{"title":"Features Matching based Merging of 3D Maps in Multi-Robot Systems","authors":"M. Drwiega","doi":"10.1109/MMAR.2019.8864711","DOIUrl":null,"url":null,"abstract":"The paper focuses on the feature matching based merging of 3D maps in a multi-robot system. The presented approach works globally what means that an initial transformation is not necessary for a proper integration of maps. The only one assumption is that the maps have a common part that can be used during a features detection, description and a matching process to compute a transformation between them. Then the found initial solution is corrected by a variation of an ICP based method. The maps are stored in the octree based representation (octomaps) but during transformation estimation a point cloud representation is used as well. In addition, the presented method was verified in various experiments, both in a simulation, with Turtlebots robots and with publicly available datasets. The solution can be applied to many robotic applications such as underwater robots, aerial robots or robots equipped with manipulators. However, so far it was mostly tested in groups of wheeled robots.","PeriodicalId":392498,"journal":{"name":"2019 24th International Conference on Methods and Models in Automation and Robotics (MMAR)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 24th International Conference on Methods and Models in Automation and Robotics (MMAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR.2019.8864711","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
The paper focuses on the feature matching based merging of 3D maps in a multi-robot system. The presented approach works globally what means that an initial transformation is not necessary for a proper integration of maps. The only one assumption is that the maps have a common part that can be used during a features detection, description and a matching process to compute a transformation between them. Then the found initial solution is corrected by a variation of an ICP based method. The maps are stored in the octree based representation (octomaps) but during transformation estimation a point cloud representation is used as well. In addition, the presented method was verified in various experiments, both in a simulation, with Turtlebots robots and with publicly available datasets. The solution can be applied to many robotic applications such as underwater robots, aerial robots or robots equipped with manipulators. However, so far it was mostly tested in groups of wheeled robots.