{"title":"Collaborative Localization Sensor for Mobile Robots in Feature-Free Environments","authors":"Shengsong Yang, P. Payeur","doi":"10.1109/I2MTC43012.2020.9128659","DOIUrl":null,"url":null,"abstract":"Localization for mobile robots has been vastly researched in recent years. However, most solutions remain dependant on the working environment by either extracting information from or installing additional sensors into the environment. An innovative localization sensor is proposed in this work, aiming at providing pose estimation for ground mobile robots while reducing the dependency of the pose estimation on the working environment. The localization approach works under a collaborative scheme where multiple instances of the sensor take relative distance and angular measurements towards each other in order to estimate their respective pose. A mathematical model is derived for the collaborative pose estimation process and two instances of the proposed sensor are implemented and tested with a stationary and a moving landmark to validate the approach.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2MTC43012.2020.9128659","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Localization for mobile robots has been vastly researched in recent years. However, most solutions remain dependant on the working environment by either extracting information from or installing additional sensors into the environment. An innovative localization sensor is proposed in this work, aiming at providing pose estimation for ground mobile robots while reducing the dependency of the pose estimation on the working environment. The localization approach works under a collaborative scheme where multiple instances of the sensor take relative distance and angular measurements towards each other in order to estimate their respective pose. A mathematical model is derived for the collaborative pose estimation process and two instances of the proposed sensor are implemented and tested with a stationary and a moving landmark to validate the approach.