Using Importance Ranks to Derive Suitable Timing of Visual Sensing in Manipulation Task Containing Error Recove

Authors
Akira Nakamura1, *, Kazuyuki Nagata1, Kensuke Harada2, Yukiyasu Domae1
1
Automation Research Team, Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo 135-0064 Japan
2
Robotic Manipulation Research Group, Systems Innovation Department, Graduate School of Engineering Science, Osaka University, Toyonaka 560-8531, Japan
*
Corresponding author. Email: [email protected]
Corresponding Author
Akira Nakamura
Received 12 October 2018, Accepted 14 November 2018, Available Online 30 March 2019.
DOI
https://doi.org/10.2991/jrnal.k.190402.002
Keywords
Manipulation skill; importance rank; error recovery; error classification; task stratification
Abstract
In general, a manipulation task can be composed of many skill primitives. Therefore, it is desirable to carry out plural visual sensing in most skill primitives; however, performing sensing all the time is difficult. In this paper, we propose the addition of importance ranks to the attribute of skill primitives in order to derive a suitable timing for performing sensing. Furthermore, we show that the skill primitives distinguished by their high importance ranks considerably correlates with error recovery.

Copyright
© 2019 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/).

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