Development of a Monitoring and Simulation Platform for Autonomous Inland Waterway Vessels

In this work, a monitoring and simulation platform for vessels operating in inland waterways was developed based on Unreal Engine, aiming to support the autonomous operation of the inland waterway traffic system and provide a modern user interface at the same time, as well as to enable virtual testing and prediction in the future. This platform was developed and tested within the scope of an ongoing research project A-SWARM II, where a concept for a swarm of small-scaled, electrically propelled autonomous freight ships was developed and demonstrated in the waterways of the Berlin-Brandenburg area. Leveraging the Data Distribution Service (DDS), the platform ensures seamless interoperability with the Robot Operating System (ROS2), enabling real-time monitoring of critical data from waterway vessel sensors, such as location, ship motion, battery charge levels, and load status. By integrating inland electronic navigation charts (IENC) into Unreal Engine and utilizing the 3D geospatial database Cesium, the platform accurately represents the surrounding environment and waterway infrastructure. This integration allows for reliable remote operation and efficient navigation. Due to its architecture design, this monitoring platform can share the navigation-relevant information such as location of traffic participants and waterway infrastructure with other waterway participants, showing its universality and enabling a global optimal route planning for the whole system.