Docking to an underwater suspended charging station: Systematic design and experimental tests

Lin, Mingwei; Lin, Ri; Yang, Canjun; Li, Dejun; Zhang, Zhuoyu; Zhao, Yanqi; Ding, Wangjie

doi:10.1016/j.oceaneng.2022.110766

Cited by 36 publications

(10 citation statements)

References 30 publications

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“…At this point, the absolute position is determined using the triangle code recognition and positioning algorithm introduced in this subsection. This approach draws inspiration from (Lin et al , 2022a), where the data received from the positioning system are processed using a sliding window algorithm. Specifically, the algorithm calculates the average of the positioning data over every five frames.…”

Section: Methodsmentioning

confidence: 99%

Triangle codes and tracer lights based absolute positioning method for terminal visual docking of autonomous underwater vehicles

Zhang,

Zhong,

Lin

et al. 2024

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Purpose Docking technology plays a crucial role in enabling long-duration operations of autonomous underwater vehicles (AUVs). Visual positioning solutions alone are susceptible to abnormal drift values due to the challenging underwater optical imaging environment. When an AUV approaches the docking station, the absolute positioning method fails if the AUV captures an insufficient number of tracers. This study aims to to provide a more stable absolute position visual positioning method for underwater terminal visual docking. Design/methodology/approach This paper presents a six-degree-of-freedom positioning method for AUV terminal visual docking, which uses lights and triangle codes. The authors use an extended Kalman filter to fuse the visual calculation results with inertial measurement unit data. Moreover, this paper proposes a triangle code recognition and positioning algorithm. Findings The authors conducted a simulation experiment to compare the underwater positioning performance of triangle codes, AprilTag and Aruco. The results demonstrate that the implemented triangular code reduces the running time by over 70% compared to the other two codes, and also exhibits a longer recognition distance in turbid environments. Subsequent experiments were carried out in Qingjiang Lake, Hubei Province, China, which further confirmed the effectiveness of the proposed positioning algorithm. Originality/value This fusion approach effectively mitigates abnormal drift errors stemming from visual positioning and cumulative errors resulting from inertial navigation. The authors also propose a triangle code recognition and positioning algorithm as a supplementary approach to overcome the limitations of tracer light positioning beacons.

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Section: Methodsmentioning

confidence: 99%

Triangle codes and tracer lights based absolute positioning method for terminal visual docking of autonomous underwater vehicles

Zhang,

Zhong,

Lin

et al. 2024

Self Cite

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“…Experimental results show a 33.3% increase in terminal location accuracy over visual ranging. In 2022, they [12] employed a 94W white SLS-5200 underwater lamp, combined with a LOS guidance scheme, to accomplish docking guidance in a lake at distances of 20-30 m. Amjad [13] employed lock-in detection to mitigate the impact of turbidity while suppressing stray light and noise. This method locks onto the blinking frequencies of two fixed-frequency emitting beacons located at the docking station, eliminating the influence of unwanted light at other frequencies.…”

Section: Led Beaconsmentioning

confidence: 99%

Review of underwater visual navigation and docking: advances and challenges

Li,

Sun

2024

Sixth Conference on Frontiers in Optical Imaging and Technology: Imaging Detection and Target Recognition

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The widespread utilization of autonomous underwater vehicles in marine science and engineering has underscored the paramount importance of precise underwater navigation and docking capabilities for underwater robots. Underwater vision navigation systems serve as a pivotal technology, encompassing various domains such as computer vision, image processing, and machine learning. Nevertheless, they confront a series of challenges. This review aims to consolidate the most recent research advancements in underwater vision navigation systems, with a particular focus on critical aspects such as beacon design, monocular and binocular vision, and detection algorithms. At present, underwater beacons can be categorized into active and passive types, with the flexibility to choose between them contingent upon the specific task and environment. On the other hand, relative to the prevalent use of monocular vision, binocular vision systems offer the potential to furnish more accurate depth information, and the seamless integration of monocular and binocular vision systems enhances the precision and stability of navigation tasks. Concerning detection algorithms, traditional feature extraction methods and deep learning approaches each exhibit their merits and drawbacks, but deep learning methods demonstrate immense potential in complex underwater environments. By summarizing and analyzing the above research results, the application of each key technology of underwater vision navigation and docking is sorted out, and its further development direction is foreseen.

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“…Optical cameras are more affordable than acoustic sensors like sonars and can provide detailed information in the highly transparent sea. They are used for AUVs required to operate with high precision near the seafloor or structures, including intervention or docking to charging stations (Lin et al, 2022; Maki, Sato, et al, 2018; Nishida et al, 2019).…”

Section: Related Workmentioning

confidence: 99%

“…In this research, a long‐range capable AUV and satellite communication are utilized to successfully accomplish extended missions without the need for close human supervision or support. There is ongoing research to develop underwater charging station systems that enable the recharging of AUVs without the need for retrieving them to the water surface (Hasaba et al, 2023; Lin et al, 2022). By deploying these systems on the seafloor or attaching them to autonomous surface vehicles (ASVs), long‐term operational capabilities for AUVs can be achieved.…”

Section: Introductionmentioning

confidence: 99%

Guidance method of underwater vehicle for rugged seafloor observation in close proximity

Noguchi,

Sekimori,

Maki

2023

Journal of Field Robotics

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Obtaining detailed information about the ocean through seafloor optical imaging is crucial, yet poses significant challenges due to the high attenuation of light, which necessitates the camera to be positioned within several meters of the seafloor. This paper proposes a method for an autonomous underwater vehicle (AUV) to track the seafloor at a close range suitable for optical survey. Through the probabilistic processing of measurements from a mechanical scanning imaging sonar, the AUV can safely follow the seafloor, even in the presence of large obstacles or overhanging geometries. The method was implemented on the low‐cost AUV, HATTORI, and its effectiveness was confirmed by sea experiments around Nishinoshima island, an uninhabited volcanic island located about 1000 km south of Tokyo, Japan. Detailed images of the rugged seafloor were successfully captured under the challenging condition of strong currents.

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Docking to an underwater suspended charging station: Systematic design and experimental tests

Cited by 36 publications

References 30 publications

Triangle codes and tracer lights based absolute positioning method for terminal visual docking of autonomous underwater vehicles

Triangle codes and tracer lights based absolute positioning method for terminal visual docking of autonomous underwater vehicles

Review of underwater visual navigation and docking: advances and challenges

Guidance method of underwater vehicle for rugged seafloor observation in close proximity

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