{"title":"智能机器人中优化工作对象位置测量的传感规划","authors":"M. Sallinen, T. Heikkilä","doi":"10.1109/CIRA.2005.1554281","DOIUrl":null,"url":null,"abstract":"This paper presents a method for planning the sensing features when the geometrical representation of the target object is known. The presented method is a synthesis -form and can be used in several measurement applications in robotics. Sensing planning is an important issue when the measurement data is sparse, includes a lot of noise or there are tight time-requirements. The criteria for selecting the measurement locations and orientations is a posteriori error covariance matrix of the parameters to be estimated. The presented approach is verified by simulation tests in the case of work object location.","PeriodicalId":162553,"journal":{"name":"2005 International Symposium on Computational Intelligence in Robotics and Automation","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sensing planning to optimize work object location measurements in intelligent robotics\",\"authors\":\"M. Sallinen, T. Heikkilä\",\"doi\":\"10.1109/CIRA.2005.1554281\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method for planning the sensing features when the geometrical representation of the target object is known. The presented method is a synthesis -form and can be used in several measurement applications in robotics. Sensing planning is an important issue when the measurement data is sparse, includes a lot of noise or there are tight time-requirements. The criteria for selecting the measurement locations and orientations is a posteriori error covariance matrix of the parameters to be estimated. The presented approach is verified by simulation tests in the case of work object location.\",\"PeriodicalId\":162553,\"journal\":{\"name\":\"2005 International Symposium on Computational Intelligence in Robotics and Automation\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 International Symposium on Computational Intelligence in Robotics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIRA.2005.1554281\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 International Symposium on Computational Intelligence in Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIRA.2005.1554281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sensing planning to optimize work object location measurements in intelligent robotics
This paper presents a method for planning the sensing features when the geometrical representation of the target object is known. The presented method is a synthesis -form and can be used in several measurement applications in robotics. Sensing planning is an important issue when the measurement data is sparse, includes a lot of noise or there are tight time-requirements. The criteria for selecting the measurement locations and orientations is a posteriori error covariance matrix of the parameters to be estimated. The presented approach is verified by simulation tests in the case of work object location.