This autonomous navigation initiative is advancing steadily within the automotive sector, yet it remains a core focus in its mission. While autonomous watercraft and certain sports applications remain limited, the Ocean European project, led by the Polytechnic University of Catalonia BarcelonaTech, aims to secure safer journeys by providing robust tools and methodologies. UPC researchers are building algorithms grounded in signal processing and machine learning to detect obstacles at sea.
In the automotive world, most cars priced above thirty thousand euros already include collision avoidance, lane-keeping assistance, and pedestrian detection systems. By comparison, only a few large ships feature early warning systems, and even then the capabilities are often costly and relatively primitive. The Ocean project aspires to steer 21st century navigation changes in seafaring, especially during slow or idling conditions when risks rise.
Each year the European naval fleet experiences around 3,000 incidents. About 28 percent are categorized as severe or very severe, resulting in casualties, pollution, fires, or property damage. Data from the European Maritime Safety Agency shows that most of these incidents occur during routine operations aboard freight ships, passenger vessels, and service fleets. The Ocean project carries clear economic incentives, particularly for the insurance sector. A consortium of 13 partners spanning seven European nations collaborates on Ocean, including UPC with the Center for Language and Speech Technologies and Applications TALP, part of the IDEAI research hub focused on intelligent data science and artificial intelligence. Other participants include the Transportation Innovation center and CIMNE, among entities in Norway, Greece, Spain, Denmark, Portugal, Ireland, and the United Kingdom.
Goals
Ocean aims to reduce boating incidents caused by human error, technical factors, operational constraints, inadequate procedures, and business pressures. It marks a first step toward professional navigation, giving sport boats more margin to react before risks escalate. Regulatory landscapes will continue to evolve, and enhancements in standards and design approaches are planned for all vessel sizes and equipment on the bridge. Ultimately, the European effort could prevent environmental disasters and safeguard marine ecosystems.
The project is co-financed by the Horizon Europe program and UK Research and Innovation. It began last October and is scheduled to run through 2025. TALP at IDEAI will contribute to sea obstacle detection alongside other European partners. Researchers will develop algorithms based on signal processing and machine learning to automatically identify floating containers and marine mammals from high resolution satellite imagery, as well as acoustic signals for marine mammal detection. Future phases envision onboard motion sensors, radar systems, and autonomous driving technologies integrated with beacon control for ships.
Following data gathered from multiple sources, the Transportation Innovation Center Zenith CIMNEE coordinates the creation of a comprehensive data platform. This platform aggregates forecast and monitoring information from partner organizations and other sea operators. With this data, navigation alerts will indicate obstacle locations at sea, highlighting marine mammals and floating cargo, which can slip from ships during operations. By communicating these locations, vessels can avoid collisions and reduce risk.