{"title":"基于激光SLAM的ODOM / DM地标组合导航方法","authors":"Bo Wei, Rong Yang, Yi Zhang, Sihao Shu, Bin Xing","doi":"10.1109/ICDSBA51020.2020.00065","DOIUrl":null,"url":null,"abstract":"To solve the problem that the navigation accuracy of logistics robot decreases with displacement, a combined Odom and Data Matrix (DM) landmark navigation method based on SLAM technology is proposed. Firstly, the odometer motion model was established to predict the particle position, and the DM code data information was used to correct its parameters. Then, the DM landmark observation model was established to update the particle importance weight. Then, during the improved particle resampling process, a fixed number of random particles were added according to the observed likelihood of the camera, so as to obtain more accurate particle distribution and effectively improve the positioning accuracy. At the same time, the particle degradation of Monte Carlo method (MCL) algorithm was weakened, and the improved algorithm solved the problem of position drift and hijacking of the robot. Finally, the position and pose of DM landmarks are constantly corrected through trajectory correction to improve the global navigation accuracy of the robot. Experiments based on the integrated navigation robot platform show that the accuracy of the integrated navigation method is 35.6% higher than that of the traditional laser SLAM navigation method, which verifies the effectiveness of the scheme.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ODOM / DM Landmark Integrated Navigation Method Based on Laser SLAM\",\"authors\":\"Bo Wei, Rong Yang, Yi Zhang, Sihao Shu, Bin Xing\",\"doi\":\"10.1109/ICDSBA51020.2020.00065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the problem that the navigation accuracy of logistics robot decreases with displacement, a combined Odom and Data Matrix (DM) landmark navigation method based on SLAM technology is proposed. Firstly, the odometer motion model was established to predict the particle position, and the DM code data information was used to correct its parameters. Then, the DM landmark observation model was established to update the particle importance weight. Then, during the improved particle resampling process, a fixed number of random particles were added according to the observed likelihood of the camera, so as to obtain more accurate particle distribution and effectively improve the positioning accuracy. At the same time, the particle degradation of Monte Carlo method (MCL) algorithm was weakened, and the improved algorithm solved the problem of position drift and hijacking of the robot. Finally, the position and pose of DM landmarks are constantly corrected through trajectory correction to improve the global navigation accuracy of the robot. Experiments based on the integrated navigation robot platform show that the accuracy of the integrated navigation method is 35.6% higher than that of the traditional laser SLAM navigation method, which verifies the effectiveness of the scheme.\",\"PeriodicalId\":354742,\"journal\":{\"name\":\"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDSBA51020.2020.00065\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSBA51020.2020.00065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ODOM / DM Landmark Integrated Navigation Method Based on Laser SLAM
To solve the problem that the navigation accuracy of logistics robot decreases with displacement, a combined Odom and Data Matrix (DM) landmark navigation method based on SLAM technology is proposed. Firstly, the odometer motion model was established to predict the particle position, and the DM code data information was used to correct its parameters. Then, the DM landmark observation model was established to update the particle importance weight. Then, during the improved particle resampling process, a fixed number of random particles were added according to the observed likelihood of the camera, so as to obtain more accurate particle distribution and effectively improve the positioning accuracy. At the same time, the particle degradation of Monte Carlo method (MCL) algorithm was weakened, and the improved algorithm solved the problem of position drift and hijacking of the robot. Finally, the position and pose of DM landmarks are constantly corrected through trajectory correction to improve the global navigation accuracy of the robot. Experiments based on the integrated navigation robot platform show that the accuracy of the integrated navigation method is 35.6% higher than that of the traditional laser SLAM navigation method, which verifies the effectiveness of the scheme.