Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

Assembly Sequence Planning for Robotic Automatic Operation

Authors
Hui Li, Xu-tang Zhang, Xi Wang
Corresponding Author
Hui Li
Available Online June 2016.
DOI
10.2991/mecs-17.2017.98How to use a DOI?
Keywords
assembly sequence planning, interference matrix, discrete particle swarm optimization algorithm, automatic operation.
Abstract

This paper has improved the traditional interference matrix, with joining the information of robotic assembly resource, which is used to search for the optimal assembly sequence. We have given a processing method of interference matrix containing the resource of the robotic assembly, which includes the decision method of geometry feasibility, method of judging the interference between two parts. By dealing with the proposed interference matrix, we define a fitness function to evaluate the value of the various assembly sequences. At last, the paper use Discrete Particle Swarm Optimization (DPSO) algorithm to search the optimal assembly sequence, which is more conformable to actually assemble by using robot.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
10.2991/mecs-17.2017.98
ISSN
2352-5401
DOI
10.2991/mecs-17.2017.98How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Hui Li
AU  - Xu-tang Zhang
AU  - Xi Wang
PY  - 2016/06
DA  - 2016/06
TI  - Assembly Sequence Planning for Robotic Automatic Operation
BT  - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecs-17.2017.98
DO  - 10.2991/mecs-17.2017.98
ID  - Li2016/06
ER  -