Authors
Akira Nakamura1, *, Natsuki Yamanobe2, Ixchel G. Ramirez-Alpizar2, Kensuke
Harada2, 3, Yukiyasu Domae2
1Department of Information Systems, Faculty of Engineering, Saitama Institute
of Technology, 1690 Fusaiji, Fukaya, Saitama 369-0293, Japan
2Industrial Cyber Physical System Research Center, National Institute of
Advanced Industrial Science and Technology (AIST) Second Annex, AIST Tokyo
Waterfront, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064 Japan
3Robotic Manipulation Research Group Systems Innovation Department, Graduate
School of Engineering Science, Osaka University, 1-3 Machikaneyama, Toyonaka
560-8531, Japan
*Corresponding author. Email: [email protected]
Corresponding Author
Akira Nakamura
Received 31 October 2020, Accepted 31 July 2021, Available Online 9 October
2021.
DOI
https://doi.org/10.2991/jrnal.k.210922.012
Keywords
Error recovery; task stratification; error classification; automation plant
Abstract
Plant automation has become increasingly popular in various industries.
However, errors are more likely to occur in difficult tasks that are often
performed in an automated plant. Such tasks are often returned to the previous
step, and re-executed in the event of a large-scale error. Therefore, it
is important to decide both the past step to which the task needs to return
and the recovery step following its return. In this study, various evaluation
standards are used to realize the planning of error recovery, while considering
these two factors.
Copyright
© 2021 The Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license
(http://creativecommons.org/licenses/by-nc/4.0/).