Error recovery using task stratification and error classification for manipulation robots in various fields
Akira Nakamura, Kazuyuki Nagata, Kensuke Harada, Natsuki Yamanobe, Tokuo Tsuji, Torea Foissotte, Yoshihiro Kawai
- Year
- 2013
- Citations
- 28
Abstract
Dexterous manipulation is an important function for working robots. Manipulator tasks such as grasping, assembly and disassembly can generally be divided into several motion primitives. We call such motion primitives “skills” and explain how most manipulator tasks can be composed of sequences of these skills. We will address the issues involved with various types of robots such as maintenance robots and service robots. We have considered hierarchizing the manipulation tasks of these robots since their tasks have become more complex than ever before. Additionally, as errors are seen likely to increase in complex tasks, it is important to implement effective error recovery technology. This paper presents our proposal for a new type of error recovery that uses the concepts of task stratification and error classification which can be expressed specifically using flow charts.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002