Collision probability reduction method for tracking control in automatic docking/berthing using reinforcement learning

Wakita, Kouki; Akimoto, Youhei; Rachman, Dimas M. et al.

Journal of Marine Science and Technology (Japan), 2023, 28, 844-861

Number of Access:450（2025-10-01 06:45 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/93224

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Title
Collision probability reduction method for tracking control in automatic docking/berthing using reinforcement learning
Creator
ORCID
0000-0003-0363-1396 0000-0003-0363-1396
CreatorName
Wakita, Kouki
NRID
1000020709654 1000020709654
CreatorName
Akimoto, Youhei
CreatorName
Rachman, Dimas M.
CreatorName
Miyauchi, Yoshiki
NRID
1000050556496 1000050556496
ORCID
0000-0002-2819-1297 0000-0002-2819-1297
researchmap permalink
atsuo_maki atsuo_maki
Scopus Author ID
24503751100 24503751100
CreatorName
Maki, Atsuo
Subject
Berthing control
Reinforcement learning
TD3
Trajectory tracking
VecTwin rudder
Description
The version of record of this article, first published in Journal of Marine Science and Technology (Japan), is available online at Publisher’s website: https://doi.org/10.1007/s00773-023-00962-5
Abstract
Automation of berthing maneuvers in shipping is a pressing issue as the berthing maneuver is one of the most stressful tasks seafarers undertake. Berthing control problems are often tackled by tracking a predefined trajectory or path. Maintaining a tracking error of zero under an uncertain environment is impossible; the tracking controller is nonetheless required to bring vessels close to desired berths. The tracking controller must prioritize the avoidance of tracking errors that may cause collisions with obstacles. This paper proposes a training method based on reinforcement learning for a trajectory tracking controller that reduces the probability of collisions with static obstacles. Via numerical simulations, we show that the proposed method reduces the probability of collisions during berthing maneuvers. Furthermore, this paper shows the tracking performance in a model experiment.
Publisher
Springer
Source Title
Journal of Marine Science and Technology (Japan)
Volume (Issue)
28
Page
844-861
Date of Issued
2023-10-19
Language
English
Handle URL
https://hdl.handle.net/11094/93224
PISSN
09484280
Relation.isIdenticalTo
DOI (Publisher Version)
https://doi.org/10.1007/s00773-023-00962-5
Access Rights
open access
CopyRight
This article is licensed under a Creative Commons Attribution 4.0 International License.
oaire:version
Version of Record
Category
学術雑誌論文 Journal Article