Robotic haptic adjective perception based on coupled sparse coding  

作　　者：Pengwen XIONG Kongfei HE Aiguo SONG Peter X.LIU 

机构地区：[1]School of Advanced Manufacturing,Nanchang University,Nanchang 330031,China [2]School of Instrument Science and Engineering,Southeast University,Nanjing 210096,China [3]Department of Systems and Computer Engineering,Carleton University,Ottawa ON KIS 5B6,Canada

出　　处：《Science China(Information Sciences)》2023年第2期275-276,共2页中国科学（信息科学）（英文版）

基　　金：supported by National Natural Science Foundation of China (Grant Nos. 62163024, 61903175, 61663027);Academic and Technical Leaders Foundation of Major Disciplines of Jiangxi Province (Grant No. 20204BCJ23006)。

摘　　要：Objects, textures, and materials can be identified by extracting haptic interaction information [1, 2]. For haptic adjective understanding, Gao et al. [3] adopted deep models as a unified way to learn information from vision and haptics modalities. Nevertheless, this approach depends on a transfer learning method designed for object classification.

关 键 词：classification ROBOTIC OBJECTS 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]