Felipe N. Martins, José Lima, Andre Schneider de Oliveira, Paulo Costa, Amy Eguchi
{"title":"社论：教育机器人与竞赛","authors":"Felipe N. Martins, José Lima, Andre Schneider de Oliveira, Paulo Costa, Amy Eguchi","doi":"10.3389/frobt.2024.1394849","DOIUrl":null,"url":null,"abstract":"(AMRs). The paper describes an innovative approach to the indoor localization system for the competition based on the Extended Kalman Filter (EKF) and ArUco markers. The authors tested and compared different innovation methods for the obtained observations in the EKF, validating their approach in a real scenario using a factory floor with the official specifications provided by the competition organization.","PeriodicalId":504612,"journal":{"name":"Frontiers in Robotics and AI","volume":"16 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Editorial: Educational robotics and competitions\",\"authors\":\"Felipe N. Martins, José Lima, Andre Schneider de Oliveira, Paulo Costa, Amy Eguchi\",\"doi\":\"10.3389/frobt.2024.1394849\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"(AMRs). The paper describes an innovative approach to the indoor localization system for the competition based on the Extended Kalman Filter (EKF) and ArUco markers. The authors tested and compared different innovation methods for the obtained observations in the EKF, validating their approach in a real scenario using a factory floor with the official specifications provided by the competition organization.\",\"PeriodicalId\":504612,\"journal\":{\"name\":\"Frontiers in Robotics and AI\",\"volume\":\"16 6\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Robotics and AI\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3389/frobt.2024.1394849\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Robotics and AI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frobt.2024.1394849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
(AMRs). The paper describes an innovative approach to the indoor localization system for the competition based on the Extended Kalman Filter (EKF) and ArUco markers. The authors tested and compared different innovation methods for the obtained observations in the EKF, validating their approach in a real scenario using a factory floor with the official specifications provided by the competition organization.
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