Aiming to generate easy-to-handle assembly sequences for robotic assembly, this study tackles assembly sequence generation by considering two tradeoff objectives: (1) insertion conditions and (2) degrees of constraints among assembled parts. We propose a multiobjective genetic algorithm to balance these two objectives for generating assembly sequences. Furthermore, the method of extracting part relation matrices including interference-free, insertion, and degree of constraint matrices is extended for application to 3D computer-aided design (CAD) models, including deformable parts. The interference of deformable parts with other parts can be easily investigated by scaling parts. A simulation experiment was conducted using the proposed method, and the results show the possibility of obtaining Pareto-optimal solutions of assembly sequences for a 3D CAD model with 33 parts including a deformable part. This approach can potentially be extended to handle various types of deformable parts and to explore graspable sequences during assembly operations.
@article{arxiv.2010.10846,
title = {Assembly Sequences Based on Multiple Criteria Against Products with Deformable Parts},
author = {Takuya Kiyokawa and Jun Takamatsu and Tsukasa Ogasawara},
journal= {arXiv preprint arXiv:2010.10846},
year = {2021}
}