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DOI:
Journal of Software:2018.29(S2):54-61

具有智能交互学习能力的机械臂写字系统
杨明浩,张珂,赵博程,朱庆杰,潘航,那燊若阳,湛永松,陶建华
(模式识别国家重点实验室(中国科学院 自动化研究所), 北京 100190;中国科学院 自动化研究所 脑科学与智能技术卓越创新中心, 北京 100190;模式识别国家重点实验室(中国科学院 自动化研究所), 北京 100190;桂林电子科技大学, 广西 桂林 541004;模式识别国家重点实验室(中国科学院 自动化研究所), 北京 100190;中国科学院大学, 北京 100190;模式识别国家重点实验室(中国科学院 自动化研究所), 北京 100190;中国科学院 自动化研究所 脑科学与智能技术卓越创新中心, 北京 100190;中国科学院大学, 北京 100190)
Robotic Writing System with Intelligent Interactive Learning Ability
YANG Ming-Hao,ZHANG Ke,ZHAO Bo-Cheng,ZHU Qing-Jie,PAN Hang,NA Shen-Ruo-Yang,ZHAN Yong-Song,TAO Jian-Hua
(National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China;Research Center for Brain-Inspired Intelligence(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China;National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China;Guilin University of Electronic Technology, Guilin 541004, China;National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China;University of Chinese Academy of Sciences, Beijing 100190, China;National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China;Research Center for Brain-Inspired Intelligence(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China;University of Chinese Academy of Sciences, Beijing 100190, China)
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Received:June 01, 2017    
> 中文摘要: 基于Uarm机械臂构建了一个学习人类写字顺序的机械臂智能写字系统,该系统首先具有对陌生汉字的自动笔画拆分和书写能力,然后基于语音对话和图像分析技术,能够根据用户教授的笔画和笔顺来学习汉字的正确书写方式.首先,系统根据输入的语音信息以及摄像头观察到的文字的图像信息,获得用户想要写的关键字及对话意图;然后通过对摄像头看到的图像信息进行分析,对检测到的汉字进行自动笔画拆分和笔顺提取,对于正在教授中的字,跟踪笔迹顺序,学习汉字笔顺的正确写法.通过对话管理,机械臂会以对话的形式进行书写反馈并与用户交互,学习人类书写顺序并实现正确书写.通过实验分析及测试者主观评测,该系统取得了不错的评价.
Abstract:In this study, a robotic intelligence writing system is built based on the Uarm to learn Chinese character strokes. This system can finish automaticly strokes spliting and writing of unfamiliar charater. Besides, based on the dialogue technology and image processing technology, the system can learn the correct strokes from human. Firstly, the system gets the keyword which user want to write and user intention according to the input voice information and the word image information from camera. Then it analyzes the word image and splitting and extracting the strokes if the keyword is detected. If the word is being taught by human, the system would record the strokes order and learn the correct way to write the character. Through the dialogue management, the Uarm can interact with human through wrting and dialogue, learn form human, and write the characters correctly. According to the experimental analysis and subjective evaluation of the test, the system has been well recognized.
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基金项目:国家重点研发项目(2017YFB1002804);国家自然科学基金(61873269,61332017);广西壮族自治区自然科学基金(2017GXNSFAA198226);广西科技计划(桂科AB17195053);广西高校图像图形智能处理重点实验室课题(GIIP201602);广西可信软件重点实验室研究课题(KX201601);广西云计算与大数据协同创新中心、广西高校云计算与复杂系统重点实验室资助项目(YD16E11);广西密码学与信息安全重点实验室研究课题(CIS201602);桂林电子科技大学研究生教育创新计划(2017YJCX55);2017年广西壮族自治区自然科学基金课题(2017JJA160182);2015年广西科技攻关课题(1598018-6) 国家重点研发项目(2017YFB1002804);国家自然科学基金(61873269,61332017);广西壮族自治区自然科学基金(2017GXNSFAA198226);广西科技计划(桂科AB17195053);广西高校图像图形智能处理重点实验室课题(GIIP201602);广西可信软件重点实验室研究课题(KX201601);广西云计算与大数据协同创新中心、广西高校云计算与复杂系统重点实验室资助项目(YD16E11);广西密码学与信息安全重点实验室研究课题(CIS201602);桂林电子科技大学研究生教育创新计划(2017YJCX55);2017年广西壮族自治区自然科学基金课题(2017JJA160182);2015年广西科技攻关课题(1598018-6)
Foundation items:National Key Research & Development Plan of China (2017YFB1002804); National Nature Science Foundation of China (61873269, 61332017); Guangxi Zhuang Autonomous Region Natural Science Foundation of China (2017GXNSFAA198226); Guangxi Science and Technology Project (桂科AB17195053); Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics (GIIP201602); Guangxi Key Laboratory of Trusted Software (KX201601); Guangxi Cooperative Innovation Center of Cloud Computing and Big Data and Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems (YD16E11); Guangxi Key Laboratory of Cryptography and Information Security (CIS201602); Innovation Project of GUET Graduate Education (2017YJCX55); Guangxi Zhuang Autonomous Region Natural Science Foundation of China, Project 2017 (2017JJA160182); Guangxi Science and Technology Research Project (1598018-6)
Author NameAffiliationE-mail
YANG Ming-Hao National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China
Research Center for Brain-Inspired Intelligence(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China 
mhyang@nlpr.ia.ac.cn 
ZHANG Ke National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China
Guilin University of Electronic Technology, Guilin 541004, China 
 
ZHAO Bo-Cheng National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China
University of Chinese Academy of Sciences, Beijing 100190, China 
 
ZHU Qing-Jie National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China
Guilin University of Electronic Technology, Guilin 541004, China 
 
PAN Hang National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China
Guilin University of Electronic Technology, Guilin 541004, China 
 
NA Shen-Ruo-Yang National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China  
ZHAN Yong-Song Guilin University of Electronic Technology, Guilin 541004, China  
TAO Jian-Hua National Laboratory of Pattern Recognition(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China
Research Center for Brain-Inspired Intelligence(Institute of Automation, The Chinese Academy of Sciences), Beijing 100190, China
University of Chinese Academy of Sciences, Beijing 100190, China 
 
Reference text:

杨明浩,张珂,赵博程,朱庆杰,潘航,那燊若阳,湛永松,陶建华.具有智能交互学习能力的机械臂写字系统.软件学报,2018,29(S2):54-61

YANG Ming-Hao,ZHANG Ke,ZHAO Bo-Cheng,ZHU Qing-Jie,PAN Hang,NA Shen-Ruo-Yang,ZHAN Yong-Song,TAO Jian-Hua.Robotic Writing System with Intelligent Interactive Learning Ability.Journal of Software,2018,29(S2):54-61