Multimodal Unknown Surface Material Classification and Its Application to Physical Reasoning | |
Wei, Junhang1,2; Cui, Shaowei1,2; Hu, Jingyi1,2; Hao, Peng1,5; Wang, Shuo1,4,5; Lou, Zheng3 | |
刊名 | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS |
2022-07-01 | |
卷号 | 18期号:7页码:4406-4416 |
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) |
ISSN号 | 1551-3203 |
DOI | 10.1109/TII.2021.3126601 |
英文摘要 | 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. |
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 |
WOS关键词 | TACTILE ; GENERATION |
WOS研究方向 | Automation & Control Systems ; Computer Science ; Engineering |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000784218500013 |
资助机构 | 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 |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/48322] |
专题 | 智能机器人系统研究 |
通讯作者 | Wang, Shuo |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Future Technol, Beijing 100049, Peoples R China 3.Chinese Acad Sci, State Key Lab Superlattices & Microstruct, Inst Semicond, Beijing 100083, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China |
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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