FRT-DS-ESSO

FRT-DS-ESSO is a repository that provides datasets measured in free running tests of Esso Osaka, intended for the purpose of data-driven ship maneuvering modeling. The datasets have been utilized for modeling or system identification in our research papers, specifically in the works authored by Wakita (2022) and Miyauchi (2022).

Experiment Overview

Subject ship (Scaled model ship of Esso Osaka)

The free-running model tests were carried out in the experimental pond known as Inukai pond, located at Osaka University. These tests utilized a model ship of VLCC M.V. Esso Osaka.

An image taken at inukai pond

Principal particular

Item	Value
Length between perpendicular: $L_{\mathrm{pp}} \ (\mathrm{m})$	3.0
Ship breadth: $B \ (\mathrm{m})$	0.489
Ship draft: $d \ (\mathrm{m})$	0.201
Diameter of propeller: $D_{\mathrm{p}} \ (\mathrm{m})$	0.084
Area of Rudder: $A_{\mathrm{R}} \ \left(\mathrm{m}^2\right)$	0.0106
Diameter of bow thruster: $D_{\mathrm{BT}} \ (\mathrm{m})$	0.050
Diameter of stern thruster: $D_{\mathrm{ST}} \ (\mathrm{m})$	0.050
Mass: $m \ (\mathrm{kg})$	244.6
Longitudinal center of gravity: $x_{\mathrm{G}} \ (\mathrm{m})$	0.094
Transverse projected area: $A_{\mathrm{T}} \ \left(\mathrm{m}^2\right)$	0.135
Lateral projected area: $A_{\mathrm{L}} \ \left(\mathrm{m}^2\right)$	0.520
Block coefficient: $C_{\mathrm{b}}$	0.830

Measurement Items

We employ two coordinate systems: the ship-fixed coordinate system denoted as $\mathrm{O}-xy$ and the space-fixed coordinate system denoted as $\mathrm{O}_0-x_0y_0$. These coordinate systems are defined as illustrated in the following right figure. Note that the origin of the $\mathrm{O}_0-x_0y_0$ system is located in close proximity to the corners of the berth.

The observed variables have been outlined in the table provided below. These variables have been derived from measured data. For example, the ship position was observed by converting the GNSS receiver position to midship position. If you require further information, please see our paper for details on the measurement systems of the model ship.

Variable	CSV header	Description
$t$	t [s]	time of measurement.
$x_{0}$	x_position_mid [m]	midship position in $x_{0}$-axis direction.
$u$	u_velo [m/s]	longitudunal ship speed of midship.
$y_{0}$	y_position_mid [m]	midship position in $y_{0}$-axis direction.
$v_{\mathrm{m}}$	vm_velo [m/s]	lateral ship speed of midship.
$\psi$	psi_hat [rad]	ship heading angle.
$r$	r_angvelo [rad/s]	yaw (heading) angular velocity.
$n$	n_prop [rps]	revolution of propeller
$\delta$	delta_rudder [rad]	angle of rudder.
$U_{\mathrm{A}}$	wind_velo_relative_mid [m/s]	relative wind velocity on midship.
$\gamma_{\mathrm{A}}$	wind_dir_relative_mid [rad]	relative wind direction of midship.
$U_{\mathrm{T}}$	wind_velo_true [m/s]	true wind velocity.
$\gamma_{\mathrm{T}}$	wind_dir_true [rad]	true wind direction.

Contents of free-running tests

The dataset contains measurement data from four types of free-running tests: turning test, zigzag test, random test, and berthing test.

Turning test

File path	$n \ \mathrm{[rps]}$	$\delta \ \mathrm{[degree]}$	File path	$n \ \mathrm{[rps]}$	$\delta \ \mathrm{[degree]}$
data/turning/turn_14-Oct-2020_14_08_51.csv	8	35	data/turning/turn_14-Oct-2020_14_17_39.csv	8	35
data/turning/turn_14-Oct-2020_14_29_49.csv	10	20	data/turning/turn_14-Oct-2020_14_39_54.csv	10	20
data/turning/turn_14-Oct-2020_14_56_07.csv	10	-20	data/turning/turn_14-Oct-2020_15_06_53.csv	10	-20
data/turning/turn_14-Oct-2020_15_21_57.csv	10	-35	data/turning/turn_14-Sep-2020_13_39_32.csv	10	35
data/turning/turn_14-Sep-2020_13_51_45.csv	10	35	data/turning/turn_14-Sep-2020_14_16_04.csv	10	-35
data/turning/turn_14-Sep-2020_14_50_41.csv	8	35	data/turning/turn_14-Sep-2020_15_47_33.csv	8	-35
data/turning/turn_14-Sep-2020_15_58_08.csv	10	20	data/turning/turn_cut_14-Sep-2020_15_58_08.csv	10	20
data/turning/turn_cut_14-Sep-2020_16_09_02.csv	10	-20

Zigzag test

File path	$n \ \mathrm{[rps]}$	$\delta \ \mathrm{[degree]}$	File path	$n \ \mathrm{[rps]}$	$\delta \ \mathrm{[degree]}$
data/zigzag/zigzag_31-Jul-2020_13_04_24.csv	16.67	$\pm$ 20	data/zigzag/zigzag_31-Jul-2020_13_14_21.csv	16.67	$\pm$ 30
data/zigzag/zigzag_31-Jul-2020_13_22_52.csv	10	$\pm$ 15	data/zigzag/zigzag_31-Jul-2020_13_29_19.csv	12	$\pm$ 15
data/zigzag/zigzag_31-Jul-2020_13_42_53.csv	10	$\pm$ 30	data/zigzag/zigzag_31-Jul-2020_13_50_28.csv	12	$\pm$ 30
data/zigzag/zigzag_31-Jul-2020_13_57_45.csv	15	$\pm$ 20	data/zigzag/zigzag_31-Jul-2020_14_03_39.csv	12	$\pm$ 20
data/zigzag/zigzag_31-Jul-2020_14_10_05.csv	12	$\pm$ 20

Random test

The random test aims to contain all possible values of control inputs and states to reduce necessary data for training and tests. In this test, control inputs were selected randomly by the human operator to collect datasets including various ship and actuator states. Please see our paper for details of this tests.

Berthing test

The berthing maneuver was conducted in the center of the pond without the berth wall and controlled manually by the operator.

Correspondence table with the paper

• Wakita (2022)

File path	Train-TZB	Train-TZRB	Train-TZRB+	Test (TZRB)
data/random/random_03-Aug-2020_11_04_37.csv	✖️	✖️	⭕️	✖️
data/random/random_06-Aug-2020_16_24_25_1.csv	✖️	✖️	⭕️	✖️
data/random/random_06-Aug-2020_16_24_25_3.csv	✖️	✖️	✖️	⭕️
data/random/random_06-Aug-2020_16_24_25_4.csv	✖️	⭕️	⭕️	✖️
data/random/random_06-Aug-2020_16_24_25_5.csv	✖️	✖️	⭕️	✖️
data/random/random_06-Aug-2020_16_24_25_6.csv	✖️	⭕️	⭕️	✖️
data/random/random_31-Jul-2020_12_29_58.csv	✖️	✖️	⭕️	✖️
data/random/random_31-Jul-2020_12_48_39.csv	✖️	✖️	⭕️	✖️
data/random/random_31-Jul-2020_14_52_18.csv	✖️	✖️	⭕️	✖️
data/turning/turn_14-Oct-2020_14_08_51.csv	✖️	✖️	⭕️	✖️
data/turning/turn_14-Oct-2020_14_17_39.csv	✖️	✖️	⭕️	✖️
data/turning/turn_14-Oct-2020_14_29_49.csv	✖️	✖️	⭕️	✖️
data/turning/turn_14-Oct-2020_14_39_54.csv	✖️	✖️	⭕️	✖️
data/turning/turn_14-Oct-2020_14_56_07.csv	✖️	✖️	⭕️	✖️
data/turning/turn_14-Oct-2020_15_06_53.csv	✖️	✖️	✖️	⭕️
data/turning/turn_14-Oct-2020_15_21_57.csv	✖️	✖️	⭕️	✖️
data/turning/turn_14-Sep-2020_13_39_32.csv	⭕️	✖️	⭕️	✖️
data/turning/turn_14-Sep-2020_13_51_45.csv	✖️	✖️	⭕️	✖️
data/turning/turn_14-Sep-2020_14_16_04.csv	⭕️	✖️	⭕️	✖️
data/turning/turn_14-Sep-2020_14_50_41.csv	✖️	✖️	⭕️	✖️
data/turning/turn_14-Sep-2020_15_47_33.csv	✖️	✖️	⭕️	✖️
data/turning/turn_14-Sep-2020_15_58_08.csv	⭕️	✖️	⭕️	✖️
data/turning/turn_cut_14-Sep-2020_15_58_08.csv	✖️	⭕️	⭕️	✖️
data/turning/turn_cut_14-Sep-2020_16_09_02.csv	⭕️	⭕️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_13_04_24.csv	✖️	✖️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_13_14_21.csv	✖️	✖️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_13_22_52.csv	⭕️	⭕️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_13_29_19.csv	⭕️	✖️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_13_42_53.csv	✖️	✖️	✖️	⭕️
data/zigzag/zigzag_31-Jul-2020_13_50_28.csv	⭕️	⭕️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_13_57_45.csv	⭕️	✖️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_14_03_39.csv	⭕️	✖️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_14_10_05.csv	✖️	✖️	⭕️	✖️
data/berthing/berthing_12-Nov-2020_11_07_23.csv	✖️	✖️	⭕️	✖️
data/berthing/berthing_12-Nov-2020_11_14_47.csv	⭕️	⭕️	⭕️	✖️
data/berthing/berthing_12-Nov-2020_11_21_46.csv	✖️	✖️	⭕️	✖️
data/berthing/berthing_12-Nov-2020_11_38_50.csv	✖️	✖️	✖️	⭕️
data/berthing/berthing_12-Nov-2020_11_49_21.csv	✖️	✖️	✖️	⭕️
data/berthing/berthing_12-Nov-2020_13_09_11.csv	✖️	✖️	⭕️	✖️
data/berthing/berthing_12-Nov-2020_13_21_03.csv	✖️	✖️	✖️	⭕️
data/berthing/berthing_12-Nov-2020_13_37_05.csv	⭕️	⭕️	⭕️	✖️

• Miyauchi (2022)

File path	Train-R	Train-TR	Train-TRZ	Test
data/random/random_03-Aug-2020_11_04_37.csv	✖️	✖️	✖️	✖️
data/random/random_06-Aug-2020_16_24_25_1.csv	⭕️	✖️	✖️	✖️
data/random/random_06-Aug-2020_16_24_25_3.csv	✖️	✖️	✖️	⭕️
data/random/random_06-Aug-2020_16_24_25_4.csv	⭕️	⭕️	⭕️	✖️
data/random/random_06-Aug-2020_16_24_25_5.csv	⭕️	⭕️	⭕️	✖️
data/random/random_06-Aug-2020_16_24_25_6.csv	⭕️	⭕️	⭕️	✖️
data/random/random_31-Jul-2020_12_29_58.csv	✖️	✖️	✖️	✖️
data/random/random_31-Jul-2020_12_48_39.csv	✖️	✖️	✖️	✖️
data/random/random_31-Jul-2020_14_52_18.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Oct-2020_14_08_51.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Oct-2020_14_17_39.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Oct-2020_14_29_49.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Oct-2020_14_39_54.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Oct-2020_14_56_07.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Oct-2020_15_06_53.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Oct-2020_15_21_57.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Sep-2020_13_39_32.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Sep-2020_13_51_45.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Sep-2020_14_16_04.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Sep-2020_14_50_41.csv	✖️	✖️	✖️	⭕️
data/turning/turn_14-Sep-2020_15_47_33.csv	✖️	✖️	✖️	✖️
data/turning/turn_14-Sep-2020_15_58_08.csv	✖️	✖️	✖️	✖️
data/turning/turn_cut_14-Sep-2020_15_58_08.csv	✖️	⭕️	✖️	✖️
data/turning/turn_cut_14-Sep-2020_16_09_02.csv	✖️	⭕️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_13_04_24.csv	✖️	✖️	✖️	✖️
data/zigzag/zigzag_31-Jul-2020_13_14_21.csv	✖️	✖️	✖️	✖️
data/zigzag/zigzag_31-Jul-2020_13_22_52.csv	✖️	✖️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_13_29_19.csv	✖️	✖️	✖️	✖️
data/zigzag/zigzag_31-Jul-2020_13_42_53.csv	✖️	✖️	✖️	✖️
data/zigzag/zigzag_31-Jul-2020_13_50_28.csv	✖️	✖️	⭕️	✖️
data/zigzag/zigzag_31-Jul-2020_13_57_45.csv	✖️	✖️	✖️	✖️
data/zigzag/zigzag_31-Jul-2020_14_03_39.csv	✖️	✖️	✖️	✖️
data/zigzag/zigzag_31-Jul-2020_14_10_05.csv	✖️	✖️	✖️	⭕️
data/berthing/berthing_12-Nov-2020_11_07_23.csv	✖️	✖️	✖️	✖️
data/berthing/berthing_12-Nov-2020_11_14_47.csv	✖️	✖️	✖️	✖️
data/berthing/berthing_12-Nov-2020_11_21_46.csv	✖️	✖️	✖️	✖️
data/berthing/berthing_12-Nov-2020_11_38_50.csv	✖️	✖️	✖️	✖️
data/berthing/berthing_12-Nov-2020_11_49_21.csv	✖️	✖️	✖️	⭕️
data/berthing/berthing_12-Nov-2020_13_09_11.csv	✖️	✖️	✖️	✖️
data/berthing/berthing_12-Nov-2020_13_21_03.csv	✖️	✖️	✖️	⭕️
data/berthing/berthing_12-Nov-2020_13_37_05.csv	✖️	✖️	✖️	✖️

Citation

If you use dataset in a scientific publication, we would appreciate references to the following papers:

• Wakita, K., Maki, A., Umeda, N., Miyauchi, Y., Shimoji, T., Rachman, D. M., & Akimoto, Y. (2022). On neural network identification for low-speed ship maneuvering model. Journal of Marine Science and Technology, 27(1), 772–785. https://doi.org/10.1007/s00773-021-00867-1
• Miyauchi, Y., Maki, A., Umeda, N., Rachman, D. M., & Akimoto, Y. (2022). System parameter exploration of ship maneuvering model for automatic docking/berthing using CMA-ES. Journal of Marine Science and Technology, 27(2), 1065–1083. https://doi.org/10.1007/s00773-022-00889-3

Biblatex entry:

@article{Wakita2022,
   author = {Kouki Wakita and Atsuo Maki and Naoya Umeda and Yoshiki Miyauchi and Tohga Shimoji and Dimas M Rachman and Youhei Akimoto},
   doi = {10.1007/s00773-021-00867-1},
   issn = {1437-8213},
   issue = {1},
   journal = {Journal of Marine Science and Technology},
   pages = {772-785},
   title = {On neural network identification for low-speed ship maneuvering model},
   volume = {27},
   url = {https://doi.org/10.1007/s00773-021-00867-1},
   year = {2022},
}

@article{Miyauchi2022,
   author = {Yoshiki Miyauchi and Atsuo Maki and Naoya Umeda and Dimas M Rachman and Youhei Akimoto},
   doi = {10.1007/s00773-022-00889-3},
   issn = {1437-8213},
   issue = {2},
   journal = {Journal of Marine Science and Technology},
   pages = {1065-1083},
   title = {System parameter exploration of ship maneuvering model for automatic docking/berthing using CMA-ES},
   volume = {27},
   url = {https://doi.org/10.1007/s00773-022-00889-3},
   year = {2022},
}

License

The dataset is released under the Creative Commons BY-NC 4.0 License.