Journal of Robotics, Networking and Artificial Life

Volume 4, Issue 2, September 2017, Pages 163 - 167

Estimation and Categorization of Errors in Error Recovery Using Task Stratification and Error Classification

Authors
Akira Nakamura, Kazuyuki Nagata, Kensuke Harada, Natsuki Yamanobe
Corresponding Author
Akira Nakamura
Available Online 1 September 2017.
DOI
https://doi.org/10.2991/jrnal.2017.4.2.13How to use a DOI?
Keywords
error recovery, task stratification, error classification, manipulation, planning
Abstract
We proposed an approach to error recovery that uses the concepts of task stratification and error classification. In our method, errors are classified according to the estimated cause into several categories, such as modeling and planning errors. When an error is classified correctly, this increases the probability that the most suitable recovery is performed. In this paper, we describe a procedure for error categorization.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
4 - 2
Pages
163 - 167
Publication Date
2017/09/01
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
https://doi.org/10.2991/jrnal.2017.4.2.13How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Akira Nakamura
AU  - Kazuyuki Nagata
AU  - Kensuke Harada
AU  - Natsuki Yamanobe
PY  - 2017
DA  - 2017/09/01
TI  - Estimation and Categorization of Errors in Error Recovery Using Task Stratification and Error Classification
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 163
EP  - 167
VL  - 4
IS  - 2
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2017.4.2.13
DO  - https://doi.org/10.2991/jrnal.2017.4.2.13
ID  - Nakamura2017
ER  -