Vision-based positioning of Unmanned Surface Vehicles using Fiducial Markers for automatic docking

Digerud, Lars; Volden, Øystein; Christensen, Kim A.; Kohtala, Sampsa; Steinert, Martin

doi:10.1016/j.ifacol.2022.10.412

Cited by 6 publications

(2 citation statements)

References 7 publications

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“…In correspondence with safety berthing principles, approaching angle, lateral speed, and wall distance are the most significant indices. Among these, the approaching angle, lateral speed, and other own-ship states are monitored through DGPS (Differential Global Positioning System) and IMU (inertial measurement unit), the berth and bollard location and target-ship detection are determined by the camera [28], millimeter wave RADAR [29], and other position sensors, while in severe weather conditions 3D LIDAR [30], ultrasonic sensor, solar-blind ultraviolet and other measurement gages are employed to make up the deficiencies.…”

Section: Risk Assessment Perception Utilization and Motion Controlmentioning

confidence: 99%

State-of-the-Art Review and Future Perspectives on Maneuvering Modeling for Automatic Ship Berthing

Zhang,

Wu,

Liu

et al. 2023

JMSE

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Automatic berthing is at the top level of ship autonomy; it is unwise and hasty to hand over the control initiative to the controller and the algorithm without the foundation of the maneuvering model. The berthing maneuver model predicts the ship responses to the steerage and external disturbances, and provides a foundation for the control algorithm. The modular MMG model is widely adopted in ship maneuverability studies. However, there are two ambiguous questions on berthing maneuver modeling: What are the similarities and differences between the conventional MMG maneuvering model and automatic berthing maneuvering model? How can an accurate automatic berthing maneuvering model be established? To answer these two questions, this paper firstly performs bibliometric analysis on automatic berthing, to discover the hot issues and emphasize the significance of maneuver modeling. It then demonstrates the similarities and differences between the conventional MMG maneuvering model and the automatic berthing maneuvering model. Furthermore, the berthing maneuver specifications and modeling procedures are explained in terms of the hydrodynamic forces on the hull, four-quadrant propulsion and steerage performances, external disturbances, and auxiliary devices. The conclusions of this work provide references for ship berthing mathematical modeling, auxiliary device utilization, berthing aid system improvement, and automatic berthing control studies.

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Section: Risk Assessment Perception Utilization and Motion Controlmentioning

confidence: 99%

State-of-the-Art Review and Future Perspectives on Maneuvering Modeling for Automatic Ship Berthing

Zhang,

Wu,

Liu

et al. 2023

JMSE

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show abstract

“…The vision-based positioning system utilizes a binocular camera to recognize the AprilTag code and employs the perspective-n-point (PNP) algorithm to measure and calculate the relative position between the active boat and the passive boat. 27,34 The flowchart of the vision-based positioning system is illustrated in Figure 7.…”

Section: Control Strategymentioning

confidence: 99%

Experimental study on autonomous docking and hook-locking control for unmanned surface vehicle platforms

Wu,

Gao,

Wang

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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The challenge in autonomous docking and hook locking of multiple unmanned surface navigation platforms is to design an appropriate autonomous docking controller and ensure that the electric control hook can iteratively dock with the passive vessel. The current docking control solution for unmanned surface platforms needs to design an automatic tracking–generated trajectory and visual guidance docking system, capable of detecting the connection status after the hook-lock action to ensure a successful connection. However, most of the docking control designs for unmanned surface platforms pay more attention to the first-time success rate but pay less attention to the failures caused by complex and intelligent docking devices or environmental interference during docking. This article proposes a control strategy for autonomous docking and hook locking of two unmanned surface platforms. It guides the active vessel to the side of the passive vessel under the task requirements and triggers the visual docking control algorithm to complete the mechanical connection of the two joints. This method employs an iterative detection mechanism to improve the automatic hook and lock capability of both the active and passive vessels. The indoor pool and outdoor lake experiments demonstrate that the proposed method can successfully perform automatic iterative docking and hook locking, even in the presence of wave disturbance, showcasing the effectiveness of the proposed method.

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A BlueROV2-based platform for underwater mapping experiments

Alinei-Poiană,

Reţe,

Martinovici

et al. 2024

IFAC-PapersOnLine

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Vision-based positioning of Unmanned Surface Vehicles using Fiducial Markers for automatic docking

Cited by 6 publications

References 7 publications

State-of-the-Art Review and Future Perspectives on Maneuvering Modeling for Automatic Ship Berthing

State-of-the-Art Review and Future Perspectives on Maneuvering Modeling for Automatic Ship Berthing

Experimental study on autonomous docking and hook-locking control for unmanned surface vehicle platforms

A BlueROV2-based platform for underwater mapping experiments

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