Research
Research Area
Our vision is to render every system involved in maritime transport, from the power and propulsion plant (i.e. fuel engine, propeller, motor) of a vessel up to the vessel traffic system autonomous with safety being the key priority!
The necessary condition for safe autonomous maritime transport is to guarantee the safe operation of every system individually. The sufficient condition though is to guarantee the safe interaction between these systems at the same level, but also transversally.
To materialize this vision we design software-based agents in a cyber-physical-human (CPH) system framework for monitoring, automatic control, planning and coordination to handle significant uncertainties (e.g. environmental effects, modelling errors, unknown human behavior, dynamic operational environment) and unexpected events (e.g. sensor faults, engine faults, communication errors, cyber-attacks, collisions, traffic congestion).
Research Publications
N. Kougiatsos, J. Zwaginga, J. Pruyn and V. Reppa, "Semantically Enhanced System and Automation Design of Complex Marine Vessels," 2023 IEEE Symposium Series on Computational Intelligence (SSCI), Mexico City, Mexico, 2023, pp. 512-518, doi: 10.1109/SSCI52147.2023.10372005
2023
Du, Z., Negenborn, R.R. and Reppa, V., 2022. Review of floating object manipulation by autonomous multi-vessel systems. Annual Reviews in Control.
Segovia, P., Pesselse, M., Van Den Boom, T. and Reppa, V., 2022. Scheduling Inland Waterway Transport Vessels and Locks Using a Switching Max-Plus-Linear Systems Approach. IEEE Open Journal of Intelligent Transportation Systems, 3, pp.748-762.
Du, Z., Negenborn, R.R. and Reppa, V., 2022, August. Dynamic coordination of multiple vessels for offshore platform transportation. In 2022 IEEE Conference on Control Technology and Applications (CCTA), pp. 76-81
Kougiatsos, N., Negenborn, R.R. and Reppa, V., 2022. A Multi-Sensory Switching-stable Architecture for Distributed Fault Tolerant Propulsion Control of Marine Vessels. In Proceedings of the International Ship Control Systems Symposium (Vol. 16, p. 27).
van Benten, M.C., Kougiatsos, N. and Reppa, V., 2022. Mission-oriented modular control of retrofittable marine power plants. In Proceedings of the International Ship Control Systems Symposium (Vol. 16, p. 20).
Hepworth, M., Garofano, V., Pang, Y. and Reppa, V., 2022. A Stereovision-based Navigation System for Autonomous Inland Vessels. In Proceedings of the International Ship Control Systems Symposium (Vol. 16, p. 6).
Tsolakis, A. et al. (2022). COLREGs-Aware Trajectory Optimization for Autonomous Surface Vessels. IFAC CAMS.
Kougiatsos, N. & Reppa, V. (2022). A Distributed Virtual Sensor Scheme for Marine Fuel Engines. IFAC CAMS.
Kougiatsos, N., Negenborn, R. R., & Reppa, V. (2022). Distributed model-based sensor fault diagnosis of marine fuel engines. IFAC-PapersOnLine, 55(6), 347-353.
Dann, N., Segovia, P. and Reppa, V., 2022. Adaptive Learning of Inland Ship Power Propulsion under Environmental Disturbances. IFAC-PapersOnLine, 55(31), pp.1-6.
Du, Z., Negenborn, R. R., & Reppa, V. (2022). COLREGS-Compliant collision avoidance for physically coupled multi-vessel systems with distributed MPC. Ocean Engineering, 260, 111917.
Du, Z., Negenborn, R. R., & Reppa, V. (2022). Multi-objective cooperative control for a ship-towing system in congested water traffic environments. IEEE Transactions on Intelligent Transportation Systems.
Segovia, P., Negenborn, R. R., & Reppa, V. (2022). Vessel passage scheduling through cascaded bridges using mixed-integer programming. IFAC-PapersOnLine, 55(16), 248-253.
2022
Zhang, Q., Zhang, X., Zhu, B. and Reppa, V., 2021, December. Fault tolerant control for autonomous surface vehicles via model reference reinforcement learning. In 2021 60th IEEE Conference on Decision and Control (CDC) (pp. 1536-1541).
Antonopoulos, S., Visser, K., Kalikatzarakis, M. and Reppa, V., 2021. MPC framework for the energy management of hybrid ships with an energy storage system. Journal of Marine Science and Engineering, 9(9), p.993.
van Pampus, M.J., Haseltalab, A., Garofano, V., Reppa, V., Deinema, Y.H. and Negenborn, R.R., 2021, June. Distributed leader-follower formation control for autonomous vessels based on model predictive control. In 2021 European Control Conference (ECC) (pp. 2380-2387).
Zhang, Q., Pan, W. and Reppa, V., 2021. Model-reference reinforcement learning for collision-free tracking control of autonomous surface vehicles. IEEE Transactions on Intelligent Transportation Systems, 23(7), pp.8770-8781.
Ye, J., Roy, S., Godjevac, M., Reppa, V. and Baldi, S., 2021. Robustifying dynamic positioning of crane vessels for heavy lifting operation. IEEE/CAA Journal of Automatica Sinica, 8(4), pp.753-765.
Ye, J., Reppa, V., Godjevac, M. and Negenborn, R.R., 2021. Construction mode detection for autonomous offshore heavy lift operations. Safety Science, 133, p.104991.
Du, Z., Reppa, V., & Negenborn, R. R. (2021, June). Mpc-based colregs compliant collision avoidance for a multi-vessel ship-towing system. In 2021 European Control Conference (ECC) (pp. 1857-1862). IEEE.
Du, Z., Negenborn, R. R., & Reppa, V. (2021). Cooperative multi-agent control for autonomous ship towing under environmental disturbances. IEEE/CAA Journal of Automatica Sinica, 8(8), 1365-1379.
Du, Z., Negenborn, R. R., & Reppa, V. (2021). Multi-vessel cooperative speed regulation for ship manipulation in towing scenarios. IFAC-PapersOnLine, 54(16), 384-389.
2021
Zhang, Q., Pan, W. and Reppa, V., 2020, December. Model-reference reinforcement learning control of autonomous surface vehicles. In 2020 59th IEEE Conference on Decision and Control (CDC) (pp. 5291-5296). IEEE.
Du, Z., Reppa, V., & Negenborn, R. R. (2020). Cooperative control of autonomous tugs for ship towing. IFAC-PapersOnLine, 53(2), 14470-14475.
Ye, J., Reppa, V. and Negenborn, R.R., 2020. Backstepping control of heavy lift operations with crane vessels. IFAC-PapersOnLine, 53(2), pp.14704-14709.
2020