进入机器人深处:来自DARPA地下挑战赛的分析和见解

IF 11.2 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Annual Review of Control Robotics and Autonomous Systems Pub Date : 2022-11-28 DOI:10.1146/annurev-control-062722-100728

Timothy H. Chung, Viktor L. Orekhov, Angela Maio

{"title":"进入机器人深处:来自DARPA地下挑战赛的分析和见解","authors":"Timothy H. Chung, Viktor L. Orekhov, Angela Maio","doi":"10.1146/annurev-control-062722-100728","DOIUrl":null,"url":null,"abstract":"The Defense Advanced Research Projects Agency (DARPA) Subterranean Challenge represented a multiyear (2018–2021), competition-based initiative to inspire and shape the future of field robotics, specifically in advancing integrated technologies for operating in complex underground environments. Bringing together robotics researchers and innovators from around the world to compete in physical and simulated contests, it spotlighted significant opportunities to incentivize and extract high-value technical results and insights to inform future advances. This article captures and quantifies these results, extracts relevant insights, and offers lessons learned and recommendations for further work. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29961,"journal":{"name":"Annual Review of Control Robotics and Autonomous Systems","volume":null,"pages":null},"PeriodicalIF":11.2000,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Into the Robotic Depths: Analysis and Insights from the DARPA Subterranean Challenge\",\"authors\":\"Timothy H. Chung, Viktor L. Orekhov, Angela Maio\",\"doi\":\"10.1146/annurev-control-062722-100728\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Defense Advanced Research Projects Agency (DARPA) Subterranean Challenge represented a multiyear (2018–2021), competition-based initiative to inspire and shape the future of field robotics, specifically in advancing integrated technologies for operating in complex underground environments. Bringing together robotics researchers and innovators from around the world to compete in physical and simulated contests, it spotlighted significant opportunities to incentivize and extract high-value technical results and insights to inform future advances. This article captures and quantifies these results, extracts relevant insights, and offers lessons learned and recommendations for further work. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.\",\"PeriodicalId\":29961,\"journal\":{\"name\":\"Annual Review of Control Robotics and Autonomous Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":11.2000,\"publicationDate\":\"2022-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Review of Control Robotics and Autonomous Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1146/annurev-control-062722-100728\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Control Robotics and Autonomous Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1146/annurev-control-062722-100728","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}

引用次数: 12

摘要

美国国防部高级研究计划局(DARPA)地下挑战赛是一项为期多年(2018-2021)的基于竞赛的计划，旨在激励和塑造战场机器人的未来，特别是在复杂地下环境中推进集成技术。它将来自世界各地的机器人研究人员和创新者聚集在一起，参加物理和模拟比赛，突出了激励和提取高价值技术成果和见解的重要机会，为未来的进步提供信息。本文捕获并量化了这些结果，提取了相关的见解，并为进一步的工作提供了经验教训和建议。预计《控制、机器人和自主系统年度评论》第14卷的最终在线出版日期是2023年5月。修订后的估计数请参阅http://www.annualreviews.org/page/journal/pubdates。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Into the Robotic Depths: Analysis and Insights from the DARPA Subterranean Challenge

The Defense Advanced Research Projects Agency (DARPA) Subterranean Challenge represented a multiyear (2018–2021), competition-based initiative to inspire and shape the future of field robotics, specifically in advancing integrated technologies for operating in complex underground environments. Bringing together robotics researchers and innovators from around the world to compete in physical and simulated contests, it spotlighted significant opportunities to incentivize and extract high-value technical results and insights to inform future advances. This article captures and quantifies these results, extracts relevant insights, and offers lessons learned and recommendations for further work. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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

Annual Review of Control Robotics and Autonomous Systems Multiple-

CiteScore

28.30

自引率

2.20%

发文量

期刊介绍： The Annual Review of Control, Robotics, and Autonomous Systems offers comprehensive reviews on theoretical and applied developments influencing autonomous and semiautonomous systems engineering. Major areas covered include control, robotics, mechanics, optimization, communication, information theory, machine learning, computing, and signal processing. The journal extends its reach beyond engineering to intersect with fields like biology, neuroscience, and human behavioral sciences. The current volume has transitioned to open access through the Subscribe to Open program, with all articles published under a CC BY license.