J.R. Marx et al.
Zisenblätter, N., Damerius, R., Schubert, A.U., Jeinsch, T., 2025. A method for automatic
collision avoidance in confined waters. In: OCEANS 2025 Brest, pp. 1-6. https://doi.
rg/10.1109/0CEANS58557.2025.11104782
Znevoldsen, T.T., Blanke, M., Galeazzi, R., 2023. Autonomy for ferries and harbour buses:
a collision avoidance perspective. IFAC-PapersOnLine 56 (2), 5735-5740. 22nd IFAC
World Congress. https://doi.org/10.1016/j.ifacol.2023.10.528
“ossen, T.I., 2002. Marine Control Systems: Guidance, Navigation and Control of Ships,
Rigs and Underwater Vehicles. Marine Cybernetics AS.
Fossen, T.I., 2011. Handbook of Marine Craft Hydrodynamics and Motion Control. John
Wiley & Sons, Ltd. https://doi.org/10.1002/9781119994138
Gonzalez, R., Kloetzer, M., Mahulea, C., 2017. Comparative study of trajectories re-
sulted from cell decomposition path planning approaches. In: 2017 21st Interna-
:ional Conference on System Theory, Control and Computing (ICSTCC), pp. 49-54.
Attps://doi.org/10.1109/1CSTCC.2017.8107010
Gu, X., Han, M., Zhang, W., Xue, G., Zhang, G., Han, Y., 2019. Intelligent vehicle path
planning based on improved artificial potential field algorithm. In: 2019 International
Zonference on High Performance Big Data and Intelligent Systems (HPBD&IS), pp.
104-109. https: //doi.org/10.1109/HPBDIS.2019.8735451
Aahn, T., Damerius, R., Rethfeldt, C., Schubert, A.U., Kurowski, M., Jeinsch, T., 2022.
Automated maneuvering using model-based control as key to autonomous shipping. at
- Automatisierungstechnik 70 (5), 456-468. https://doi.org/10.1515/auto-2021-0146
Mahn, T., Kolewe, B., Jeinsch, T., 2023. Identification of a maneuvering vessel based
an regular operation. IFAC-PapersOnLine 56 (2), 11584-11589. https://doi.org/10.
1016/j.ifacol.2023.10.460
Hansen, P.N., Enevoldsen, T.T., Papageorgiou, D., Blanke, M., 2022. Autonomous naviga-
tion in confined waters - a COLREGs rule 9 compliant framework. IFAC-PapersOnLine
55 (31), 222-228. 14th IFAC Conference on Control Applications in Marine Systems,
Robotics, and Vehicles CAMS 2022. https://doi.org/10.1016/j.ifacol.2022.10.435
ATart, P.E., Nilsson, N.J., Raphael, B., 1968. A formal basis for the heuristic determination
of minimum cost paths. In: IEEE Transactions on Systems Science and Cybernetics
SSC4. Vol. 2, pp. 100-107.
Aashimoto, H., Nishimura, H., Nishiyama, H., Higuchi, G., 2021. Development of AI-
based automatic collision avoidance system and evaluation by actual ship experiments.
ClassNK Tech. J. 3, 41-50.
Adewing, L., Wabersich, K.P., Menner, M., Zeilinger, M.N., 2020. Learning-based model
predictive control: toward safe learning in control. Ann. Rev. Control Robot. Autonom.
Syst. 3, 269-296.
Higaki, T., Nobe, H., Hashimoto, H., 2024. Human-like automatic berthing system based
ın imitative trajectory plan and tracking control. In: OCEANS 2024 - Singapore. https:
//doi.org/10.1109/0CEANS51537.2024.10682182
Aigo, Y., Sakano, M., Nobe, H., Hashimoto, H., 2023. Development of trajectory-tracking
maneuvering system for automatic berthing/unberthing based on double deep q-
network and experimental validation with an actual large ferry. Ocean Eng. 287.
nttps://doi.org/10.1016/j.oceaneng.2023.115750
Aomburger, H., Baumgärtner, K., Wirtensohn, S., Diehl, M., Reuter, J., 2024a. Iterative
learning-based nonlinear model predictive control of an underactuated autonomous
surface vessel in current fields. In: IEEE Conference on Decision and Control (CDC).
Milan, Italy.
Aomburger, H., Wirtensohn, S., Diehl, M., Reuter, J., 2024b. Energy-optimal planning and
;hrinking horizon MPC for vessel docking in river current fields. European Control
Conference (ECC) .
Homburger, H., Wirtensohn, S., Hoher, P., Baur, T., Griesser, D., Diehl, M., Reuter, J.,
2025. Solgenia — a test vessel toward energy-efficient autonomous water taxi applica-
tions. https: //doi.org/10.48550/arXiv.2502.01207
Aomburger, H., Wirtensohn, S., Reuter, J., 2022. Docking control of a fully-actuated au-
tonomous vessel using model predictive path integral control. In: European Control
Conference (ECC). London, United Kingdom.
ıMO, 1972. Convention on the international regulations for preventing collisions at sea.
1972 (COLREGS).
Jerez, J.L., Goulart, P.J., Richter, S., Constantinides, G.A., Kerrigan, E.C., Morari, M.,
2014. Embedded online optimization for model predictive control at megahertz rates.
[EEE Trans. Automat. Contr. 59 (12), 3238-3251. https: //doi.org/10.1109/TAC.2014.
2351991
Karaman, S., Frazzoli, E., 2010. Incremental sampling-based algorithms for optimal mo-
tion planning. https://doi.org/10.15607/RSS.2010.V1.034
Karez, I., Fadil, M.K.M., Jeinsch, T., 2025. Maritime environmental perception
with FMCW-liDARs. In: OCEANS 2025 Brest, pp. 1-7. https://doi.org/10.1109/
OCEANS58557.2025.11104369
Kavraki, L.E., Svestka, P., Latombe, J.C., Overmars, M.H., 1996a. Probabilistic roadmaps
for path planning in high-dimensional configuration spaces. IEEE Trans. Robot. Au-
tomat. 12 (4), 566-580. https://doi.org/10.1109/70.508439
Kavraki, L.E., Svestka, P., Latombe, J.C., Overmars, M.H., 1996b. Probabilistic roadmaps
for path planning in high-dimensional configuration spaces. IEEE Trans. Robot. Au-
tomat. 12 (4), 566-580. https://doi.org/10.1109/70.508439
Koschorrek, P., Hahn, T., Jeinsch, T., 2018. A thrust allocation algorithm considering
lynamic positioning and roll damping thrust demands using multi-step quadratic pro-
zramming. IFAC-PapersOnLine 51, 438-443. https://doi.org/10.1016/i.ifacol.2018
09.448
Kurowski, M., Roy, S., Gehrt, J.-J., Damerius, R., Büskens, C., Abel, D., Jeinsch, T., 2019a.
Multi-vehicle guidance, navigation and control towards autonomous ship maneuvering
n confined waters. In: 2019 18th European Control Conference (ECC), pp. 2559-7564
https: //doi.org/10.23919/ECC.2019.8795726
Kurowski, M., Thal, J., Damerius, R., Korte, H., Jeinsch, T., 2019b. Automated survey in
very shallow water using an unmanned surface vehicle. IFAC-PapersOnLine 52 (21),
146-151. 12th IFAC Conference on Control Applications in Marine Systems, Robotics,
and Vehicles CAMS 2019. https://doi.org/10.1016/i.ifacol.2019.12.298
Ocean Engineering 343 (2026) 123388
„aValle, S.M., 1998. Rapidly-exploring random trees : a new tool for path planning. The
Annual Research Report.
„aValle, S.M., 2006. Planning Algorithms. Cambridge University Press, Cambridge, U.K.
http://planning.cs.uiuc.edu/.
ewis, F.L., Vrabie, D., Syrmos, V.L., 2012. Optimal Control. Wiley. 3. edition.
ikhachev, M., Ferguson, D., 2009. Planning long dynamically feasible maneuvers for
autonomous vehicles. Int. J. Rob. Res. 28 (8), 933-945. https://doi.org/10.1177/
0278364909340445
"in, P., Choi, W.Y., Chung, C.C., 2020. Local path planning using artificial potential
Äeld for waypoint tracking with collision avoidance. In: 2020 IEEE 23rd International
Conference on Intelligent Transportation Systems (ITSC), pp. 1-7. https: //doi.org/10.
1109/1TSC45102.2020.9294717
ingelbach, F., 2004. Path planning using probabilistic cell decomposition. In: IEEE Inter-
national Conference on Robotics and Automation, 2004. Proceedings. ICRA ’04. 2004.
Vol. 1, pp. 467-472 Vol.1. https://doi.org/10.1109/ROBOT.2004.1307193
ıu, Y., Bu, R., Gao, X., 2018. Ship trajectory tracking control system design based on
sliding mode control algorithm. Pol. Mar. Res. 25 (3), 26-34.
utz, M., Meurer, T., 2021. Optimal trajectory planning and model predictive control of
underactuated marine surface vessels using a flatness-based approach. arXiv preprint
arXiv:2101.12730.
Marx, J., Damerius, R., Jeinsch, T., 2023. Linearized model predictive control with offset-
'reeness for trajectory tracking on inland vessels. In: 2023 31st Mediterranean Con-
“erence on Control and Automation (MED), pp. 692-697. https://doi.org/10.1109/
MED59994.2023.10185819
Marx, J., Damerius, R., Jeinsch, T., 2024. Predictive disturbance rejection method to
control vessels in presence of currents and wind. In: OCEANS 2024 - Singapore.
nttps://doi.org/10.1109/0CEANS51537.2024.10682418
Miyoshi, S., Ioki, T., 2021. Development of maneuvering system for realizing autonomous
ships. ClassNK Technical Journal (3), 67-79.
Voreen, I., Khan, A., Habib, Z., 2016. Optimal path planning using RRT* based approaches:
a survey and future directions. Int. J. Adv. Comput. Sci/ Appl. 7. https: //doi.org/10.
14569/1JACSA.2016.071114
a0, A., 2010. A survey of numerical methods for optimal control. Adv. Astronaut. Sci.
135, 1-32.
Aethfeldt, C., Jeinsch, T., 2024. Combined actuator allocation for underwater vehicles
with variable buoyancy systems using QP-based optimization. In: OCEANS 2024 - Hal-
ıfax, pp. 1-7. https://doi.org/10.1109/0CEANS55160.2024.10754543
Rethfeldt, C., Schubert, A.U., Damerius, R., Kurowski, M., Jeinsch, T., 2021. System ap-
3roach for highly automated manoeuvring with research vessel DENEB. In: 13th IFAC
Conference on Control Applications in Marine Systems, Robotics, and Vehicles CAMS
2021. Vol. 54, pp. 153-160. https: //doi.org/10.1016/j.ifacol.2021.10.087
Zuscio, D., 2013. Model predictive control with integral action: a simple MPC algorithm.
Model. Identif. Control 34, 119-129. https://doi.org/10.4173/mic.2013.3.2
Schubert, A.U., Damerius, R., Jeinsch, T., 2024a. Energy demand of vessels depending on
surrent wind conditions. In: 2024 European Control Conference (ECC), pp. 1147-1152.
nttps://doi.org/10.23919/ECC64448.2024.10590911
Schubert, A.U., Damerius, R., Rethfeldt, C., Kurowski, M., Jeinsch, T., 2022. Adaptation
of parameter space model for automatic maneuvering with research vessel DENEB. In:
2022 30th Mediterranean Conference on Control and Automation (MED), pp. 719-724.
nttps://doi.org/10.1109/MED54222.2022.9837130
Schubert, A.U., Damerius, R., Rethfeldt, C., Kurowski, M., Jeinsch, T., Gluch, M., 2023.
Concepts and system requirements for automatic ship operations. In: OCEANS 2023 -
_imerick. https://doi.org/10.1109/O0CEANSLimerick52467.2023.10244661
Schubert, A.U., Eisenblätter, N., Damerius, R., Jeinsch, T., 2024b. Automatic maneuvering
of vessels with power-optimized thrust allocation. Conference Proceedings of iSCSS.
https://doi.org/10.24868/11146
Schubert, A.U., Kurowski, M., Damerius, R., Fischer, S., Gluch, M., Baldauf, M., Jeinsch,
T., 2019. From manoeuvre assistance to manoeuvre automation. J. Phys. 1357 (1).
nttps://doi.org/10.1088/1742-6596/1357/1/012006
Schubert, A.U., Kurowski, M., Gluch, M., Simanski, O., Jeinsch, T., 2018. Manoeu-
‚ring automation towards autonomous shipping. In: Proceedings of the 14th Inter-
ıational Naval Engineering Conference INEC, International Ship Control Systems
Symposium iSCSS. Glasgow, UK, pp. 1-8. https://doi.org/10.24868/issn.2631-8741
2018.020
Shan, T., Wang, W., Englot, B., Ratti, C., Rus, D., 2020. A receding horizon multi-objective
planner for autonomous surface vehicles in urban waterways. In: 2020 59th IEEE
Conference on Decision and Control (CDC), pp. 4085-4092. https: //doi.org/10.1109/
CDC42340.2020.9304298
Sleumer, N., Tschichold-Gürmann, N., 1999. Exact Cell Decomposition of Arrangements
ısed for Path Planning in Robotics. Technical Report. ETH Zurich. Technical Re-
nort / ETH Zurich, Department of Computer Science 329. https://doi.0rg/10.3929/
ethz-a-006653440
Stentz, A., 2003. Optimal and efficient path planning for unknown and dynamic environ-
‚nents. Proc. IEEE Int. Conf. Robot. Autom. 10, 1-38. https://apps.dtic.mil/sti/html/
ır/ADA273871/
Suzuki, T., 2021. Challenge of technology development through MEGURI 2040 - for safe
navigation and workload reduction. ClassNK Technical Journal (3), 51-58.
Sgrensen, A.J., 2005. Structural issues in the design and operation of marine control sys-
tems. Annu. Rev. Control 29 (1), 125-149.
Theodorou, E., Todorov, E., 2012. Relative entropy and free energy dualities: connections
to path integral and KL control. IEEE Conference on Decision and Control , 1466-1473.
Veksler, A., Johansen, T.A., Borrelli, F., Realfsen, B., 2016. Dynamic positioning with
model predictive control. IEEE Trans. Control Syst. Technol. 24 (1), 162-175. https:
//doi.org/10.1109/TCST.2015.2421342
Wang, W., Fernändez-Gutierrez, D., Doornbusch, R., Jordan, J., Shan, T., Leoni, P., Hage-
mann, N., Schiphorst, J.K., Duarte, F., Ratti, C., Rus, D., 2023. Roboat III: an au-