The overall mission is to advance transport through innovative technologies, harnessing the power of informatics and robotics to radically advance the future of the industry. The lab was founded with two main objectives: to develop tools that improve transportation systems of all kinds, and to train the next generation of professionals in this direction.
In cooperation with a worldwide network of industrial and scientific partners, the developed solutions can be evaluated in a continuous chain reaching from the application concept simulation in lab trials to in the field testing in no time.
For example in the context of the “Ro-Boat Races”, sea trials under realistic conditions guarantee an application-related real world assessment. This unique combination of laboratory infrastructure and realistic missions to examine and evaluate technology readiness enables the development of robust and reliable systems.
Members of the SMART MOVE lab have participated in several EU funded projects such as: VesselAI, BigDataOcean, RELAR, SELIS and many more.
Currently active projects of the lab may be found below:
RELAR (REmote Learning system based on AR in maritime VET education)
RELAR project aims to create a crisis-proof resilient maritime VET ecosystem by enabling remote learning and examination using Augmented Reality. This project addresses key challenges of the maritime and port education ecosystem caused by structural change due to new digital technologies.
Study for Eurostat
Study to support an Impact Assessment for the revision of Regulation (EC) No. 223/2009 on European Statistics for Eurostat
Below are listed some of the most significant research publications of the Laboratory from the previous year. The articles cover topics from the entire portfolio of research programs.
Millefiori, L.M., Braca, P., Zissis, D. et al. COVID-19 impact on global maritime mobility. Nature Sci Rep 11, 18039 (2021). https://doi.org/10.1038/s41598-021-97461-7
G. Ferri et al., “Developing a Robotic Hybrid Network for Coastal Surveillance: the INFORE Experience,” OCEANS 2021: San Diego – Porto, 2021, pp. 1-10, doi: 10.23919/OCEANS44145.2021.9705662.
Xidias, E., Zacharia, P. & Nearchou, A. Intelligent fleet management of autonomous vehicles for city logistics. Appl Intell (2022). https://doi.org/10.1007/s10489-022-03535-y
N. Zygouras, G. Spiliopoulos and D. Zissis, “Detecting representative trajectories from global AIS datasets,” 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 2278-2285, doi: 10.1109/ITSC48978.2021.9564657.
(2021) A Decision Algorithm for Motion Planning of Car-Like Robots in Dynamic Environments, Cybernetics and Systems, 52:6, 533-52, DOI: 10.1080/01969722.2021.1909844
Word cloud obtained from the titles of our publications