Assembly Sequence Generation for New Objects via Experience Learned from Similar Object
Zhongxiang Zhou, Rong Xiong, Zexi Chen, Yue Wang
Abstract
Assembly orders of components have direct influence on feasibility and efficiency of assembly process in manufacturing and are usually defined by experienced operators. To automate the assembly sequence generation process, we present a method using the idea of case-based reasoning, which can take advantage of experience of a reference assembly to generate the assembly sequence of a new assembly. First, a novel assembly representation method named assembly graph is present in which nodes indicating components’ 3D shape information and edges indicating the geometry constraints. Second, a similar components retrieve process is conducted based on assembly graph representation. Then, the assembly sequence is generated by applying the assembly order of retrieved components to the new ones. Next, the generated sequence is revised to satisfy the inherent constraints in the new assembly which is formulated as a contact graph. Finally, the revised sequence is stored into a case library with corresponding assembly model. We apply the proposed method to generate assembly sequences for chair assemblies and experimental results show its effectiveness and flexibility.
BibTeX
@inproceedings{iros2021_assemblysequence,
title = {Assembly Sequence Generation for New Objects via Experience Learned from Similar Object},
author = {Zhongxiang Zhou and Rong Xiong and Zexi Chen and Yue Wang},
booktitle = {IROS 2021},
year = {2021}
}