A System for Autonomous Seaweed Farm Inspection with an Underwater Robot

Stenius, Ivan; Folkesson, John; Bhat, Sriharsha; Sprague, Christopher Iliffe; Ling, Li; Özkahraman, Özer; Bore, Nils; Zheng, Cong; Severholt, Josefine; Ljung, Carl; Arnwald, Anna; Torroba, Ignacio; Gröndahl, Fredrik; Thomas, Jean‐Baptiste

doi:10.3390/s22135064

Cited by 16 publications

(6 citation statements)

References 24 publications

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“…Chemisky conducts a review of the close-range optical methods for the underwater oil and gas industry [6]. Stenius presents the application of AUVs for seaweed farm inspection [7]. Underwater visual localization technology such as underwater visual SLAM is one of the key technologies for underwater inspection tasks.…”

Section: Introductionmentioning

confidence: 99%

An Underwater Localization Method Based on Visual SLAM for the Near-Bottom Environment

Liu,

Wang,

et al. 2024

JMSE

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The feature matching of the near-bottom visual SLAM is influenced by underwater raised sediments, resulting in tracking loss. In this paper, the novel visual SLAM system is proposed in the underwater raised sediments environment. The underwater images are firstly classified based on the color recognition method by adding the weights of pixel location to reduce the interference of similar colors on the seabed. The improved adaptive median filter method is proposed to filter the classified images by using the mean value of the filter window border as the discriminant condition to retain the original features of the image. The filtered images are finally processed by the tracking module to obtain the trajectory of underwater vehicles and the seafloor maps. The datasets of seamount areas captured in the western Pacific Ocean are processed by the improved visual SLAM system. The keyframes, mapping points, and feature point matching pairs extracted from the improved visual SLAM system are improved by 5.2%, 11.2%, and 4.5% compared with that of the ORB-SLAM3 system, respectively. The improved visual SLAM system has the advantage of robustness to dynamic disturbances, which is of practical application in underwater vehicles operated in near-bottom areas such as seamounts and nodules.

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Section: Introductionmentioning

confidence: 99%

An Underwater Localization Method Based on Visual SLAM for the Near-Bottom Environment

Liu,

Wang,

et al. 2024

JMSE

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“…Currently, intelligent inspection systems are being widely used so that inspections are faster, more effective, and safer as they do not require a human in risky environments, especially underwater inspections [2] [3] [4] [5] [6] [7] [8]. In order for the inspection to acquire good results, it is necessary, in addition to analyzing recognized patterns, to also check for unknown patterns, called anomalies.…”

Section: Introductionmentioning

confidence: 99%

Novelty detection in underwater inspection videos

Batista,

Caarls,

Mendonza

et al. 2024

Anais Do XVI Congresso Brasileiro De Inteligência Computacional

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This work consists of a study on the detection of anomalies in underwater inspection videos. Novelty detection is the identification of new or distinct data from a dataset, where the challenge is for an intelligent algorithm to be able to detect an input pattern as being previously unknown. Then, different models with different configurations were chosen, trained using different video frames and analyzed in order to find the best pattern detection model. The objective of this work is to contribute to the automatic detection of anomalies, which is currently a task carried out by specialists who analyze these videos. The model shows promise compared to other similar works in the area.

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“…The acoustic sensor (also called a transducer) is the main component of the sonar system used to perform sound transmission and receival. In the design of such sensors, due to the complexity of the application environment, theoretical calculations cannot guarantee satisfactory performance, while field experiments are also difficult to carry out in the early stage of development [ 2 ]. For the purpose of design verification, in addition to the accumulation of practical experiences, researchers usually have to resort to certain analysis tools, e.g., a sonar simulator.…”

Section: Introductionmentioning

confidence: 99%

A High–Efficiency Side–Scan Sonar Simulator for High–Speed Seabed Mapping

Meng

Shen

et al. 2023

Sensors

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Side scan sonar (SSS) is a multi–purpose ocean sensing technology, but due to the complex engineering and variable underwater environment, its research process often faces many uncertain obstacles. A sonar simulator can provide reasonable research conditions for guiding development and fault diagnosis, by simulating the underwater acoustic propagation and sonar principle to restore the actual experimental scenarios. However, the current open–source sonar simulators gradually lag behind mainstream sonar technology; therefore, they cannot be of sufficient assistance, especially due to their low computational efficiency and unsuitable high–speed mapping simulation. This paper presents a sonar simulator based on a two–level network architecture, which has a flexible task scheduling system and extensible data interaction organization. The echo signal fitting algorithm proposes a polyline path model to accurately capture the propagation delay of the backscattered signal under high–speed motion deviation. The large–scale virtual seabed is the operational nemesis of the conventional sonar simulators; therefore, a modeling simplification algorithm based on a new energy function is developed to optimize the simulator efficiency. This paper arranges several seabed models to test the above simulation algorithms, and finally compares the actual experiment results to prove the application value of this sonar simulator.

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A System for Autonomous Seaweed Farm Inspection with an Underwater Robot

Cited by 16 publications

References 24 publications

An Underwater Localization Method Based on Visual SLAM for the Near-Bottom Environment

An Underwater Localization Method Based on Visual SLAM for the Near-Bottom Environment

Novelty detection in underwater inspection videos

A High–Efficiency Side–Scan Sonar Simulator for High–Speed Seabed Mapping

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