Unit 5 4 Stanley DARPA Grand ChallengeYouTube↗  IA↗(long shot)
Howto & Style  10K views 51 likes 0 dislikes   23 Oct 2011
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In my own research, I've extensively used machine learning for robotics.
私の研究では機械学習を ロボット工学に大々的に利用しました
What you see here is a robot my students and I built at Stanford
スタンフォード大学で生徒と作ったロボット “スタンリー”を紹介します
called Stanley, and it won the DARPA Grand Challenge.
DARPAグランドチャレンジで優勝した
It's a self-driving car that drives without any human assistance whatsoever,
人間の補助なしで自律的に運転する自動車です
and this vehicle extensively uses machine learning.
この自動車には機械学習を広範囲で用いました
The robot is equipped with a laser system
このロボットには レーザシステムが搭載されています
I will talk more about lasers in my robotics class,
詳細はロボット工学のクラスで説明します
but here you can see how the robot is able to build
ここではロボットがどのように地形の3Dモデルを
3-D models of the terrain ahead.
構築するのかをお見せします
These are almost like video game models that allow it to make
それはビデオゲームの地形図のようなもので
assessments where to drive and where not to drive.
運転可能な場所の判断に用います
Essentially, it's trying to drive on flat ground.
基本的にロボットは平地を走ろうとします
The problem with these lasers is that they don't see very far. They see about 25 meters out, so to drive really fast the robot has to see further.
しかしレーザで検知できるのは ほんの25メートル先までです 高速で走るには もっと遠くまで見渡す必要があります
This is where machine learning comes into play.
ここで機械学習が威力を発揮します
What you see here is camera images delivered by the robot
遠くまで検知できないレーザのデータに
superimposed with laser data that doesn't see very far,
ロボットが取得した映像を重ねます
but the laser is good enough to extract samples
レーザで走行可能な道の表面のサンプルを抽出し
of driveable road surface that can then be machine learned and extrapolated into the entire camera image.
映像全体にサンプルを適用することで 学習するのです
That enables the robot to use the camera
このようにカメラを利用すればロボットは
to see driveable terrain all the way to the horizon
高速で走りながら200メートル先まで
up to like 200 meters out, enough to drive really, really fast.
運転可能な地形を見分けることができます
This ability to adapt its vision by driving its own training examples using lasers
レーザを使って訓練コースを運転する際に 映像を適用する能力は
but seeing out 200 meters or more was a key factor in winning the race.
200メートル以上先を見渡す能力と共に 私たちの勝因となりました
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