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Information Theory in Formation Control: An Error Analysis to Multi-Robot Formation
Multi-robot formation control makes prerequisites for a team of robots to execute complex tasks cooperatively, which has been widely applied in both civilian and military scenarios. However, the limited precision of sensors and controllers may inevitably cause position errors in the finally achieved...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513147/ https://www.ncbi.nlm.nih.gov/pubmed/33265707 http://dx.doi.org/10.3390/e20080618 |
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author | Wan, Shuo Lu, Jiaxun Fan, Pingyi Letaief, Khaled B. |
author_facet | Wan, Shuo Lu, Jiaxun Fan, Pingyi Letaief, Khaled B. |
author_sort | Wan, Shuo |
collection | PubMed |
description | Multi-robot formation control makes prerequisites for a team of robots to execute complex tasks cooperatively, which has been widely applied in both civilian and military scenarios. However, the limited precision of sensors and controllers may inevitably cause position errors in the finally achieved formation, which will affect the tasks undertaken. In this paper, the formation error is analyzed from the viewpoint of information theory. The desired position and the actually achieved position are viewed as two random variables. By calculating the mutual information between them, a lower bound of the formation error is derived. The results provide insights for the estimation of possible formation errors in the multi-robot system, which can assist designers to choose sensors and controllers with proper precision. |
format | Online Article Text |
id | pubmed-7513147 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75131472020-11-09 Information Theory in Formation Control: An Error Analysis to Multi-Robot Formation Wan, Shuo Lu, Jiaxun Fan, Pingyi Letaief, Khaled B. Entropy (Basel) Article Multi-robot formation control makes prerequisites for a team of robots to execute complex tasks cooperatively, which has been widely applied in both civilian and military scenarios. However, the limited precision of sensors and controllers may inevitably cause position errors in the finally achieved formation, which will affect the tasks undertaken. In this paper, the formation error is analyzed from the viewpoint of information theory. The desired position and the actually achieved position are viewed as two random variables. By calculating the mutual information between them, a lower bound of the formation error is derived. The results provide insights for the estimation of possible formation errors in the multi-robot system, which can assist designers to choose sensors and controllers with proper precision. MDPI 2018-08-20 /pmc/articles/PMC7513147/ /pubmed/33265707 http://dx.doi.org/10.3390/e20080618 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wan, Shuo Lu, Jiaxun Fan, Pingyi Letaief, Khaled B. Information Theory in Formation Control: An Error Analysis to Multi-Robot Formation |
title | Information Theory in Formation Control: An Error Analysis to Multi-Robot Formation |
title_full | Information Theory in Formation Control: An Error Analysis to Multi-Robot Formation |
title_fullStr | Information Theory in Formation Control: An Error Analysis to Multi-Robot Formation |
title_full_unstemmed | Information Theory in Formation Control: An Error Analysis to Multi-Robot Formation |
title_short | Information Theory in Formation Control: An Error Analysis to Multi-Robot Formation |
title_sort | information theory in formation control: an error analysis to multi-robot formation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513147/ https://www.ncbi.nlm.nih.gov/pubmed/33265707 http://dx.doi.org/10.3390/e20080618 |
work_keys_str_mv | AT wanshuo informationtheoryinformationcontrolanerroranalysistomultirobotformation AT lujiaxun informationtheoryinformationcontrolanerroranalysistomultirobotformation AT fanpingyi informationtheoryinformationcontrolanerroranalysistomultirobotformation AT letaiefkhaledb informationtheoryinformationcontrolanerroranalysistomultirobotformation |