Parameter Estimation of Mixture PDF Model for Mobile Robots by EM Algorithm

• Tanaka Masahiro

  Dept. of Intelligence and Informatics, Konan University

• Wada Masahiro

  Dept. of Intelligence and Informatics, Konan University

• Umetani Tomohiro

  Dept. of Intelligence and Informatics, Konan University

• Ito Minoru

  Dept. of Control Engineering, Maizuru National College of Technology

抄録

The authors have been developing an autonomous mobile robot system to be used in the campus of universities. Our robot software adheres stochastic models, where the probability density function is a mixture of several basic distributions. It is well-known that Expectation-Maximization (EM) algorithm is useful for the identification of Gaussian mixture distribution. We apply EM algorithm for our mixture model consisting of Gaussian distribution, two Exponential distributions, delta distribution and a uniform distribution. In the experimental study, we will show some Monte Carlo simulation results for several cases so that this algorithm is shown to be useful for this mixture distribution model. Next, we will apply our algorithm to real data. Finally the parameter values obtained in our algorithm will be applied to the state estimation problem. The usefulness of this algorithm will be discussed.

収録刊行物

• Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications

  Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 2014 (0), 381-388, 2014-05-05

  システム制御情報学会ストカスティックシステムシンポジウム

キーワード

• Materials Science (miscellaneous)

詳細情報

• CRID: 1390001288035408640
• NII論文ID: 130007377542
• DOI: 10.5687/sss.2014.381
• ISSN: 21884749
• ISSN: 21884730
• Web Site: https://www.jstage.jst.go.jp/article/sss/2014/0/2014_381/_pdf
• 本文言語コード: en
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