Analysis of movement for unmanned underwater vehicle using a low cost integrated sensor
This paper presents the development of low cost integrated Smart Sensor for Unmanned Underwater Vehicle (UUV) namely as underwater Remotely Operated Vehicle (ROV). In the underwater industries, the most crucial issues are the sensors that are needed for the underwater task. The sensors that are util...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/14552/1/1.4915770.pdf http://eprints.utem.edu.my/id/eprint/14552/ |
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| Summary: | This paper presents the development of low cost integrated Smart Sensor for Unmanned Underwater Vehicle
(UUV) namely as underwater Remotely Operated Vehicle (ROV). In the underwater industries, the most crucial issues
are the sensors that are needed for the underwater task. The sensors that are utilized in this area are quite expensive and sensitive. Every sensors used in the underwater vehicle are not in the form of integrated sensors and most of them based on case to case basis. However, nowadays, a lot of industries are involved in the development of the integrated sensor in order to reduce the production cost as well as to increase accuracies, efficiencies and productivities. Therefore, this
research proposes an integrated sensor to be applied in the underwater operations. The integrated sensor is designed
based on three goal performances which are; the accuracies; the sensitivities and the cost efficiencies. This integrated
sensor is the combination of pressure sensor, inertial measurement unit (IMU), digital compass and temperature sensor that are placed in a waterproof casing. This integrated sensor is targeted to be used to control the movement of ROV to maintain its position called station keeping. The purpose of the station keeping is to ensure the ROV to remain stationary at the desired depth by utilizing the pressure sensor. The experimental studies have been carried out in order to see the responses of each sensor. |
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