Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 1

Fast Obstacle Distance Estimation using Laser Line Imaging Technique for Smart Wheelchair

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 6 No. 4 (2016)

DOI
10.11591/ijece.v6i4.9798
ISSN
2088-8708, 2088-8708
Published
2016-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc-nd/4.0

Abstract

This paper presents an approach of obstacle distance estimation for smart wheelchair. A smart wheelchair was equipped with a camera and a laser line. The camera was used to capture an image from the environment in order to sense the pathway condition. The laser line was used in combination with camera to recognize an obstacle in the pathway based on the shape of laser line image in certain angle. A blob method detection was then applied on the laser line image to separate and recognize the pattern of the detected obstacles. The laser line projector and camera which was mounted in fixed-certain position ensured a fixed relation between blobs-gap and obstacle-to-wheelchair distance. A simple linear regression from 16 obtained data was used to respresent this relation as the estimated obstacle distance. As a result, the average error between the estimation and the actual distance was 1.25 cm from 7 data testing experiments. Therefore, the experiment results show that the proposed method was able to estimate the distance between wheelchair and the obstacle.

Collaboration network of the authors

40 authors · 110 co-authorship links · 19 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University of Brawijaya
  • Politeknik Negeri Malang
  • Institut Teknologi Sepuluh Nopember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Barlian Henryranu PrasetioUniversity of Brawijaya5
Agung Setia BudiUniversity of Brawijaya4
Eko SetiawanUniversity of Brawijaya4
Fitra Abdurrachman BachtiarUniversity of Brawijaya3
Edita Rosana WidasariUniversity of Brawijaya3
Eko SetiawanUniversity of Brawijaya3
Agus Zainal ArifinInstitut Teknologi Sepuluh Nopember2
Imam CholissodinUniversity of Brawijaya2
Rekyan Regasari Mardi PutriUniversity of Brawijaya2
Firnanda Al Islama Achyunda PutraUniversity of Brawijaya1
Wayan Firdaus MahmudyUniversity of Brawijaya1
Naser JawasInstitut Teknologi Sepuluh Nopember1
Dwi Taufik HidayatInstitut Teknologi Sepuluh Nopember1
IsnanAffiliation unknown1
Arief Andy SoebrotoUniversity of Brawijaya1
Maria Tenika FrestantiyaUniversity of Brawijaya1
Ziya El AriefUniversity of Brawijaya1
Ihwanudien Hasan RobbaniUniversity of Brawijaya1
Enny TrisnawatiUniversity of Brawijaya1
Rakhmadina NoviyantiUniversity of Brawijaya1
Afrizal RivaldiUniversity of Brawijaya1
Romario Yudo HerlambangUniversity of Brawijaya1
Waskitha WijayaUniversity of Brawijaya1
Herman TolleUniversity of Brawijaya1
Gembong Edhi SetyawanUniversity of Brawijaya1
Benny AdiwijayaUniversity of Brawijaya1
Widhy Hayuhardhika Nugraha PutraUniversity of Brawijaya1
Indrazno SiradjuddinPoliteknik Negeri Malang1
Ferdian RonilayaPoliteknik Negeri Malang1
Adhitya BhawiyugaUniversity of Brawijaya1
Budi Eko PrasetyoPoliteknik Negeri Malang1
Sigi Syah WibowoPoliteknik Negeri Malang1
Supriatna AdhisuwignjoPoliteknik Negeri Malang1
Yurdha Fadhila HernawanUniversity of Brawijaya1

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>Fast Obstacle Distance Estimation using Laser Line Imaging Technique for Smart Wheelchair</dc:title><dc:creator>Utaminingrum, Fitri</dc:creator><dc:creator>Fitriyah, Hurriyatul</dc:creator><dc:creator>Wihandika, Randy Cahya</dc:creator><dc:creator>Fauzi, M Ali</dc:creator><dc:creator>Syauqy, Dahnial</dc:creator><dc:creator>Maulana, Rizal</dc:creator><dc:description>&lt;jats:p&gt;This paper presents an approach of obstacle distance estimation for smart wheelchair. A smart wheelchair was equipped with a camera and a laser line. The camera was used to capture an image from the environment in order to sense the pathway condition. The laser line was used in combination with camera to recognize an obstacle in the pathway based on the shape of laser line image in certain angle. A blob method detection was then applied on the laser line image to separate and recognize the pattern of the detected obstacles. The laser line projector and camera which was mounted in fixed-certain position ensured a fixed relation between blobs-gap and obstacle-to-wheelchair distance. A simple linear regression from 16 obtained data was used to respresent this relation as the estimated obstacle distance. As a result, the average error between the estimation and the actual distance was 1.25 cm from 7 data testing experiments. Therefore, the experiment results show that the proposed method was able to estimate the distance between wheelchair and the obstacle.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2016-08-01</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.v6i4.9798</dc:identifier><dc:identifier>10.11591/ijece.v6i4.9798</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 6 No 4 (2016); 1602</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/728/650</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc-nd/4.0</dc:rights></oai_dc:dc>