| Presentation | 2004/3/12 A Statistical Identification Method for Environmental Models of Mobile Robots Katsuyoshi KANEMOTO, Junichiro YOSHIMOTO, Shin ISHII, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | For controlling mobile robots within the framework of statistical inference, precise models of state transition and observation processes are crucial. Although these models can be obtained if the robot makes use of external information, such a setting makes the robot's applicability narrow and the implementation costly. In this study, we propose a method to identify these models from the robot's own observation. In this method, an environment is formulated as a parameterized probabilistic model in consideration of a geometric property and sensory non-linearity. The unknown parameters are determined based on the maximum likelihood estimation. We evaluated the performance of the proposed method using synthetic and real datasets. The results showed that the method successfully obtained the environmental model with a fairly good precision only from the robot's own sensory information. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Mobile robots / Probabilistic model / System Identification / EM algorithm / Particle Filter |
| Paper # | NC2003-204 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 2004/3/12(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Statistical Identification Method for Environmental Models of Mobile Robots |
| Sub Title (in English) | |
| Keyword(1) | Mobile robots |
| Keyword(2) | Probabilistic model |
| Keyword(3) | System Identification |
| Keyword(4) | EM algorithm |
| Keyword(5) | Particle Filter |
| 1st Author's Name | Katsuyoshi KANEMOTO |
| 1st Author's Affiliation | Graduate School of Information Science, Nara Institute of Science and Technology() |
| 2nd Author's Name | Junichiro YOSHIMOTO |
| 2nd Author's Affiliation | CREST, Japan Science and Technology Agency |
| 3rd Author's Name | Shin ISHII |
| 3rd Author's Affiliation | Graduate School of Information Science, Nara Institute of Science and Technology |
| Date | 2004/3/12 |
| Paper # | NC2003-204 |
| Volume (vol) | vol.103 |
| Number (no) | 734 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |