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27 June 2023 Robot arm gripping pose estimation algorithm based on binocular camera
Jiao Zhao, Wanyi Ge, Zhe Xu, Shuxu Jing
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Proceedings Volume 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022); 127050D (2023) https://doi.org/10.1117/12.2680144
Event: Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 2022, Nanjing, China
Abstract
The robot can work stably and reliably on the assembly line with fixed position. However, when the position of the robot is not fixed and the pose of the working object is unknown, the robot needs to obtain the pose of the working object and the relative position relationship between the robot and the working object to grasp the target. Aiming at the above problems, this paper designs a pose estimation method for the manipulator to grasp the target. Firstly, the backbone network ResNet50 is replaced by a lightweight, efficient and less computationally intensive MobileNet network to improve the Mask R-CNN network. Secondly, the improved neural network was trained by transfer learning based on image acquisition and COCO dataset. Finally, the pose estimation method of binocular data source based on line features is designed to obtain the pose information of grasping objects. Experimental results show that the operating speed of MobileNet Mask R-CNN network is faster than Mask R-CNN network, and the speed of target recognition is also increased by about 4%. At the same time, high precision pose information can be obtained, and it has high efficiency and robustness.
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Citation Download Citation
Jiao Zhao, Wanyi Ge, Zhe Xu, and Shuxu Jing "Robot arm gripping pose estimation algorithm based on binocular camera", Proc. SPIE 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 127050D (27 June 2023); https://doi.org/10.1117/12.2680144
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KEYWORDS
Convolution
Education and training
Cameras
Image segmentation
Pose estimation
Target recognition
Detection and tracking algorithms
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