dynamic obstacles, traffic congestions, or facility changes, as individual units remain unaware of the broader environmental context. DMAP introduces a unified, cloud-based Dynamic Semantic Map updated in real-time through high-speed 5G streams. The system leverages Collaborative Semantic Mapping, where perception data from multiple AMRs (3D LiDAR/IMU/RADAR/Camera fusion) and fixed infrastructure sensors (RSUs/Cameras) are fused at the Multi-Access Edge Computing (MEC) level. By utilizing 5G Network Slicing, DMAP ensures mission-critical performance: an URLLC slice guarantees sub-10ms latency for safety-critical data, while an eMBB slice facilitates the high-bandwidth transmission of 3D point clouds. The project will deliver a Live Semantic Twin of the facility, enabling predictive long-horizon planning and edge-native coordination. By eliminating deadlocks and enabling proactive path planning, DMAP transforms factory logistics into a synchronized, transparent, and highly adaptive ecosystem, setting a new benchmark for 5G-Advanced industrial applications.