{"title":"使用两个像素摄像头和人工色码签名信标的全向机器人室内定位","authors":"Mohanad N. Noaman, Z. Al-Shibaany, Saba Al-Wais","doi":"10.1145/3440840.3440849","DOIUrl":null,"url":null,"abstract":"Location estimation of Autonomous mobile robots is an essential and challenging task, especially for indoor applications. Despite the many solutions and algorithms that have been suggested in the literature to provide a precise localisation technique for mobile robots, it continues to be an open research problem and worth further study. In this paper, a predefined map with artificial colour code signature (CCs) beacons are used to build an effective algorithm to achieve an indoor localisation and position prediction of an omnidirectional mobile robot. This algorithm is primarily based on calculating the distance between the robot and the beacon using Pixy cameras, as vision sensors; then, estimating the position of the robot using a trilateration method. By comparing the results obtained in this paper with the mathematically obtained results, it is clearly shown that the robot effectively follows the localisation algorithm to estimate its pose (position and orientation), improving its localisation abilities in addition to obtaining its initial position. Furthermore, the limitations associated with using Pixy cameras are discussed in this paper as well.","PeriodicalId":273859,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Computational Intelligence and Intelligent Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Omnidirectional Robot Indoor Localisation using Two Pixy Cameras and Artificial Colour Code Signature Beacons\",\"authors\":\"Mohanad N. Noaman, Z. Al-Shibaany, Saba Al-Wais\",\"doi\":\"10.1145/3440840.3440849\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Location estimation of Autonomous mobile robots is an essential and challenging task, especially for indoor applications. Despite the many solutions and algorithms that have been suggested in the literature to provide a precise localisation technique for mobile robots, it continues to be an open research problem and worth further study. In this paper, a predefined map with artificial colour code signature (CCs) beacons are used to build an effective algorithm to achieve an indoor localisation and position prediction of an omnidirectional mobile robot. This algorithm is primarily based on calculating the distance between the robot and the beacon using Pixy cameras, as vision sensors; then, estimating the position of the robot using a trilateration method. By comparing the results obtained in this paper with the mathematically obtained results, it is clearly shown that the robot effectively follows the localisation algorithm to estimate its pose (position and orientation), improving its localisation abilities in addition to obtaining its initial position. Furthermore, the limitations associated with using Pixy cameras are discussed in this paper as well.\",\"PeriodicalId\":273859,\"journal\":{\"name\":\"Proceedings of the 2020 3rd International Conference on Computational Intelligence and Intelligent Systems\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 3rd International Conference on Computational Intelligence and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3440840.3440849\",\"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 the 2020 3rd International Conference on Computational Intelligence and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3440840.3440849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Omnidirectional Robot Indoor Localisation using Two Pixy Cameras and Artificial Colour Code Signature Beacons
Location estimation of Autonomous mobile robots is an essential and challenging task, especially for indoor applications. Despite the many solutions and algorithms that have been suggested in the literature to provide a precise localisation technique for mobile robots, it continues to be an open research problem and worth further study. In this paper, a predefined map with artificial colour code signature (CCs) beacons are used to build an effective algorithm to achieve an indoor localisation and position prediction of an omnidirectional mobile robot. This algorithm is primarily based on calculating the distance between the robot and the beacon using Pixy cameras, as vision sensors; then, estimating the position of the robot using a trilateration method. By comparing the results obtained in this paper with the mathematically obtained results, it is clearly shown that the robot effectively follows the localisation algorithm to estimate its pose (position and orientation), improving its localisation abilities in addition to obtaining its initial position. Furthermore, the limitations associated with using Pixy cameras are discussed in this paper as well.