{"title":"从现场获得更多的自主导航:演示III XUV程序","authors":"M. Rosemblum, B. Gothard, J. Jaczkowski","doi":"10.1109/DASC.1999.822001","DOIUrl":null,"url":null,"abstract":"The authors have applied a systems philosophy to the computer vision problem, and they have designed a system called O-NAV (Object NAVigation) that can harness all of the computer vision technology to date, and combine these approaches into one integrated system. In O-NAV, no one sub-component bears the burden of the problem. In other words, it is not expected that algorithms alone will solve the computer vision problem. If we choose effective sensing that inherently performs some level of scene discrimination at the phenomenology level, algorithms will be handed a partially analyzed scene before they ever encounter the raw image data. The algorithms have been designed to exploit an optimized processing hardware infrastructure, to maximize computation for the \"real-time\" application of autonomous robot navigation.","PeriodicalId":269139,"journal":{"name":"Gateway to the New Millennium. 18th Digital Avionics Systems Conference. Proceedings (Cat. No.99CH37033)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Getting more from the scene for autonomous navigation: demo III XUV program\",\"authors\":\"M. Rosemblum, B. Gothard, J. Jaczkowski\",\"doi\":\"10.1109/DASC.1999.822001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors have applied a systems philosophy to the computer vision problem, and they have designed a system called O-NAV (Object NAVigation) that can harness all of the computer vision technology to date, and combine these approaches into one integrated system. In O-NAV, no one sub-component bears the burden of the problem. In other words, it is not expected that algorithms alone will solve the computer vision problem. If we choose effective sensing that inherently performs some level of scene discrimination at the phenomenology level, algorithms will be handed a partially analyzed scene before they ever encounter the raw image data. The algorithms have been designed to exploit an optimized processing hardware infrastructure, to maximize computation for the \\\"real-time\\\" application of autonomous robot navigation.\",\"PeriodicalId\":269139,\"journal\":{\"name\":\"Gateway to the New Millennium. 18th Digital Avionics Systems Conference. Proceedings (Cat. No.99CH37033)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Gateway to the New Millennium. 18th Digital Avionics Systems Conference. Proceedings (Cat. No.99CH37033)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DASC.1999.822001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gateway to the New Millennium. 18th Digital Avionics Systems Conference. Proceedings (Cat. No.99CH37033)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DASC.1999.822001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Getting more from the scene for autonomous navigation: demo III XUV program
The authors have applied a systems philosophy to the computer vision problem, and they have designed a system called O-NAV (Object NAVigation) that can harness all of the computer vision technology to date, and combine these approaches into one integrated system. In O-NAV, no one sub-component bears the burden of the problem. In other words, it is not expected that algorithms alone will solve the computer vision problem. If we choose effective sensing that inherently performs some level of scene discrimination at the phenomenology level, algorithms will be handed a partially analyzed scene before they ever encounter the raw image data. The algorithms have been designed to exploit an optimized processing hardware infrastructure, to maximize computation for the "real-time" application of autonomous robot navigation.