高速なガウス過程回帰を用いた予測モデルに基づくサンプリングベース動作計画 Sampling-based Motion Planning with a Prediction Model using Fast Gaussian Process Regression

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著者

    • 岡留 有哉 Okadome Yuya
    • 大阪大学 基礎工学研究科 システム創成専攻 Osaka University, Graduate of Engineering Science, Department of System Innovation
    • 中村 泰 Nakamura Yutaka
    • 大阪大学 基礎工学研究科 システム創成専攻 Osaka University, Graduate of Engineering Science, Department of System Innovation
    • 石黒 浩 Ishiguro Hiroshi
    • 大阪大学 基礎工学研究科 システム創成専攻 Osaka University, Graduate of Engineering Science, Department of System Innovation

抄録

Recently, motion/path planning methods become popular and achieve practical applications such as autonomous car. Most of studies focuses on the planning based on a given mathematical model, but the development of data-driven system identification method is also crucial for practical applications, since the precise model of a control target is not always available in advance. In this research, we propose a motion planning method where a fast Gaussian process regression is used as a model of the control target, since Gaussian process regression is a powerful non-parametric method which is widely used in various practical and complicate applications. Thanks to Bayesian property of Gaussian process regression, our method can deal with uncertainty of the prediction. We apply our method to the control problem of simple-pendulum with non-linearity and achieve the swinging up task.

収録刊行物

  • 電気学会論文誌. C

    電気学会論文誌. C 135(5), 526-533, 2015

    The Institute of Electrical Engineers of Japan

各種コード

  • NII論文ID(NAID)
    130005068052
  • NII書誌ID(NCID)
    AN10065950
  • 本文言語コード
    JPN
  • ISSN
    0385-4221
  • NDL 記事登録ID
    026423446
  • NDL 請求記号
    Z16-795
  • データ提供元
    NDL  J-STAGE 
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