空间与人工智能应用

Parthasarathi Pattnayak, Sanghamitra Patnaik
{"title":"空间与人工智能应用","authors":"Parthasarathi Pattnayak, Sanghamitra Patnaik","doi":"10.1109/OCIT56763.2022.00039","DOIUrl":null,"url":null,"abstract":"The probabilities to have a look at and have interaction with any given spacecraft are intrinsically restricted as compared to ground-based technology because of more than a few of factors. Crew availability, communication lag times, and power budgets are just a few of these. They also take into account the reachability and bandwidth of their ground connection. Every spacecraft must have some amount of autonomy, but research and previous missions have shown that by incorporating more sophisticated autonomous processes, many missions can be much more effective based on consistency, the production of knowledge, and the amount of work required to operate is a method that is becoming more and more popular for obtaining on-board autonomy. However, the variety of artificial intelligence methods and versions that are now written about in the literature is equally as wide-ranging as their prospective fields of application. This paper provides a thorough analysis of the state-of-the-art methods and algorithms for Fault Detection Isolation and Recovery (FDIR) and anomaly detection, and it provides examples of current ground- and space-based applications.","PeriodicalId":425541,"journal":{"name":"2022 OITS International Conference on Information Technology (OCIT)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Space and Applications of Artificial Intelligence\",\"authors\":\"Parthasarathi Pattnayak, Sanghamitra Patnaik\",\"doi\":\"10.1109/OCIT56763.2022.00039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The probabilities to have a look at and have interaction with any given spacecraft are intrinsically restricted as compared to ground-based technology because of more than a few of factors. Crew availability, communication lag times, and power budgets are just a few of these. They also take into account the reachability and bandwidth of their ground connection. Every spacecraft must have some amount of autonomy, but research and previous missions have shown that by incorporating more sophisticated autonomous processes, many missions can be much more effective based on consistency, the production of knowledge, and the amount of work required to operate is a method that is becoming more and more popular for obtaining on-board autonomy. However, the variety of artificial intelligence methods and versions that are now written about in the literature is equally as wide-ranging as their prospective fields of application. This paper provides a thorough analysis of the state-of-the-art methods and algorithms for Fault Detection Isolation and Recovery (FDIR) and anomaly detection, and it provides examples of current ground- and space-based applications.\",\"PeriodicalId\":425541,\"journal\":{\"name\":\"2022 OITS International Conference on Information Technology (OCIT)\",\"volume\":\"146 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 OITS International Conference on Information Technology (OCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OCIT56763.2022.00039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 OITS International Conference on Information Technology (OCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCIT56763.2022.00039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

由于许多因素,与地面技术相比,观察任何给定航天器并与之互动的可能性本质上受到限制。机组人员可用性、通信延迟时间和电力预算只是其中的一部分。它们还考虑到地面连接的可达性和带宽。每个航天器都必须有一定程度的自主性,但研究和以前的任务表明,通过结合更复杂的自主过程,许多任务可以更有效地基于一致性,知识的生产,以及操作所需的工作量,这是一种越来越受欢迎的获得机载自主性的方法。然而,现在在文献中所写的各种人工智能方法和版本与它们的潜在应用领域一样广泛。本文对故障检测、隔离和恢复(FDIR)和异常检测的最新方法和算法进行了全面分析,并提供了当前地面和空间应用的示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Space and Applications of Artificial Intelligence
The probabilities to have a look at and have interaction with any given spacecraft are intrinsically restricted as compared to ground-based technology because of more than a few of factors. Crew availability, communication lag times, and power budgets are just a few of these. They also take into account the reachability and bandwidth of their ground connection. Every spacecraft must have some amount of autonomy, but research and previous missions have shown that by incorporating more sophisticated autonomous processes, many missions can be much more effective based on consistency, the production of knowledge, and the amount of work required to operate is a method that is becoming more and more popular for obtaining on-board autonomy. However, the variety of artificial intelligence methods and versions that are now written about in the literature is equally as wide-ranging as their prospective fields of application. This paper provides a thorough analysis of the state-of-the-art methods and algorithms for Fault Detection Isolation and Recovery (FDIR) and anomaly detection, and it provides examples of current ground- and space-based applications.
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
期刊最新文献
Visualization of 3D Point Clouds for Vehicle Detection Based on LiDAR and Camera Fusion Distributed Self Intermittent Fault outlier identification technique for WSN s Vision-Based Detection of Hospital and Police Station Scene Natural Question Generation using Transformers and Reinforcement Learning Edge Intelligence Based Mitigation of False Data Injection Attack In IoMT Framework
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1