State Space - Artificial Intelligence for Robotics Udacity English Japanese

State Space - Artificial Intelligence for RoboticsYouTube↗ IA↗(long shot)
Education 10.9K views 7 likes 1 dislikes 29 May 2012

Udacity 651K subscribers United States YouTube↗

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[Narrator] So, in this class you will learn about particle filters.

今回の講義では粒子フィルタについて学びます

In our sequence of algorithms for estimating the state of a system,

システムの状態を予測するための一連のアルゴリズムで

this is the third one and in many ways is the best one.

3番目ですがいろいろな意味で一番良いプログラムです

It's the easiest to program and in most ways is the most flexible.

プログラムするのが最も簡単でかつ融通が利きます

And to understand why I'm saying this let me start with a little quiz that goes back into the first 2 classes.

私の考察を理解してもらうために最初の2つの講義に関する小テストです

In class 1, we learned about histogram filters,

1つ目の講義ではヒストグラムフィルタについて学びました

in class 2 about Kalman filters,

2つ目の講義ではカルマンフィルタを学び

and we even had to prove there.

証明もしなければなりませんでした

Today, I'll teach you about particle filters,

粒子フィルタについては今回の講義で学ぶので

but we can't really know about particle filters quite yet. So, my questions will only pertain to histogram filters and Kalman filters.

質問はヒストグラムフィルタとカルマンフィルタについてのみです

First, I'd like to know whether the state space was discrete or continuous.

まず初めに状態空間が離散しているのか連続しているのかという質問です

Please check exactly 1 of those 2 boxes over here,

この2つの選択肢のうち1つだけを選んでください

and I understand these are not entirely non-ambiguous questions,

少しあいまいな質問だとは思いますが

but in the spirit of the method please check whichever fits best.

どちらか最適な方を選んでください

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