An Assembly Sequence Planning Framework for Complex Data using General Voronoi Diagram

被引:2
|
作者
Dorn, Sebastian [1 ]
Wolpert, Nicola [2 ]
Schoemer, Elmar [3 ]
机构
[1] Mercedes Benz AG, Prod Planning, Stuttgart, Germany
[2] Univ Appl Sci Stuttgart, Dept Geomat Comp Sci & Math, Stuttgart, Germany
[3] Johannes Gutenberg Univ Mainz, Dept Phys Math & Comp Sci, Mainz, Germany
来源
2022 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA 2022 | 2022年
关键词
ALGORITHMS;
D O I
10.1109/ICRA46639.2022.9811867
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We present the first realization of an assembly sequence planning framework for large-scale and complex 3D real-world CAD scenarios. Other than in academic benchmark data sets, in our scenario each assembled part is allowed to contain flexible fastening elements and the number of assembled parts is quite high. With our framework we are able to derive a meaningful assembly priority graph for the parts. Our framework divides the disassembly motion of each part into a NEAR- and a subsequent FAR planning phase and uses existing specialized motion planners for each phase. To reduce the number of unsuccessful motion planning requests we use a general Voronoi diagram graph and a novel collision perceiving method which significantly speed up our framework. At the end, we create an assembly priority graph to indicate which parts must be disassembled before others. In our experiments, we show that our framework is the first one which is able to generate a priority graph for a representative data set from the automotive industry. Moreover, the reported disassembly motions for the individual parts are shorter and can be computed faster than with other state-of-the-art frameworks.
引用
收藏
页码:9896 / 9902
页数:7
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