Calculation of likelihood based on quasi-euclidean norm for robust particle-filer-based self-localization
In this paper, we propose to calculate a likelihood based on a quasi-euclidean norm for a fast and robust particle-filter-based self-localization of mobile robots. The quasi-euclidean norm can be calculated faster than the conventional L2 norm. Furthermore, such norm is much robust to noises than th...
| Main Authors: | , |
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| Format: | Article |
| Language: | Japanese |
| Published: |
The Japan Society of Mechanical Engineers
2014-08-01
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| Series: | Nihon Kikai Gakkai ronbunshu |
| Subjects: | |
| Online Access: | https://www.jstage.jst.go.jp/article/transjsme/80/816/80_2014dr0242/_pdf/-char/en |
| Summary: | In this paper, we propose to calculate a likelihood based on a quasi-euclidean norm for a fast and robust particle-filter-based self-localization of mobile robots. The quasi-euclidean norm can be calculated faster than the conventional L2 norm. Furthermore, such norm is much robust to noises than the L1 or L2 norm. In this work, we perform self-localization experiments based on the L1 norm, L2 norm and quasi euclidean norm likelihood to compare the robustness and processing time. Through these experiments, we confirm the effectiveness of our method. |
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| ISSN: | 2187-9761 |