{"title":"Sensor Lattices: Structures for Comparing Information Feedback","authors":"S. LaValle","doi":"10.1109/RoMoCo.2019.8787364","DOIUrl":null,"url":null,"abstract":"This paper addresses the sensing uncertainty associated with the many-to-one mapping from a physical state space onto a sensor observation space. By studying preimages of this mapping for each sensor, a notion of sensor dominance is introduced, which enables interchangeability of sensors and a clearer understanding of their tradeoffs. The notion of a sensor lattice is also introduced, in which all possible sensor models are arranged into a hierarchy that indicates their power and gives insights into the construction of filters over time and space. This provides a systematic way to compare and characterize information feedback in robotic systems, in terms of their level of ambiguity with regard to state estimation.","PeriodicalId":415070,"journal":{"name":"2019 12th International Workshop on Robot Motion and Control (RoMoCo)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 12th International Workshop on Robot Motion and Control (RoMoCo)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RoMoCo.2019.8787364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This paper addresses the sensing uncertainty associated with the many-to-one mapping from a physical state space onto a sensor observation space. By studying preimages of this mapping for each sensor, a notion of sensor dominance is introduced, which enables interchangeability of sensors and a clearer understanding of their tradeoffs. The notion of a sensor lattice is also introduced, in which all possible sensor models are arranged into a hierarchy that indicates their power and gives insights into the construction of filters over time and space. This provides a systematic way to compare and characterize information feedback in robotic systems, in terms of their level of ambiguity with regard to state estimation.