CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Image Segmentation of Cabin Assembly Scene Based on Improved RGB-D Mask R-CNN
Fu, Yichen1,2; Fan, Junfeng1,2; Xing, Shiyu1,2; Wang, Zhe1,2; Jing, Fengshui1,2; Tan, Min1,2
Source PublicationIEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
ISSN0018-9456
2022
Volume71Pages:12
Corresponding AuthorJing, Fengshui(fengshui.jing@ia.ac.cn)
AbstractCabin pose measurement is one of the key procedures in the assembly and docking process of large cabins, which provides important feedback information for the subsequent docking control system. As the basis of cabin pose measurement, the accuracy and robustness of cabin assembly image segmentation are particularly important. However, traditional image segmentation method based on RGB sensor is extremely susceptible to interference from the external environment, which greatly weakens the recognition effect. In this article, an image segmentation method of cabin assembly scene based on improved red-green-blue-depth (RGB-D) Mask R-CNN is proposed, and its network structure is designed to be able to specifically process four-channel images. The method can accurately extract the corresponding area of the cabin under complex and severe environmental disturbances, with high robustness and generalization capability. Meanwhile, the excellence of deep learning segmentation algorithms with depth channel information input is highlighted. In experiments, improved classic segmentation network U-Net, SegNet, pyramid scene parsing network (PSPNet), and Deeplab-v3 based on RGB-D were constructed as control, and these models were tested and evaluated on the enhanced test sets to verify their segmentation accuracy and robustness performance. Comparing experiments fully demonstrate the superiority of the segmentation network model of RGB-D four-channel input over RGB input. At the same time, vision system using the proposed Mask R-CNN algorithm based on RGB-D has the best cabin segmentation accuracy, robustness, and generalization capability, which has practical significance for industrial applications.
KeywordImage segmentation Robustness Production Position measurement Feature extraction Deep learning Adaptation models Cabin docking cabin pose measurement deep neural network (DNN) red-green-blue-depth (RGB-D) image segmentation RGB-D sensor
DOI10.1109/TIM.2022.3145388
WOS KeywordUNCERTAINTIES EVALUATION ; ALIGNMENT SYSTEM ; AIRCRAFT ; CALIBRATION ; COMPONENT
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[U1813208] ; National Natural Science Foundation of China[62003341] ; National Natural Science Foundation of China[62173327] ; National Natural Science Foundation of China[61903362] ; National Key Research and Development Program of China[2019YFB1312703]
Funding OrganizationNational Natural Science Foundation of China ; National Key Research and Development Program of China
WOS Research AreaEngineering ; Instruments & Instrumentation
WOS SubjectEngineering, Electrical & Electronic ; Instruments & Instrumentation
WOS IDWOS:000761251000025
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Sub direction classification多模态智能
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/48070
Collection复杂系统管理与控制国家重点实验室_先进机器人
Corresponding AuthorJing, Fengshui
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Fu, Yichen,Fan, Junfeng,Xing, Shiyu,et al. Image Segmentation of Cabin Assembly Scene Based on Improved RGB-D Mask R-CNN[J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,2022,71:12.
APA Fu, Yichen,Fan, Junfeng,Xing, Shiyu,Wang, Zhe,Jing, Fengshui,&Tan, Min.(2022).Image Segmentation of Cabin Assembly Scene Based on Improved RGB-D Mask R-CNN.IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,71,12.
MLA Fu, Yichen,et al."Image Segmentation of Cabin Assembly Scene Based on Improved RGB-D Mask R-CNN".IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 71(2022):12.
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