Towards automatic hole detection of a net for fish farms by means of robotic intelligence
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Inclou dades d'ús des de 2022
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hdl:2117/391368
Tipus de documentArticle
Data publicació2023
EditorSARTI
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 4.0 Internacional
Abstract
In the last decades fish farms became one of the most important sources of seafood. This industry is facing complex and costly problems like net holes, especially due to unexpected situations, such as depredators and storm effects. This is a complex problem because fishes can escape from the fish farms containers or a depredator can enter in the container. To solve this problem divers are needed, but this solution is difficult and sometimes can be dangerous for the diver. The main objective of this work is to present the current state of a system where an underwater robot can detect holes in the net of a fish farm. Once the robot detects the hole it will proceed to manipulate it. This task is bordered using convolutional neural networks and the BlueROV2 platform with the Newton Gripper from BlueRobotics, which will be upgraded in a second stage to perform preliminary net repairs. This work contributes in the area of aquaculture, computer vision, underwater inspection and manipulation.
CitacióLópez Barajas, S. [et al.]. Towards automatic hole detection of a net for fish farms by means of robotic intelligence. 10th International Workshop on Marine Technology (MARTECH 2023)". ""Instrumentation viewpoint", 2023, núm. 22, p. 76.
Dipòsit legalB-32814-2006
ISSN1886-4864
Col·leccions
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ID40.pdf | Article | 1,713Mb | Visualitza/Obre |