{"title":"在多传感器系统中聚合相互依赖的传感数据","authors":"O. Basir, H. C. Shen","doi":"10.1109/IROS.1993.583125","DOIUrl":null,"url":null,"abstract":"The authors investigate the issue of information interdependence in multisensor systems. A consensus group approach which accounts for interdependence between group sensors is presented. The approach is based on an information theory formulation. An algorithm for computing a weighting scheme for the group sensors is developed. The algorithm rewards each sensor for the quality of its measurements and penalizes it for its interdependence with other sensors in the group.","PeriodicalId":299306,"journal":{"name":"Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Aggregating interdependent sensory data in multisensor systems\",\"authors\":\"O. Basir, H. C. Shen\",\"doi\":\"10.1109/IROS.1993.583125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors investigate the issue of information interdependence in multisensor systems. A consensus group approach which accounts for interdependence between group sensors is presented. The approach is based on an information theory formulation. An algorithm for computing a weighting scheme for the group sensors is developed. The algorithm rewards each sensor for the quality of its measurements and penalizes it for its interdependence with other sensors in the group.\",\"PeriodicalId\":299306,\"journal\":{\"name\":\"Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IROS.1993.583125\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.1993.583125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Aggregating interdependent sensory data in multisensor systems
The authors investigate the issue of information interdependence in multisensor systems. A consensus group approach which accounts for interdependence between group sensors is presented. The approach is based on an information theory formulation. An algorithm for computing a weighting scheme for the group sensors is developed. The algorithm rewards each sensor for the quality of its measurements and penalizes it for its interdependence with other sensors in the group.