The objective of the SSAVE project is to develop a framework enabling shared situational awareness for maritime vessels. Advancements in connected and maritime vehicles are severely constrained by the limitations of existing communication methodologies and data exchange information. Due to the insecure nature of the current information sharing platform (like AIS) between vessels, information sharing is vulnerable to spoofing. Also the data content of AIS, today, Is estimated to be 100% correct in only 30% of the cases. AIS update rates are too low to be valuable in autonomous systems and further decrease when many assets are active simultaneously within one zone.
The goal is to improve data quality, interconnectivity and interoperability between assets in the maritime and inland waterway environment. This will be achieved by allowing secure and verified direct and indirect communication between assets. The exchanged data information will be extended with additional sensor information to efficiently represent and communicate shared situational awareness. This sensor data extension, representation and communication is a crucial step towards efficient and flexible interoperability.
Project Publications
2022
- R. Lahouli, G. De Cubber, B. Pairet, C. Hamesse, T. Freville, and R. Haelterman, “Deep Learning based Object Detection and Tracking for Maritime Situational Awareness," in Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications – Volume 4: VISAPP,, 2022, pp. 643-650.
[BibTeX] [Download PDF] [DOI]@conference{visapp22, author={Lahouli, Rihab and De Cubber, Geert and Pairet, Benoit and Hamesse, Charles and Freville, Timothee and Haelterman, Rob}, title={Deep Learning based Object Detection and Tracking for Maritime Situational Awareness}, booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,}, year={2022}, pages={643-650}, publisher={SciTePress}, organization={INSTICC}, doi={10.5220/0010901000003124}, isbn={978-989-758-555-5}, project={SSAVE}, url={https://www.scitepress.org/PublicationsDetail.aspx?ID=mJ5eF6o+SbM=&t=1}, unit= {meca-ras} }
2021
- G. De Cubber, R. Lahouli, D. Doroftei, and R. Haelterman, “Distributed coverage optimisation for a fleet of unmanned maritime systems," ACTA IMEKO, vol. 10, iss. 3, pp. 36-43, 2021.
[BibTeX] [Abstract] [Download PDF] [DOI]
Unmanned maritime systems (UMS) can provide important benefits for maritime law enforcement agencies for tasks such as area surveillance and patrolling, especially when they are able to work together as one coordinated system. In this context, this paper proposes a methodology that optimises the coverage of a fleet of UMS, thereby maximising the opportunities for identifying threats. Unlike traditional approaches to maritime coverage optimisation, which are also used, for example, in search and rescue operations when searching for victims at sea, this approach takes into consideration the limited seaworthiness of small UMS, compared with traditional large ships, by incorporating the danger level into the design of the optimiser.
@ARTICLE{cubberimeko2021, author={De Cubber, Geert and Lahouli, Rihab and Doroftei, Daniela and Haelterman, Rob}, journal={ACTA IMEKO}, title={Distributed coverage optimisation for a fleet of unmanned maritime systems}, year={2021}, volume={10}, number={3}, pages={36-43}, issn={2221-870X}, url={https://acta.imeko.org/index.php/acta-imeko/article/view/IMEKO-ACTA-10%20%282021%29-03-07/pdf}, project={MarSur, SSAVE}, publisher={IMEKO}, month=oct, abstract = {Unmanned maritime systems (UMS) can provide important benefits for maritime law enforcement agencies for tasks such as area surveillance and patrolling, especially when they are able to work together as one coordinated system. In this context, this paper proposes a methodology that optimises the coverage of a fleet of UMS, thereby maximising the opportunities for identifying threats. Unlike traditional approaches to maritime coverage optimisation, which are also used, for example, in search and rescue operations when searching for victims at sea, this approach takes into consideration the limited seaworthiness of small UMS, compared with traditional large ships, by incorporating the danger level into the design of the optimiser. }, doi={http://dx.doi.org/10.21014/acta_imeko.v10i3.1031}, unit= {meca-ras}} - Y. Baudoin, G. De Cubber, and E. Cepolina, “Mobile Robots Supporting Risky Interventions, Humanitarian actions and Demining, in particular the promising DISARMADILLO Tool," in Proceedings of TC17-VRISE2021 – A VIRTUAL Topical Event of Technical Committee on Measurement and Control of Robotics (TC17), International Measurement Confederation (IMEKO), Theme: “Robotics for Risky Interventions and Environmental Surveillance", Houston, TX, USA, 2021, pp. 5-6.
[BibTeX] [Download PDF]@INPROCEEDINGS{knvrise, author={Baudoin, Yvan and De Cubber, Geert and Cepolina, Emanuela}, booktitle={Proceedings of TC17-VRISE2021 - A VIRTUAL Topical Event of Technical Committee on Measurement and Control of Robotics (TC17), International Measurement Confederation (IMEKO), Theme: "Robotics for Risky Interventions and Environmental Surveillance"}, title={Mobile Robots Supporting Risky Interventions, Humanitarian actions and Demining, in particular the promising DISARMADILLO Tool}, year={2021}, volume={}, number={}, pages={5-6}, url={https://mecatron.rma.ac.be/pub/2021/TC17-VRISE2021-Abstract%20Proceedings.pdf}, project={AIDED, Alphonse, MarSur, SSAVE, MarLand, iMUGs, ICARUS, TIRAMISU}, publisher={IMEKO}, address={Houston, TX, USA}, month=oct, unit= {meca-ras} }
2020
- G. De Cubber, R. Lahouli, D. Doroftei, and R. Haelterman, “Distributed coverage optimization for a fleet of unmanned maritime systems for a maritime patrol and surveillance application," in ISMCR 2020: 23rd International Symposium on Measurement and Control in Robotics, Budapest, Hungary, 2020.
[BibTeX] [Abstract] [Download PDF] [DOI]
In order for unmanned maritime systems to provide added value for maritime law enforcement agencies, they have to be able to work together as a coordinated team for tasks such as area surveillance and patrolling. Therefore, this paper proposes a methodology that optimizes the coverage of a fleet of unmanned maritime systems, and thereby maximizes the chances of noticing threats. Unlike traditional approaches for maritime coverage optimization, which are also used for example in search and rescue operations when searching for victims at sea, this approaches takes into consideration the limited seaworthiness of small unmanned systems, as compared to traditional large ships, by incorporating the danger level in the design of the optimizer.
@InProceedings{decubber2020dco, author = {De Cubber, Geert and Lahouli, Rihab and Doroftei, Daniela and Haelterman, Rob}, booktitle = {ISMCR 2020: 23rd International Symposium on Measurement and Control in Robotics}, title = {Distributed coverage optimization for a fleet of unmanned maritime systems for a maritime patrol and surveillance application}, year = {2020}, month = oct, organization = {ISMCR}, publisher = {{IEEE}}, abstract = {In order for unmanned maritime systems to provide added value for maritime law enforcement agencies, they have to be able to work together as a coordinated team for tasks such as area surveillance and patrolling. Therefore, this paper proposes a methodology that optimizes the coverage of a fleet of unmanned maritime systems, and thereby maximizes the chances of noticing threats. Unlike traditional approaches for maritime coverage optimization, which are also used for example in search and rescue operations when searching for victims at sea, this approaches takes into consideration the limited seaworthiness of small unmanned systems, as compared to traditional large ships, by incorporating the danger level in the design of the optimizer.}, project = {SSAVE,MarSur}, address = {Budapest, Hungary}, doi = {10.1109/ISMCR51255.2020.9263740}, url = {http://mecatron.rma.ac.be/pub/2020/conference_101719.pdf}, unit= {meca-ras} }