Knowledge Commons of Institute of Automation,CAS
Multimodal Unknown Surface Material Classification and Its Application to Physical Reasoning | |
Wei, Junhang1,2; Cui, Shaowei1,2; Hu, Jingyi1,2; Hao, Peng2,3; Wang, Shuo2,3,4; Lou, Zheng5 | |
发表期刊 | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS |
ISSN | 1551-3203 |
2022-07-01 | |
卷号 | 18期号:7页码:4406-4416 |
摘要 | Unknown surface material classification (SMC) can inform a robot about material properties, enabling it to interact with environments appropriately. Recent research has leveraged multimodal data using deep learning to improve the performance of SMC. In this article, we present a deep learning model, multimodal temporal convolutional neural network (MTCNN), which integrates energy spectrum, dilated convolutions, and sequence poolings into a unified network architecture. The proposed model can learn material representations from auditory and multitactile (i.e., acceleration, normal force, and friction force) data generated by dragging a tool along surfaces, and distinguish unknown object surface materials into categories. For surface material data collection, a tool is also designed to detect different object surfaces. The performance of MTCNN is evaluated on a public dataset and the highest classification accuracy is 87.55%. A robotic curling example is provided to illustrate how the presented model helps the robot in manipulation. |
关键词 | Robots Convolutional neural networks Visualization Informatics Feature extraction Task analysis Haptic interfaces Auditory and haptic information deep learning multimodal fusion physical reasoning unknown surface material classification (USMC) |
DOI | 10.1109/TII.2021.3126601 |
关键词[WOS] | TACTILE ; GENERATION |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key R&D Program of China[2018AAA0103003] ; National Natural Science Foundation of China[61773378] ; National Natural Science Foundation of China[U1913201] ; National Natural Science Foundation of China[U1713222] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32050100] ; Beijing Advanced Discipline Fund |
项目资助者 | National Key R&D Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Science ; Beijing Advanced Discipline Fund |
WOS研究方向 | Automation & Control Systems ; Computer Science ; Engineering |
WOS类目 | Automation & Control Systems ; Computer Science, Interdisciplinary Applications ; Engineering, Industrial |
WOS记录号 | WOS:000784218500013 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 智能机器人 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48323 |
专题 | 多模态人工智能系统全国重点实验室_智能机器人系统研究 多模态人工智能系统全国重点实验室 |
通讯作者 | Wang, Shuo |
作者单位 | 1.Univ Chinese Acad Sci, Sch Future Technol, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China 5.Chinese Acad Sci, State Key Lab Superlattices & Microstruct, Inst Semicond, Beijing 100083, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Wei, Junhang,Cui, Shaowei,Hu, Jingyi,et al. Multimodal Unknown Surface Material Classification and Its Application to Physical Reasoning[J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,2022,18(7):4406-4416. |
APA | Wei, Junhang,Cui, Shaowei,Hu, Jingyi,Hao, Peng,Wang, Shuo,&Lou, Zheng.(2022).Multimodal Unknown Surface Material Classification and Its Application to Physical Reasoning.IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,18(7),4406-4416. |
MLA | Wei, Junhang,et al."Multimodal Unknown Surface Material Classification and Its Application to Physical Reasoning".IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 18.7(2022):4406-4416. |
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