Journal of Ocean Engineering and Technology (한국해양공학회지)

Korean Society of Ocean Engineers (한국해양공학회)
권호 표지
DOI QR코드

DOI QR Code

Trajectory Optimization for Autonomous Berthing of a Twin-Propeller Twin-Rudder Ship

  • Received : 2023.05.16
  • Accepted : 2023.06.14
  • Published : 2023.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Autonomous berthing is a crucial technology for autonomous ships, requiring optimal trajectory planning to prevent collisions and minimize time and control efforts. This paper presents a two-phase, two-point boundary value problem (TPBVP) strategy for creating an optimal berthing trajectory for a twin-propeller, twin-rudder ship with autonomous berthing capabilities. The process is divided into two phases: the approach and the terminal. Tunnel thruster use is limited during the approach but fully employed during the terminal phase. This strategy permits concurrent optimization of the total trajectory duration, individual phase trajectories, and phase transition time. The efficacy of the proposed method is validated through two simulations. The first explores a scenario with phase transition, and the second generates a trajectory relying solely on the approach phase. The results affirm our algorithm's effectiveness in deciding transition necessity, identifying optimal transition timing, and optimizing the trajectory accordingly. The proposed two-phase TPBVP approach holds significant implications for advancements in autonomous ship navigation, enhancing safety and efficiency in berthing operations.

Keywords

Acknowledgement

This research was supported by a grant from the National R&D Project "Development of an electric-powered car ferry and a roll-on/roll-off power supply system" funded by the Ministry of Oceans and Fisheries, Korea (Grant No. PMS4420).

References

  1. Andersson, J. A. E., Gillis, J., Horn, G., Rawlings, J. B., & Diehl, M. (2019). CasADi: A software framework for nonlinear optimization and optimal control. Mathematical Programming Computation, 11(1), Article 1. https://doi.org/10.1007/s12532-018-0139-4
  2. Bitar, G., Eriksen, B.-O. H., Lekkas, A. M., & Breivik, M. (2021). Three-Phase Automatic Crossing for a Passenger Ferry With Field Trials. 2021 European Control Conference (ECC), 2271-2277. https://doi.org/10.23919/ECC54610.2021.9655139
  3. Bitar, G., Martinsen, A. B., Lekkas, A. M., & Breivik, M. (2020). Trajectory Planning and Control for Automatic Docking of ASVs with Full-Scale Experiments**This work is supported by the Research Council of Norway through the project number 269116 as well as through the Centres of Excellence funding scheme with project number 223254. IFAC-PapersOnLine, 53(2), 14488-14494. https://doi.org/10.1016/j.ifacol.2020.12.1451
  4. Fossen, T. I. (2011). Handbook of Marine Craft Hydrodynamics and Motion Control. John Wiley & Sons.
  5. Lindegaard, K.-P. (2003). Acceleration feedback in dynamic positioning.
  6. Lindegaard, K.-P., & Fossen, T. I. (2003). Fuel-efficient rudder and propeller control allocation for marine craft: Experiments with a model ship. IEEE Transactions on Control Systems Technology, 11(6), 850-862. https://doi.org/10.1109/TCST.2003.815613
  7. Martinsen, A. B., Bitar, G., Lekkas, A. M., & Gros, S. (2020). Optimization-Based Automatic Docking and Berthing of ASVs Using Exteroceptive Sensors: Theory and Experiments. IEEE Access, 8, 204974-204986. https://doi.org/10.1109/ACCESS.2020.3037171
  8. Martinsen, A. B., Lekkas, A. M., & Gros, S. (2019). Autonomous docking using direct optimal control. IFAC-PapersOnLine, 52(21), Article 21.
  9. Martinsen, A. B., Lekkas, A. M., & Gros, S. (2022). Optimal Model-Based Trajectory Planning With Static Polygonal Constraints. IEEE Transactions on Control Systems Technology, 30(3), Article 3. https://doi.org/10.1109/TCST.2021.3094617
  10. Miyauchi, Y., Sawada, R., Akimoto, Y., Umeda, N., & Maki, A. (2022). Optimization on planning of trajectory and control of autonomous berthing and unberthing for the realistic port geometry. Ocean Engineering, 245, 110390. https://doi.org/10.1016/j.oceaneng.2021.110390
  11. Odven, P. K., Martinsen, A. B., & Lekkas, A. M. (2022). Static and dynamic multi-obstacle avoidance and docking of ASVs using computational geometry and numerical optimal control. IFAC-PapersOnLine, 55(31), Article 31. https://doi.org/10.1016/j.ifacol.2022.10.408
  12. Quan, T. D., Suh, J.-H., & Kim, Y.-B. (2019). Leader-Following Control System Design for a Towed Vessel by Tugboat. Journal of Ocean Engineering and Technology, 33(5), 462-469. https://doi.org/10.26748/KSOE.2019.075
  13. Rachman, D. M., Maki, A., Miyauchi, Y., & Umeda, N. (2022). Warm-started semionline trajectory planner for ship's automatic docking (berthing). Ocean Engineering, 252, 111127. https://doi.org/10.1016/j.oceaneng.2022.111127
  14. Skjetne, R., Smogeli, O. N., & Fossen, T. I. (2004). A Nonlinear Ship Manoeuvering Model: Identification and adaptive control with experiments for a model ship. Modeling, Identification and Control: A Norwegian Research Bulletin, 25(1), 3-27. https://doi.org/10.4173/mic.2004.1.1
  15. Wachter, A., & Biegler, L. T. (2006). On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming. Mathematical Programming, 106(1), 25-57. https://doi.org/10.1007/s10107-004-0559-y