Band 70, Heft 5 - Special Issue: Autonomous Shipping and Navigation / Dirk Abel, Thomas Meurer

The demands on maritime shipping, one of the oldest and most international industries in the world, are increasing. The complexity of the transport chains, their constantly increasing size and the evolving regulatory requirements with regard to safety and sustainability continuously present new challenges. In addition, unforeseeable developments and the increasing utilization of the seas by other industries cause a constant uncertainty, by political and military conflicts along main shipping routes, as well as changed routing schemes caused by introduction of new environmental protection areas. Highly automated, remote-controlled or fully autonomous ships are intended to improve safety at sea and lead shipping into a more sustainable future. Experts in the maritime domain recommend the automation of ships (completely or partly unmanned) and the implementation of Artificial intelligence (AI) for more safety in navigation with a harmonized Maritime Cyber Risk Management. In a technology development platform such highly complex maritime systems can be validated and tested under realistic conditions, for instance to engage in determining positions more reliably and resiliently in view of the susceptibility and vulnerability of satellite-based Global Navigation Satellite Systems (GNSS), such as GPS, GLONASS or Galileo.

This paper describes the conception and implementation of the research and control center VeLABi for the development of automation functions up to a fully autonomous inland vessel. A high-tech simulator was designed and built as the central component of VeLABi. It allows simulative developments and demonstrations of automation functions. Furthermore, ongoing research activities aim at transforming the simulator into a remote operators’ stand to remotely control inland vessels and, in case of an autonomous vessel, to provide corresponding monitoring and emergency intervention functions.

Accurate and reliable navigation systems are necessary to deploy autonomous shipping. For this purpose, georeferenced vehicle-pose information is often generated using sensor data fusion consisting of GNSS data, inertial measurement, and other applicable aiding sensors. This technical overview summarizes current European projects and international work in the field of GNSS-based maritime navigation and introduces and discusses the sensors and methods involved. The review focuses on approaches with proprioceptive sensor technology. Therefore, as a limitation, environment sensing algorithms (e. g., SLAM) are explicitly not included. It is concluded that highly accurate and reliable sensor fusion should include complementary and redundant onboard sensors, which are tightly coupled.

The automation of ships will in the long run enable new mobility concepts and profitable business models both for offshore and inland vessels. However, automation in shipping can already today offer significant benefits for the environment as well as for the safety of people, infrastructure and the vessel itself. To gain these advantages, sophisticated sensors, reliable propulsion systems and intelligent algorithms are required. In this context, the project AKOON is investigating the potential of the automation of a river ferry. The ferry under investigation operates on the Rhine near Mainz in Germany and is being converted to a fully automated vessel as part of the research project. This article gives an overview of the guidance, navigation and control (GNC) modules of the automation with focus on the trajectory planning and trajectory tracking modules. The trajectory planning uses hybrid-state A* to find safe and fuel-efficient routes. The subsequent trajectory tracking is achieved by a two-level approach that uses a state-space controller and an optimization-based thrust allocation to efficiently operate the over-actuated propulsion system consisting of four cycloidal propellers. Results from a high-fidelity vessel simulator based on state-of-the-art hydrodynamic simulations show that the presented approach allows the generation of collision-free reference trajectories, that can be tracked safely even in cases of model mismatches and disturbances.

Autonomous ferry operation in harbor and coastal areas is especially challenging due to the tendency to impose a high traffic density, prohibited areas, and a wide variety of different traffic participants to the automation task. To this end, we propose a concept for automated guidance and control of harbor ferry fleet operation. Subsequently, we differentiate guidance into a central, on-land scheduling unit and an on-ship trajectory planning unit that generates a set of waypoints and corresponding desired speeds by means of a flatness-based optimal control problem. Moreover, static obstacles are taken into account by means of a dual approach and the trajectory planning is linked to the control module realized as a path following model predictive control autopilot, which also handles dynamic obstacles.

The paper discusses methods to increase the level of automation in ship handling towards autonomous operations with a focus on conventional vessels in maneuvering situations. In this context, a model-based approach for control system design of maneuvering vessels is introduced. The resulting model is applied to a multivariable control system including allocation, feedforward, and feedback modules. The established hybrid control system distinguishes between a transit mode with control in two degrees of freedom in compliance with the prevailing traffic regulations and a dynamic positioning mode in three degrees of freedom for the final stages of a berthing maneuver. The supervisor switches automatically between these two modes. The methods are validated on board the German research vessel DENEB in the port of Rostock.

Autonomous marine surface vehicles rely on computer systems with computer intelligence making decisions to assist or replace the navigating officer. A fundamental requirement for the design and implementation of such a cyber-physical system is seamless, predictable, and secure interoperability between vendor-specific hardware and software subsystems. The article describes a system design that includes mechanisms to mitigate the risks and consequences of software defects, individual component malfunction, and harmful cyber interference. It addresses international regulations in the field and demonstrates a system design that can meet the requirements for safe behaviour in foreseeable events while also having the ability to call for human assistance if the autonomous system is unable to handle a situation. The paper presents a design for highly automated vessels with several inherent risk-reducing features, including the ability to isolate and encapsulate abnormal behaviours, built-in features to support resilience to unexpected events, and mechanisms for internal defence against cyber-attacks. The article shows how this is provided by a novel middleware that supports risk mitigation, dependability, and resilience.

The paper describes an autonomous water vehicle (ASV) capable of autonomously mapping shallow water environments above and below the water surface. Over the past two years, Fraunhofer IOSB has developed a system that is fully electrified and equipped with extensive sensor technology (multibeam sonar, lidar, cameras, IMU, GNSS). For autonomous navigation, the complete processing pipeline was implemented, from obstacle detection and avoidance to trajectory planning and control to multi-sensor localization and mapping. Above water, both lidar-based mapping and photogrammetric methods are used; underwater, bathymetry data is obtained using sonar. The interface to the operator is realized by an interactive digital map table, which allows intuitive mission specification and evaluation.