Automated picking-sorting system for assembling components in an IKEA chair based on the robotic vision system

Yang, Ruizhi; Nguyen, Thong; Park, Sung Hyuk; Yoon, Jonghun

doi:10.1080/0951192x.2021.1992658

Cited by 8 publications

(4 citation statements)

References 29 publications

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“…The system was implemented based on the robot operating system (ROS) and Python. Yang et al [7] use the UR5 robot arm and intel RealSense D435 camera with YOLOv3 to detect objects and grasp them. YOLO was great for recognizing and localizing the objects in the image.…”

Section: Literature Review 21 Review Robot With Vision Systemmentioning

confidence: 99%

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Pick-and-place application using a dual arm collaborative robot and an RGB-D camera with YOLOv5

Kijdech

Vongbunyong²

2023

IJRA

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Nowadays, many industries use robots and cameras in tandem to detect specific objects and perform specific tasks. However, misdetection can occur due to inconsistencies in lighting, background, and environment. In order to address the aforementioned issues, this study proposes using a dual arm six-degree-of-freedom (6-DoF) collaborative robot, ABB YuMi, and red, green, blue-depth (RGB-D) camera with YOLOv5 in a pick-and-place application. In order to prepare the dataset, the images are collected and labeled. The dataset has been trained with the YOLOv5 machine learning algorithm. It has taken on the role of weight for real-time detection. When RGB images from a camera are sent to YOLOv5, data pertaining to the bottle’s position x-y and color are extracted from the depth and color images. The position of the robot is used to control its movement. There are three parts to the experiment. To begin, YOLOv5 is tested with and without trained images. Second, YOLOv5 is tested with real-time camera images. Finally, we assume that YOLOv5 has perfect detection and grasping ability. The results were 95, 90, and 90%.

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Section: Literature Review 21 Review Robot With Vision Systemmentioning

confidence: 99%

“…(1) After that, (1), (2), and (4) would be represented in (5). Eventually, the position of the object in the robot coordinate can be obtained from ( 6) to (7).…”

Section: Coordinate Systemmentioning

confidence: 99%

Pick-and-place application using a dual arm collaborative robot and an RGB-D camera with YOLOv5

Kijdech

Vongbunyong²

2023

IJRA

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“…Due to the safety issue, collaborative robots are suitable for applications that work alongside with human operators. Wu and Hong [4] and Yang et al [5] used robots with YOLO on ROS with Python for detecting objects. Yang et al [5] used the UR5 robot arm and intel RealSense D435 camera with YOLOv3 to detect object and grasp.…”

Section: Review Robot With Vision Systemmentioning

confidence: 99%

“…Wu and Hong [4] and Yang et al [5] used robots with YOLO on ROS with Python for detecting objects. Yang et al [5] used the UR5 robot arm and intel RealSense D435 camera with YOLOv3 to detect object and grasp. YOLO was great for recognising and localising the objects when training with augmented images with various object orientation.…”

Section: Review Robot With Vision Systemmentioning

confidence: 99%

Using Yumi Robot and RGB-D Camera With Yolov5 for Pick-and-Place Application, 1-10.

Kijdech,

Vongbunyong

2023

International Journal of Robotics and Automation

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Nowadays, in many industries, robots and cameras are used together to detect certain objects and perform specific tasks. However, misdetection can be occurred due to uncertainty of lighting condition, background, and environment. Using a dual arm 7-DOF collaborative robot and RGB-D camera with YOLOv5 in pickand-place application is proposed in this research to resolve the aforementioned problems. The images are collected and labelled in preparation of the dataset. The dataset is trained with the machine learning algorithm, YOLOv5. It became weight for realtime detection. When RGB images from the camera are sent to YOLOv5, data in regard to position x -y and colour of the bottle is extracted from the depth and the colour images. The experiments were done to assess the performance of YOLO and the grasping capability of the robot.

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Review of current vision-based robotic machine-tending applications

Jia,

Ma,

Ahmad

2024

Int J Adv Manuf Technol

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Automated picking-sorting system for assembling components in an IKEA chair based on the robotic vision system

Cited by 8 publications

References 29 publications

Pick-and-place application using a dual arm collaborative robot and an RGB-D camera with YOLOv5

Pick-and-place application using a dual arm collaborative robot and an RGB-D camera with YOLOv5

Using Yumi Robot and RGB-D Camera With Yolov5 for Pick-and-Place Application, 1-10.

Review of current vision-based robotic machine-tending applications

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