火星探测器的自动定位

T. Estlin, R. Castaño, B. Bornstein, D. Gaines, R. Anderson, C. D. Granville, D. Thompson, M. Burl, M. Judd, Steve Ankuo Chien
{"title":"火星探测器的自动定位","authors":"T. Estlin, R. Castaño, B. Bornstein, D. Gaines, R. Anderson, C. D. Granville, D. Thompson, M. Burl, M. Judd, Steve Ankuo Chien","doi":"10.1109/SMC-IT.2009.38","DOIUrl":null,"url":null,"abstract":"The Autonomous Exploration for Gathering Increased Science System (AEGIS) will soon provide automated targeting for remote sensing instruments on the Mars Exploration Rover (MER) mission, which currently has two rovers exploring the surface of Mars. Targets for rover remote-sensing instruments, especially narrow field-of-view instruments (such as the MER Mini-TES spectrometer or the 2011 Mars Science Laboratory (MSL) Mission ChemCam Spectrometer), are typically selected manually based on imagery already on the ground with the operations team. AEGIS enables the rover flight software to analyze imagery onboard in order to autonomously select and sequence targeted remote-sensing observations in an opportunistic fashionIn this paper, we first provide background information on the larger autonomous science framework in which AEGIS was developed. We then describe how AEGIS was specifically developed and tested on the JPL FIDO rover. Finally we discuss how AEGIS will be uploaded and used on the Mars Exploration Rover (MER) mission in mid 2009.","PeriodicalId":422009,"journal":{"name":"2009 Third IEEE International Conference on Space Mission Challenges for Information Technology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Automated Targeting for the MER Rovers\",\"authors\":\"T. Estlin, R. Castaño, B. Bornstein, D. Gaines, R. Anderson, C. D. Granville, D. Thompson, M. Burl, M. Judd, Steve Ankuo Chien\",\"doi\":\"10.1109/SMC-IT.2009.38\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Autonomous Exploration for Gathering Increased Science System (AEGIS) will soon provide automated targeting for remote sensing instruments on the Mars Exploration Rover (MER) mission, which currently has two rovers exploring the surface of Mars. Targets for rover remote-sensing instruments, especially narrow field-of-view instruments (such as the MER Mini-TES spectrometer or the 2011 Mars Science Laboratory (MSL) Mission ChemCam Spectrometer), are typically selected manually based on imagery already on the ground with the operations team. AEGIS enables the rover flight software to analyze imagery onboard in order to autonomously select and sequence targeted remote-sensing observations in an opportunistic fashionIn this paper, we first provide background information on the larger autonomous science framework in which AEGIS was developed. We then describe how AEGIS was specifically developed and tested on the JPL FIDO rover. Finally we discuss how AEGIS will be uploaded and used on the Mars Exploration Rover (MER) mission in mid 2009.\",\"PeriodicalId\":422009,\"journal\":{\"name\":\"2009 Third IEEE International Conference on Space Mission Challenges for Information Technology\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Third IEEE International Conference on Space Mission Challenges for Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMC-IT.2009.38\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Third IEEE International Conference on Space Mission Challenges for Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMC-IT.2009.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

摘要

自动探测收集增强科学系统(AEGIS)将很快为火星探测漫游者(MER)任务上的遥感仪器提供自动瞄准,该任务目前有两个漫游者在火星表面探测。漫游者遥感仪器的目标,特别是窄视场仪器(如MER Mini-TES光谱仪或2011年火星科学实验室(MSL)任务化学凸轮光谱仪),通常是根据地面上已有的图像与操作团队手动选择的。AEGIS使漫游者飞行软件能够分析机载图像,以便以机会主义的方式自主选择和排序目标遥感观测。在本文中,我们首先提供了开发AEGIS的更大的自主科学框架的背景信息。然后我们描述了AEGIS是如何在JPL FIDO探测器上进行开发和测试的。最后,我们讨论了如何将AEGIS上传并用于2009年中期的火星探测漫游者(MER)任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Targeting for the MER Rovers
The Autonomous Exploration for Gathering Increased Science System (AEGIS) will soon provide automated targeting for remote sensing instruments on the Mars Exploration Rover (MER) mission, which currently has two rovers exploring the surface of Mars. Targets for rover remote-sensing instruments, especially narrow field-of-view instruments (such as the MER Mini-TES spectrometer or the 2011 Mars Science Laboratory (MSL) Mission ChemCam Spectrometer), are typically selected manually based on imagery already on the ground with the operations team. AEGIS enables the rover flight software to analyze imagery onboard in order to autonomously select and sequence targeted remote-sensing observations in an opportunistic fashionIn this paper, we first provide background information on the larger autonomous science framework in which AEGIS was developed. We then describe how AEGIS was specifically developed and tested on the JPL FIDO rover. Finally we discuss how AEGIS will be uploaded and used on the Mars Exploration Rover (MER) mission in mid 2009.
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:481959085
Book学术官方微信