Manipulation of a Complex Object Using Dual-Arm Robot with Mask R-CNN and Grasping Strategy

Manipulation of a Complex Object Using Dual-Arm Robot with Mask R-CNN and Grasping Strategy

Hot forging is one of the common manufacturing processes for producing brass workpieces. However forging produces flash which is a thin metal part around the desired part formed with an excessive material. Using robots with vision system to manipulate this workpiece has encountered several challengi...

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Bibliographic Details
Published in:Journal of intelligent & robotic systems Vol. 110; no. 3; p. 103
Main Authors: Kijdech, Dumrongsak, Vongbunyong, Supachai
Format: Journal Article
Language:English
Published: Dordrecht Springer Netherlands 10-07-2024
Springer Nature B.V
Subjects:
Artificial Intelligence
Artificial neural networks
Color imagery
Control
Electrical Engineering
Engineering
Grasping (robotics)
Hot forging
Image manipulation
Image processing
Machine learning
Mechanical Engineering
Mechatronics
Neural networks
Regular Paper
Robotics
Robots
Strategy
Vision systems
Workpieces
RGB-D
AI
YuMi
Image processing
Mask R-CNN
Online Access:Get full text
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Description
Summary:Hot forging is one of the common manufacturing processes for producing brass workpieces. However forging produces flash which is a thin metal part around the desired part formed with an excessive material. Using robots with vision system to manipulate this workpiece has encountered several challenging issues, e.g. the uncertain shape of flash, color, reflection of brass surface, different lighting condition, and the uncertainty surrounding the position and orientation of the workpiece. In this research, Mask region-based convolutional neural network together with image processing is used to resolve these issues. The depth camera can provide images for visual detection. Machine learning Mask region-based convolutional neural network model was trained with color images and the position of the object is determined by the depth image. A dual arm 7 degree of freedom collaborative robot with proposed grasping strategy is used to grasp the workpiece that can be in inappropriate position and pose. Eventually, experiments were conducted to assess the visual detection process and the grasp planning of the robot.
ISSN:1573-0409
0921-0296
1573-0409
DOI:10.1007/s10846-024-02132-0