Yanjiang Chen, Yanbo Wang, Junqin Lin, Zhihong Chen, Yao Wang
{"title":"基于视觉SLAM的多机器人点云图融合算法","authors":"Yanjiang Chen, Yanbo Wang, Junqin Lin, Zhihong Chen, Yao Wang","doi":"10.1109/ICCECE51280.2021.9342251","DOIUrl":null,"url":null,"abstract":"To solve the problem of inaccurate judgment of overlapping areas in multi-robot system point cloud map fusion, an overlapping areas judgment method based on visual SLAM key frames relative motion size is mooted. On the basis of SLAM mapping, the relative motion is determined comprehensively through features matching and geometric constraint between key frames. Then overlapping areas of maps are determined by relative motion size. At last initial transformation matrix between maps can be calculated. We run our algorithm in both open datasets and real world environment. The results show that the accuracy of this algorithm is higher than that of traditional algorithms.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Robot Point Cloud Map Fusion Algorithm Based on Visual SLAM\",\"authors\":\"Yanjiang Chen, Yanbo Wang, Junqin Lin, Zhihong Chen, Yao Wang\",\"doi\":\"10.1109/ICCECE51280.2021.9342251\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the problem of inaccurate judgment of overlapping areas in multi-robot system point cloud map fusion, an overlapping areas judgment method based on visual SLAM key frames relative motion size is mooted. On the basis of SLAM mapping, the relative motion is determined comprehensively through features matching and geometric constraint between key frames. Then overlapping areas of maps are determined by relative motion size. At last initial transformation matrix between maps can be calculated. We run our algorithm in both open datasets and real world environment. The results show that the accuracy of this algorithm is higher than that of traditional algorithms.\",\"PeriodicalId\":229425,\"journal\":{\"name\":\"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCECE51280.2021.9342251\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECE51280.2021.9342251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-Robot Point Cloud Map Fusion Algorithm Based on Visual SLAM
To solve the problem of inaccurate judgment of overlapping areas in multi-robot system point cloud map fusion, an overlapping areas judgment method based on visual SLAM key frames relative motion size is mooted. On the basis of SLAM mapping, the relative motion is determined comprehensively through features matching and geometric constraint between key frames. Then overlapping areas of maps are determined by relative motion size. At last initial transformation matrix between maps can be calculated. We run our algorithm in both open datasets and real world environment. The results show that the accuracy of this algorithm is higher than that of traditional algorithms.