@inproceedings{8cebd6bda554422b85322b1b7824b60c,
title = "Estimate and control position autonomous Underwater Vehicle based on determined trajectory using Fuzzy Kalman Filter method",
abstract = "Unmanned Underwater Vehicle (UUV), known as underwater drones, are any vehicle that are able to operate underwater without human occupant. AUV (Autonomous Underwater Vehicle) are one of categories of these vehicles which operate independently of direct human input. This AUV is required to have a navigation system that can manoeuvred 6 Degree of Freedom (DOF) and able to estimate the exact position based on the determined trajectory. Fuzzy Kalman Filter (FKF) method is used to estimate the position of the AUV. This process is used to maintain the accuracy of the trajectory. The performance of FKF algorithm on some several trajectory cases show that this method has relatively small Root Means Square Error (RSME), which is less than 10%.",
keywords = "AUV, Fuzzy Kalman Filter, estimation",
author = "Zunif Ermayanti and Erna Apriliani and Hendro Nurhadi and Teguh Herlambang",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, ICAMIMIA 2015 ; Conference date: 15-10-2015 Through 16-10-2015",
year = "2016",
month = jul,
day = "8",
doi = "10.1109/ICAMIMIA.2015.7508022",
language = "English",
series = "ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "156--161",
booktitle = "ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE",
address = "United States",
}