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Open access Jurnal SINTA 3

THE DESIGN OF PEOPLE FOLLOWER ROBOT TO TRANSPORT HARVESTS USING YOLO V5 DETECTION

SemanTIK: Teknik Informasi · Vol. 9 No. 2 (2023) · pp. 173–180

DOI
10.55679/semantik.v9i2.45261
ISSN
2502-8928, 2460-1446
Published
2023-12-26
Publisher
Informatics Engineering Department of Halu Oleo University
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Robots transporting harvested products is commonly use automatic navigation systems with sensors such as lidar, cameras and ultrasonic proximity sensors are important for detecting obstacles and avoiding collisions. Mapping and positioning algorithm are crucial for precise the robot determine position in the field. A dependable drive system, adaptable to diverse terrains, and a robust motor are essential components. Efficient energy requirements must be addressed by using long-lasting battery systems and, where possible, automatic charging solutions. Robots picking mechanisms that can adapt to different types of plants, as well as storage systems that protect vegetables from damage during transport, also need to be considered. This writing utilizes does not huge robot harvest hardware as a prototype due to research scope limitations. Instead, it involves instructing a Jetson Nano and Arduino Uno to direct the camera towards the tracked object using coding through python and Arduino IDE. Computer mini used Jetson Nano for running the best model object tracking. Output serial connected with Arduino for control actuator like motor DC and servo motor. The method used is YOLOv5, while the image processing technique employs object detection, which likely serves for object identification and localization. The additional computer vision facilitates the camera to adapt to the objects. Through testing, the system successfully detects objects, particularly vest, with an average confidence value of 0.91%, indicating that the detection system has a very high level of accuracy in identifying and detecting vest. Keywords; Robot, Jetson nano, Arduino Uno, Object Detection, Yolov5

Keywords

Collaboration network of the authors

11 authors · 39 co-authorship links · 14 across different organisations

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

  • Politeknik Pertanian Negeri Samarinda
  • Mulawarman University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
⁠⁠Eny MariaPoliteknik Pertanian Negeri Samarinda1
Bagus SatriaPoliteknik Pertanian Negeri Samarinda1
Reza AndreaMulawarman University1
Syafei KarimPoliteknik Pertanian Negeri Samarinda1
Fajar RamadhaniPoliteknik Pertanian Negeri Samarinda1
Suswanto SuswantoPoliteknik Pertanian Negeri Samarinda1
Emil Riza PutraPoliteknik Pertanian Negeri Samarinda1
Hasbi SjamsirMulawarman University1

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://ojs.uho.ac.id/index.php/semantik/oai, first harvested 29 Okt 2026, last seen 29 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">THE DESIGN OF PEOPLE FOLLOWER ROBOT TO TRANSPORT HARVESTS USING YOLO V5 DETECTION</dc:title>
	<dc:creator>Imron, Imron</dc:creator>
	<dc:creator>Satria, Bagus</dc:creator>
	<dc:creator>Nuraini, Nuraini</dc:creator>
	<dc:subject xml:lang="en-US">Software Engineering; Robotics</dc:subject>
	<dc:description xml:lang="en-US">Robots transporting harvested products is commonly use automatic navigation systems with sensors such as lidar, cameras and ultrasonic proximity sensors are important for detecting obstacles and avoiding collisions. Mapping and positioning algorithm are crucial for precise the robot determine position in the field. A dependable drive system, adaptable to diverse terrains, and a robust motor are essential components. Efficient energy requirements must be addressed by using long-lasting battery systems and, where possible, automatic charging solutions. Robots picking mechanisms that can adapt to different types of plants, as well as storage systems that protect vegetables from damage during transport, also need to be considered. This writing utilizes does not huge robot harvest hardware as a prototype due to research scope limitations. Instead, it involves instructing a Jetson Nano and Arduino Uno to direct the camera towards the tracked object using coding through python and Arduino IDE. Computer mini used Jetson Nano for running the best model object tracking. Output serial connected with Arduino for control actuator like motor DC and servo motor. The method used is YOLOv5, while the image processing technique employs object detection, which likely serves for object identification and localization. The additional computer vision facilitates the camera to adapt to the objects. Through testing, the system successfully detects objects, particularly vest, with an average confidence value of 0.91%, indicating that the detection system has a very high level of accuracy in identifying and detecting vest.

Keywords; Robot, Jetson nano, Arduino Uno, Object Detection, Yolov5</dc:description>
	<dc:publisher xml:lang="en-US">Informatics Engineering Department of Halu Oleo University</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2023-12-26</dc:date>
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	<dc:identifier>https://ojs.uho.ac.id/index.php/semantik/article/view/45261</dc:identifier>
	<dc:identifier>10.55679/semantik.v9i2.45261</dc:identifier>
	<dc:source xml:lang="en-US">SemanTIK : Teknik Informasi; Vol 9, No 2 (2023): SemanTIK : Teknik Informasi; 173-180</dc:source>
	<dc:source>2502-8928</dc:source>
	<dc:source>2460-1446</dc:source>
	<dc:source>10.55679/semantik.v9i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs.uho.ac.id/index.php/semantik/article/view/45261/pdf</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 semanTIK : Teknik Informasi</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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