@inproceedings{75eb9a953d4947679b3bcb228f8aef04,
title = "Formation Control of Multi-robot Motion Systems and State Estimation using Extended Kalman Filter",
abstract = "The multi-robot motion system is a dynamical system from a group of robots which moved in an unknown environment. Multi-robot is the development of a single robot that can overcome cooperative motion by utilizing information from its neighbours. We consider the formation of controls imposed on the observed multi-robot motion system. Robots that have different starting points will then be controlled to a meeting point (rendezvous), then controlled to move in a formation at a specified speed. The movements trajectory of these robots observed will be estimated using the Extended Kalman filter method. The purpose of this estimation is to observe the movement of robots when we have minimum measurement data. This method is one example of a data assimilation method which is combining model system and measurement system to get better approximation. The results of the tracking estimation are very good with very small error.",
keywords = "Kalman filter, formation control, multi-robot",
author = "Prima Aditya and Erna Apriliani and Guisheng Zhai and Arif, {Didik Khusnul}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 7th International Conference on Electrical Engineering and Informatics, ICEEI 2019 ; Conference date: 09-07-2019 Through 10-07-2019",
year = "2019",
month = jul,
doi = "10.1109/ICEEI47359.2019.8988841",
language = "English",
series = "Proceedings of the International Conference on Electrical Engineering and Informatics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "99--104",
booktitle = "Proceeding of 2019 International Conference on Electrical Engineering and Informatics, ICEEI 2019",
}