Volume 4, Issue 2, September 2017, Pages 163 - 167
Estimation and Categorization of Errors in Error Recovery Using Task Stratification and Error Classification
Akira Nakamura, Kazuyuki Nagata, Kensuke Harada, Natsuki Yamanobe
Available Online 1 September 2017.
- https://doi.org/10.2991/jrnal.2017.4.2.13How to use a DOI?
- error recovery, task stratification, error classification, manipulation, planning
- 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.
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 -