Presentation | 2005-01-24 Environment Recognition Method for Autonomous Mobile Robot by Using the Self-Organizing Map Mitsuru NAKAGAWA, Hiroomi HIKAWA, Takenori HIRABAYASI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper discuses the location recognition of the autonomous mobile robot by using self-organizing map (SOM). Direction sensor information is fed to the SOM to find where the robot is located. Two types of SOMs are examined for the recognition. One uses memory so that it can use the information in the past. The other is feedback SOM that can handle time variant input. Their recognition performances are studied through experiments, which show that SOM with memory has a better performance when the learned environment is changed while the feedback SOM is robust against the speed change of the robot. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Self-organizing map / Feedback SOM / Direction information / Environment recognition |
Paper # | NLP2004-92 |
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Committee | NLP |
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Conference Date | 2005/1/17(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Nonlinear Problems (NLP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Environment Recognition Method for Autonomous Mobile Robot by Using the Self-Organizing Map |
Sub Title (in English) | |
Keyword(1) | Self-organizing map |
Keyword(2) | Feedback SOM |
Keyword(3) | Direction information |
Keyword(4) | Environment recognition |
1st Author's Name | Mitsuru NAKAGAWA |
1st Author's Affiliation | Department of Computer Science and Intelligent Systems Oita Univ.() |
2nd Author's Name | Hiroomi HIKAWA |
2nd Author's Affiliation | Department of Computer Science and Intelligent Systems Oita Univ. |
3rd Author's Name | Takenori HIRABAYASI |
3rd Author's Affiliation | Department of Computer Science and Intelligent Systems Oita Univ. |
Date | 2005-01-24 |
Paper # | NLP2004-92 |
Volume (vol) | vol.104 |
Number (no) | 583 |
Page | pp.pp.- |
#Pages | 6 |
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