3 Realization

3.2 Implementation

Implementation of automated ship control

Within this work package, the tuned algorithms from work package 3.1 (fine conception and tuning of the algorithms) will be implemented on the ship. For this purpose, a ROS2 infrastructure will be established. ROS2 stands for Robot Operating System 2 and contains a framework for the simple exchange of data between several distributed systems. The sensors installed on the ship provide their data in the form of ROS2 topics within the infrastructure. Nodes of the ROS2 network, which contain an implementation of various algorithms, can then receive and process the data. The same principle is used to provide the control data, which is calculated by the algorithms and then made available to the ship’s actuators.

In addition to simple communication, however, the ROS2 system has other advantages. A recording capability of all sensor and also control data is already natively available within this system. Many algorithms for the navigation of robots, which are already state of the art, are furthermore already integrated into the ROS2 framework. These can also be used for navigation of the autonomous barge. Via the NAV2 package, for example, the A-Star as well as the Time Elastic Bands algorithm can be executed directly with the sensor data provided.


As already described in WP 3.1, navigation is divided into global and local path planning. Both are performed on the basis of so-called obstacle maps and include static (global path planning) and dynamic obstacles (local path planning) in their calculations.

For first tests within the test drives, virtual obstacles are used at first. Using simulated (lidar) point clouds, encounters with other road users and driving through narrow sections of water can initially be tested with a significantly reduced risk.

As soon as a path has been calculated by the path planning, the ship has to follow this path with the help of a controller. For this purpose, different control concepts are tested and parameterized to represent the test vessel. In addition to a PID controller, a sliding window controller is also implemented and tested.

Work packages

The simulation environment as a virtual image of the real world is the central development environment for all control and monitoring algorithms. A digital twin of the test vessel is implemented in the simulation environment.


The development of the automated control of the inland vessel will initially take place in a simulator. In the first work package, the existing simulator will therefore be extended so that sensor readings can be generated virtually. The artificial intelligence (AI) developed in parallel in a modular fashion for ship control and for implementing the driving behavior functions will then be integrated in a simulation model in such a way that a later parallel porting to a real inland waterway vessel will be possible. Furthermore, the behavior of other road users (vessels in the vicinity of the automated barge) will be modeled and integrated into the simulation environment. The development of the AI for the implementation of the driving behavior functions for different tasks is initially carried out in parallel and then tested in the simulator. Fundamental questions about the choice and structure of the module are efficiently addressed in this way.

1.1 Simulator

The virtual home of the digital twin

1.2 AI / Behavior Control

The central algorithms: ship guidance and driving behavior functions

1.3 Behavior of other Road Users

Prerequisite for accident-free traffic: understanding the traffic situation

To test the test vessel, test scenarios are first defined. Subsequently, the automated vessel control is integrated and iteratively adapted. Test runs are absolutely necessary for this. 

2.1 Sensors

The senses of AI

2.2 Actuator

Artificial intelligence takes the control

2.3 Human-Machine Interface

Development of the human-machine interface

The realization of the automation of the test vessel requires a fine conception and coordination of the algorithms. Furthermore, the automation functions must be tested in advance in the simulation environment. This is followed by validation on the real system.

3.1 Fine-Tuning and Tuning of the Algorithms

Fine conception and tuning of the algorithms for the automation of the inland vessel.

3.2 Implementation

Technical implementation of the automation functions

3.3 Integration of Autom. Vessel Guidance in the Simulation Environment

Integration of automated ship guidance in the simulation environment

3.4 Validation ML/KI and Vessel Control

Validation of the AI

Sensors and actuators will be used to equip the test vessel. A human-machine interface is also being developed.

4.1 Definition of Test Scenarios

Testing of the developments

4.2 Integration and Adaptation of Control in Test Vessel

Integration and Adaptation of Control in Test Vessel

4.3 Test Drives and Demonstration

From theory to practice

The simulation environment as a virtual image of the real world is the central development environment for all control and monitoring algorithms. A digital twin of the test vessel is implemented in the simulation environment.

5.1 Profitability Analysis

Economic efficiency analysis

5.2 Rating

Final evaluation of automation