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Path Planning Based on Fuzzy Decision Trees and Potential Field

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 6 No. 1 (2016)

DOI
10.11591/ijece.v6i1.8606
ISSN
2088-8708, 2088-8708
Published
2016-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc-nd/4.0

Abstract

The fuzzy logic algorithm is an artificial intelligence algorithm that uses mathematical logic to solve to by the data value inputs which are not precise in order to reach an accurate conclusion. In this work, Fuzzy decision tree (FDT) has been designed to solve the path planning problem by considering all available information and make the most appropriate decision given by the inputs. The FDT is often used to make a path planning decision in graph theory. It has been applied in the previous researches in the field of robotics, but it still shows drawbacks in that the robot will stop at the local minima and is not able to find the shortest path. Hence, this paper combines the FDT algorithm with the potential field algorithm. The potential field algorithm provides weight to the FDT algorithm which enables the robot to successfully avoid the local minima and find the shortest path.

Collaboration network of the authors

23 authors · 53 co-authorship links · 4 across different organisations

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  • Universitas Gadjah Mada
  • Muhammadiyah University of Yogyakarta
  • Muhammadiyah University of Surakarta
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Hari MaghfirohAffiliation unknown4
Kuo Lung LianAffiliation unknown4
Bwo Ren KeAffiliation unknown4
Teguh Bharata AdjiUniversitas Gadjah Mada4
Hendri Himawan TriharmintoUniversitas Gadjah Mada4
Igi ArdiyantoUniversitas Gadjah Mada4
Tatiya Padang TunggalMuhammadiyah University of Yogyakarta2
Andi SupriyantoMuhammadiyah University of Yogyakarta2
Nur Mukhammad Zaidatur RochmanMuhammadiyah University of Yogyakarta2
Ibnu FaishalMuhammadiyah University of Yogyakarta2
Imam PambudiMuhammadiyah University of Yogyakarta2
Adhi SusantoUniversitas Gadjah Mada2
Muhammad KusbanMuhammadiyah University of Surakarta2
Almido Haryanto GintingUniversitas Gadjah Mada2
Anna Nur Nazilah ChamimMuhammadiyah University of Yogyakarta1
Muhammad Heru GustamanMuhammadiyah University of Yogyakarta1
Nia Maharani RaharjaMuhammadiyah University of Yogyakarta1
Lasmadi LasmadiUniversitas Gadjah Mada1
Risanuri HidayatUniversitas Gadjah Mada1
Samiadji HerdjunantoUniversitas Gadjah Mada1

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.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Path Planning Based on Fuzzy Decision Trees and Potential Field</dc:title><dc:creator>Iswanto, Iswanto</dc:creator><dc:creator>Wahyunggoro, Oyas</dc:creator><dc:creator>Imam Cahyadi, Adha</dc:creator><dc:description>&lt;jats:p&gt;The fuzzy logic algorithm is an artificial intelligence algorithm that uses mathematical logic to solve to by the data value inputs which are not precise in order to reach an accurate conclusion. In this work, Fuzzy decision tree (FDT) has been designed to solve the path planning problem by considering all available information and make the most appropriate decision given by the inputs. The FDT is often used to make a path planning decision in graph theory. It has been applied in the previous researches in the field of robotics, but it still shows drawbacks in that the robot will stop at the local minima and is not able to find the shortest path. Hence, this paper combines the FDT algorithm with the potential field algorithm. The potential field algorithm provides weight to the FDT algorithm which enables the robot to successfully avoid the local minima and find the shortest path.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2016-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v6i1.8606</dc:identifier><dc:identifier>10.11591/ijece.v6i1.8606</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 6 No 1 (2016); 212</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://www.iaescore.com/journals/index.php/IJECE/article/viewFile/98/114</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc-nd/4.0</dc:rights></oai_dc:dc>