Towards 3D Point cloud based object maps for household environments

被引:753
|
作者
Rusu, Radu Bogdan [1 ]
Marton, Zoltan Csaba [1 ]
Blodow, Nico [1 ]
Dolha, Mihai [1 ]
Beetz, Michael [1 ]
机构
[1] Tech Univ Munich, Dept Comp Sci, Intelligent Autonomous Syst Grp, D-85748 Garching, Germany
关键词
Environment object model; Point cloud data; Geometrical reasoning;
D O I
10.1016/j.robot.2008.08.005
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article investigates the problem of acquiring 3D object maps of indoor household environments, in particular kitchens. The objects modeled in these maps include cupboards, tables, drawers and shelves, which are of particular importance for a household robotic assistant. Our mapping approach is based on PCD (point cloud data) representations. Sophisticated interpretation methods operating on these representations eliminate noise and resample the data without deleting the important details, and interpret the improved point clouds in terms of rectangular planes and 3D geometric shapes. We detail the steps of our mapping approach and explain the key techniques that make it work. The novel techniques include statistical analysis, persistent histogram features estimation that allows for a consistent registration, resampling with additional robust fitting techniques, and segmentation of the environment into meaningful regions. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:927 / 941
页数:15
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