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杂乱场景的空间拓扑关系分析。

Spatial Topological Relation Analysis for Cluttered Scenes.

机构信息

State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China.

Shaanxi Fast Auto Drive Group Co., LTD, Xi'an 710119, China.

出版信息

Sensors (Basel). 2020 Dec 15;20(24):7181. doi: 10.3390/s20247181.

Abstract

The spatial topological relations are the foundation of robot operation planning under unstructured and cluttered scenes. Defining complex relations and dealing with incomplete point clouds from the surface of objects are the most difficult challenge in the spatial topological relation analysis. In this paper, we presented the classification of spatial topological relations by dividing the intersection space into six parts. In order to improve accuracy and reduce computing time, convex hulls are utilized to represent the boundary of objects and the spatial topological relations can be determined by the category of points in point clouds. We verified our method on the datasets. The result demonstrated that we have great improvement comparing with the previous method.

摘要

空间拓扑关系是机器人在非结构化和杂乱场景下进行操作规划的基础。在空间拓扑关系分析中,定义复杂关系和处理物体表面不完整的点云是最具挑战性的难题。本文通过将相交空间分为六个部分,对空间拓扑关系进行了分类。为了提高精度和减少计算时间,我们利用凸包来表示物体的边界,通过点云中的点的类别来确定空间拓扑关系。我们在数据集上验证了我们的方法。结果表明,与以前的方法相比,我们有了很大的改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a975/7765252/7c2d92ea5e94/sensors-20-07181-g001.jpg

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