Authors
Akira [email protected], Kazuyuki [email protected]
Intelligent Systems Research Institute, National Institute of Advanced Industrial Science and Technology (AIST) Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki, 305-8568 Japan
Kensuke [email protected]
Robotic Manipulation Research Group, Systems Innovation Department, Graduate School of Engineering Science, Osaka University 1-3 Machikaneyama, Toyonaka 560-8531, Japan
Natsuki [email protected]
Intelligent Systems Research Institute, National Institute of Advanced Industrial Science and Technology (AIST) Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki, 305-8568 Japan
www.aist.go.jp

Available Online 30 June 2018.
DOI
https://doi.org/10.2991/jrnal.2018.5.1.13How to use a DOI?
Keywords
error recovery; task stratification; error classification; manipulation; artificial intelligence
Abstract
We have proposed an error recovery method using the concepts of task stratification and error classification. In this paper, the recovery process after the judgment of error is described in detail. In particular, we explain how to change the parameters of planning, modeling, and sensing when error recovery is performed. Furthermore, we apply artificial intelligence (AI) techniques, such as deep learning, to error recovery.

Copyright
Copyright © 2018, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).