Efficient Hearing-Dog-Robot Searching for User Using Life Pattern Clustering

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  • クラスタリングを用いた生活パターン推定による聴導犬ロボットの効率的ユーザ探索
  • クラスタリング オ モチイタ セイカツ パターン スイテイ ニ ヨル チョウドウケン ロボット ノ コウリツテキ ユーザ タンサク

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Abstract

<p>Hearing dogs can search for deaf people to alert important life sounds. The dogs use their own body and touch the people to inform them of the sound. Meanwhile, few of the dogs work actually. To solve the problem, a hearing-dog robot has been proposed and developed so far. Furuta et al. proposed a method to estimate a user’s life pattern. The life pattern is estimated using past searching data acquired from what the robot had searched for the user. The proposal aims to more quickly detect the user. But, lack and bias of the past searching data make the method weak. This paper proposes a method to estimate life pattern of the user. The life pattern is described as proper probabilistic distribution. To achieve the probabilistic distribution, the method applies a clustering algorithm for the past data. The method hires Dirichlet process mixture model for the clustering. We conducted a simulation experiment to evaluate the method. The experiment prepared a user model that has a certain life pattern on the experiment environment. We evaluated time cost for the robot to search for the user model. The experimental result showed efficient searching in comparison with the method of Furuta et al.</p>

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