Sugeno模糊系统与证据理论在NAO机器人颜色识别中的结合

T. Nguyen, R. Boukezzoula, D. Coquin, S. Perrin
{"title":"Sugeno模糊系统与证据理论在NAO机器人颜色识别中的结合","authors":"T. Nguyen, R. Boukezzoula, D. Coquin, S. Perrin","doi":"10.1109/FUZZ-IEEE.2015.7337900","DOIUrl":null,"url":null,"abstract":"Nowadays, robotics technologies act more and more important roles in our industrial life. However, developing a robot with intelligent behaviors that follow human perception and reasoning is really a challenge. This paper introduces an artificial intelligence technique that helps a NAO robot intuitively recognize the color of a required object. Firstly, fuzzy logic is used to infer a linguistic color from pixel values. After that, evidence theory is employed to fuse fuzzy results from multiple cameras to make better decision. These methodologies obtain a good recognition quality through real time experimentations.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Combination of Sugeno fuzzy system and evidence theory for NAO robot in colors recognition\",\"authors\":\"T. Nguyen, R. Boukezzoula, D. Coquin, S. Perrin\",\"doi\":\"10.1109/FUZZ-IEEE.2015.7337900\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, robotics technologies act more and more important roles in our industrial life. However, developing a robot with intelligent behaviors that follow human perception and reasoning is really a challenge. This paper introduces an artificial intelligence technique that helps a NAO robot intuitively recognize the color of a required object. Firstly, fuzzy logic is used to infer a linguistic color from pixel values. After that, evidence theory is employed to fuse fuzzy results from multiple cameras to make better decision. These methodologies obtain a good recognition quality through real time experimentations.\",\"PeriodicalId\":185191,\"journal\":{\"name\":\"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FUZZ-IEEE.2015.7337900\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZ-IEEE.2015.7337900","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

如今,机器人技术在我们的工业生活中扮演着越来越重要的角色。然而,开发一个具有跟随人类感知和推理的智能行为的机器人确实是一个挑战。本文介绍了一种帮助NAO机器人直观地识别所需物体颜色的人工智能技术。首先,利用模糊逻辑从像素值中推断语言颜色。然后,利用证据理论对多个摄像机的模糊结果进行融合,从而做出更好的决策。通过实时实验,这些方法获得了较好的识别质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combination of Sugeno fuzzy system and evidence theory for NAO robot in colors recognition
Nowadays, robotics technologies act more and more important roles in our industrial life. However, developing a robot with intelligent behaviors that follow human perception and reasoning is really a challenge. This paper introduces an artificial intelligence technique that helps a NAO robot intuitively recognize the color of a required object. Firstly, fuzzy logic is used to infer a linguistic color from pixel values. After that, evidence theory is employed to fuse fuzzy results from multiple cameras to make better decision. These methodologies obtain a good recognition quality through real time experimentations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信