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Enhanced Precision Control of a 4-DOF Robotic Arm Using Numerical Code Recognition for Automated Object Handling

Journal of Robotics and Control (JRC) · Vol. 6 No. 1 (2025) · hlm. 315–335

DOI
10.18196/jrc.v6i1.24349
ISSN
2715-5072, 2715-5056
Terbit
2025-02-06
Penerbit
Universitas Muhammadiyah Yogyakarta
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

This research develops a 4-DOF robotic arm system that utilizes numerical codes for accurate, automated object handling, supporting advancements in sustainable industrial automation aligned with the UN Sustainable Development Goals (SDGs), particularly Industry, Innovation, and Infrastructure (SDG 9). Key contributions include the integration of EasyOCR for reliable code recognition and a control mechanism that enables precise positioning. The robotic system combines a webcam for visual sensing, servo motors for movement, and a gripper for object manipulation. EasyOCR effectively recognizes numerical codes on randomly positioned objects against a uniform background while the microcontroller calculates servo angles to guide the arm accurately to target positions. Testing results show a success rate exceeding 94% for detecting codes 1 to 4, with minor servo angle errors requiring adjustments in arm extension by 30 mm to 50 mm. Positional error analysis reveals an average error of less than 1.5 degrees. Although environmental factors like lighting can influence code visibility, this approach outperforms traditional methods in adaptability and precision. Future research will focus on enhancing code recognition under variable lighting and expanding the system's adaptability for diverse object types, broadening its applications in industries demanding high efficiency.

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  • Universitas Trunodjoyo Madura
  • INTI International University
  • State University of Semarang
  • University of Dhaka
  • Universiti Teknologi Brunei
  • Muhammadiyah University of Yogyakarta
  • Universitas Ahmad Dahlan
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Rekan penulisOrganisasiArtikel bersama
Muhammad FuadUniversitas Trunodjoyo Madura2
Hairil BudiartoUniversitas Trunodjoyo Madura2
Vivi TriwidyaningrumUniversitas Trunodjoyo Madura2
Sri HandayaniState University of Semarang1
Siti SetiatiAfiliasi tidak diketahui1
Muhammad Khifzhon AzwarAfiliasi tidak diketahui1
Fauzia KiranaAfiliasi tidak diketahui1
Malathy BatumalayINTI International University1
Suriayati ChupraAfiliasi tidak diketahui1
M. PriyadharshniAfiliasi tidak diketahui1
Grande Naga JyothiAfiliasi tidak diketahui1
V. VijayakumarAfiliasi tidak diketahui1
C. Srinivasa MurthyAfiliasi tidak diketahui1
Wahyu CaesarendraUniversiti Brunei Darussalam1
Alfian Ma’arifUniversitas Ahmad Dahlan1
Iswanto SuwarnoMuhammadiyah University of Yogyakarta1
Achmad UbaidillahUniversitas Trunodjoyo Madura1
Nuniek FahrianiUniversitas Muhammadiyah Gresik1
Sri Intan WahyuniState University of Semarang1
Ilham NurwahyudiUniversitas Trunodjoyo Madura1
Mochammad Ilham DarwamanUniversitas Trunodjoyo Madura1
Fahmi Agung MaulanaUniversitas Trunodjoyo Madura1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.umy.ac.id/index.php/jrc/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Enhanced Precision Control of a 4-DOF Robotic Arm Using Numerical Code Recognition for Automated Object Handling</dc:title>
	<dc:creator>Sukri, Hanifudin</dc:creator>
	<dc:creator>Ibadillah, Achmad Fiqhi</dc:creator>
	<dc:creator>Thinakaran, Rajermani</dc:creator>
	<dc:creator>Umam, Faikul</dc:creator>
	<dc:creator>Dafid, Ach.</dc:creator>
	<dc:creator>Kurniawan, Adi</dc:creator>
	<dc:creator>Morshed, Md. Monzur</dc:creator>
	<dc:creator>Kurniawan, Denni</dc:creator>
	<dc:subject xml:lang="en-US">Robotic Arm</dc:subject>
	<dc:subject xml:lang="en-US">4-DOF</dc:subject>
	<dc:subject xml:lang="en-US">Manufacturing Innovation</dc:subject>
	<dc:subject xml:lang="en-US">EasyOCR</dc:subject>
	<dc:subject xml:lang="en-US">Numerical Code</dc:subject>
	<dc:subject xml:lang="en-US">Precision Control</dc:subject>
	<dc:description xml:lang="en-US">This research develops a 4-DOF robotic arm system that utilizes numerical codes for accurate, automated object handling, supporting advancements in sustainable industrial automation aligned with the UN Sustainable Development Goals (SDGs), particularly Industry, Innovation, and Infrastructure (SDG 9). Key contributions include the integration of EasyOCR for reliable code recognition and a control mechanism that enables precise positioning. The robotic system combines a webcam for visual sensing, servo motors for movement, and a gripper for object manipulation. EasyOCR effectively recognizes numerical codes on randomly positioned objects against a uniform background while the microcontroller calculates servo angles to guide the arm accurately to target positions. Testing results show a success rate exceeding 94% for detecting codes 1 to 4, with minor servo angle errors requiring adjustments in arm extension by 30 mm to 50 mm. Positional error analysis reveals an average error of less than 1.5 degrees. Although environmental factors like lighting can influence code visibility, this approach outperforms traditional methods in adaptability and precision. Future research will focus on enhancing code recognition under variable lighting and expanding the system's adaptability for diverse object types, broadening its applications in industries demanding high efficiency.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Muhammadiyah Yogyakarta</dc:publisher>
	<dc:date>2025-02-06</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.umy.ac.id/index.php/jrc/article/view/24349</dc:identifier>
	<dc:identifier>10.18196/jrc.v6i1.24349</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Robotics and Control (JRC); Vol. 6 No. 1 (2025); 315-335</dc:source>
	<dc:source>2715-5072</dc:source>
	<dc:source>2715-5056</dc:source>
	<dc:source>10.18196/jrc.v6i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.umy.ac.id/index.php/jrc/article/view/24349/11290</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Hanifudin Sukri</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>