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Proceedings Paper

Self maintenance robot system using physical information learning for mobile robot with visual sensors
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Paper Abstract

We propose self-maintenance robot system as a method which realizes work for a long time without maintenance by the human workers. This system absorbs the change which occurs in robot's hardware by learning, and maintains working ability. We propose the two methods of learning changes in the physical information of the robot as methods which realizes the maintenance-free robot system. One is a method to learn robot's physical information based on the input and output information in the task practice from the no physical information of the robot by using a neural network which has a task common layer and a task independence layer. We use a neural network which has a task common layer and a task independence layer to learning. Other is a method to learn robot's physical information based on the difference in hoping action and actual action. In this report, we verify of these learning system by the computer simulation.

Paper Details

Date Published: 6 December 2005
PDF: 10 pages
Proc. SPIE 6052, Optomechatronic Systems Control, 605208 (6 December 2005); doi: 10.1117/12.648774
Show Author Affiliations
Naohiro Sekiguchi, Hokkaido Univ. (Japan)
Takayuki Tanaka, Hokkaido Univ. (Japan)
Shun'ichi Kaneko, Hokkaido Univ. (Japan)


Published in SPIE Proceedings Vol. 6052:
Optomechatronic Systems Control
Farrokh Janabi-Sharifi, Editor(s)

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