Abstract

Indonesia, well known as a maritime country, has a very wide water territorial. Exploration carried out nowadays on average is limited to the sea surface while underwater exploration is still very rarely conducted. With technological advances in the marine and shipping fields, it is hoped that it can support the optimization of underwater surveys and exploration. The underwater surveys and explorations already conducted still used conventional methods, namely divers plunging directly into the water, then conduct surveys and explorations without the help of any tools. The obstacle that divers encountered with was the difficulty of the dive field resulting in an in optimal exploration. Not only did the underwater surveys require high technology, but also did the detection of drowning victims in reservoirs or lakes also requires diving equipment to find drowning victims. Given a certain depth, water pressure can endanger divers. The use of robotics in the shipping discipline is expected to assist in the detection of drowning victims. Robots commonly used to assist these explorations are underwater robots. ROV (Remotely Operated Vehicle) based water robots in developed countries have been used in underwater exploration. The ROV is considered more optimal in underwater exploration compared to the conventional methods. This paper is to apply the ROV motion estimation on the XY plane or on the water surface to help the SAR team find drowning victims. The estimation method used was the Unscented Kalman Filter method. The simulation results show that the UKF method could effectively estimate the position of the ROV on the water surface or the XY plane with an accuracy of about 98%.

Original languageEnglish
Title of host publication1st International Conference on Neuroscience and Learning Technology, ICONSATIN 2021
EditorsArika Indah Kristiana, Ridho Alfarisi
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735443006
DOIs
Publication statusPublished - 4 Jan 2023
Event1st International Conference on Neuroscience and Learning Technology, ICONSATIN 2021 - Jember, Indonesia
Duration: 18 Sept 202119 Sept 2021

Publication series

NameAIP Conference Proceedings
Volume2679
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference1st International Conference on Neuroscience and Learning Technology, ICONSATIN 2021
Country/TerritoryIndonesia
CityJember
Period18/09/2119/09/21

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