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Dynamic Path Planning for Mobile Robots with Cellular Learning Automata

Journal of ICT Research and Applications (JICTRA) · Vol. 10 No. 1 (2016) · pp. 1–14

DOI
10.5614/itbj.ict.res.appl.2016.10.1.1
ISSN
2338-5499, 2337-5787
Published
2016-04-30
Publisher
DRI - ITB
Language
eng

Abstract

In this paper we propose a new approach to path planning for mobile robots with cellular automata and cellular learning automata. We divide the planning into two stages. In the first stage, global path planning is performed by cellular automata from an initial position to a goal position. In this stage, the minimum distance is computed. To compute the path, we use a particular two-dimensional cellular automata rule. The process of computation is performed using simple arithmetic operations, hence it can be done efficiently. In the second stage, local planning is used to update the global path. This stage is required to adapt to changes in a dynamic environment. This planning is implemented using cellular learning automata to optimize performance by collecting information from the environment. This approach yields a path that stays near to the obstacles and therefore the total time and distance to the goal can be optimized.

Collaboration network of the authors

6 authors · 9 co-authorship links

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  • Bandung Institute of Technology
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
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Co-authorOrganisationJoint articles
Rinaldi MunirBandung Institute of Technology2
Sarwono SutiknoBandung Institute of Technology2
Wiseto Prasetyo AgungAffiliation unknown2

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jictra/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Dynamic Path Planning for Mobile Robots with Cellular Learning Automata</dc:title>
	<dc:creator>Santoso, Judhi</dc:creator>
	<dc:creator>Riyanto, Bambang</dc:creator>
	<dc:creator>Adiprawita, Widyawardhana</dc:creator>
	<dc:description xml:lang="en-US">In this paper we propose a new approach to path planning for mobile robots with cellular automata and cellular learning automata. We divide the planning into two stages. In the first stage, global path planning is performed by cellular automata from an initial position to a goal position. In this stage, the minimum distance is computed. To compute the path, we use a particular two-dimensional cellular automata rule. The process of computation is performed using simple arithmetic operations, hence it can be done efficiently. In the second stage, local planning is used to update the global path. This stage is required to adapt to changes in a dynamic environment. This planning is implemented using cellular learning automata to optimize performance by collecting information from the environment. This approach yields a path that stays near to the obstacles and therefore the total time and distance to the goal can be optimized.</dc:description>
	<dc:publisher xml:lang="en-US">DRI - ITB</dc:publisher>
	<dc:date>2016-04-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/jictra/article/view/1556</dc:identifier>
	<dc:identifier>10.5614/itbj.ict.res.appl.2016.10.1.1</dc:identifier>
	<dc:source xml:lang="en-US">Journal of ICT Research and Applications; Vol. 10 No. 1 (2016); 1-14</dc:source>
	<dc:source>2338-5499</dc:source>
	<dc:source>2337-5787</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jictra/article/view/1556/1181</dc:relation>
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