TEDGlobal 2013
Raffaello D'Andrea: The astounding athletic power of quadcopters
拉菲罗·安德烈: 四轴飞行器灵活的运动性能
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在TEDGlobal的机器人试验室里，拉菲洛·安德烈展示了如运动员一般思考的四轴飞行器，四轴飞行器能根据被输入的运算法则灵活解决问题。在一系列漂亮演示中，安德烈展示了飞行器如何接球，掌握平衡及如何与人一同作出决定。让我们一同关注由Kinect控制的四轴飞行器精彩表演。
Raffaello D'Andrea - Autonomous systems pioneer
Raffaello D'Andrea explores the possibilities of autonomous technology by collaborating with artists, engineers and entrepreneurs. Full bio
Raffaello D'Andrea explores the possibilities of autonomous technology by collaborating with artists, engineers and entrepreneurs. Full bio
Double-click the English transcript below to play the video.
00:23
So what does it mean for a machine to be athletic?
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机器的运动性能指的是什么？
00:26
We will demonstrate the concept of machine athleticism
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我们将向你展示机器运动性能的概念
00:29
and the research to achieve it
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及对此所做的相关研究工作。
00:31
with the help of these flying machines called quadrocopters,
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我们将借助这些被称为四轴飞行器
00:34
or quads, for short.
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或简称“四轴”的飞行机器人来做演示。
00:38
Quads have been around for a long time.
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四轴飞行器存在有很长一段时间了。
00:40
The reason that they're so popular these days
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它们之所以如此受欢迎，
00:42
is because they're mechanically simple.
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是因为它们机械构造简单。
00:44
By controlling the speeds of these four propellers,
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只要通过控制四个螺旋桨的速度，
00:46
these machines can roll, pitch, yaw,
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飞行器便可完成横滚、俯仰、偏摆等动作
00:49
and accelerate along their common orientation.
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并能沿着同一个方向加速。
00:52
On board are also a battery, a computer,
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飞行器上还装有电池、电脑
00:55
various sensors and wireless radios.
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及各种感应器和无线收发器。
00:59
Quads are extremely agile, but this agility comes at a cost.
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四轴飞行器运行极其灵活，但也正因其灵活性，
01:03
They are inherently unstable, and they need some form
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它运行却相对不稳定，需要某种形式的
01:06
of automatic feedback control in order to be able to fly.
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自动反馈装置控制才能顺利飞行。
01:16
So, how did it just do that?
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那么，它是如何完成刚才的动作的呢？
01:19
Cameras on the ceiling and a laptop
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天花板上的摄像机与笔记本电脑配合
01:21
serve as an indoor global positioning system.
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成为室内的定位系统，
01:23
It's used to locate objects in the space
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用来定位在空间中
01:26
that have these reflective markers on them.
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带有反光感应的飞行器。
01:28
This data is then sent to another laptop
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收集到的数据被发送到
01:30
that is running estimation and control algorithms,
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正在进行运行估算的另一台电脑上，
01:32
which in turn sends commands to the quad,
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电脑将指令反馈给
01:34
which is also running estimation and control algorithms.
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也在运行估算的四轴飞行器上。
01:41
The bulk of our research is algorithms.
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我们的大部分时间是花在研究运算法则上
01:44
It's the magic that brings these machines to life.
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正是这些运算法赋予了机器新生命。
01:48
So how does one design the algorithms
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那么 如何设计运算法则
01:50
that create a machine athlete?
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来让机械具有运动员一般的灵活性呢？
01:52
We use something broadly called model-based design.
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我们采用称为 “基于模型设计” 的方法
首先，我们以数学模式来形容
01:55
We first capture the physics with a mathematical model
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机器运作的物理特征
01:58
of how the machines behave.
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02:00
We then use a branch of mathematics
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然后使用数学理论的分支 — 控制理论
02:03
called control theory to analyze these models
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来分析这些数学模式，
02:05
and also to synthesize algorithms for controlling them.
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与集合各种算法来控制他们。
02:09
For example, that's how we can make the quad hover.
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举例说明，这就是我们如何能让飞行器在空中悬浮：
02:12
We first captured the dynamics
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我们先以微分方程式来
02:14
with a set of differential equations.
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描述悬浮的物理现象。
02:16
We then manipulate these equations with the help
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然后使用控制理论来重整这些方程式，
02:18
of control theory to create algorithms that stabilize the quad.
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进而得出稳定飞行器的运算法。
02:23
Let me demonstrate the strength of this approach.
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现在我来演示这种计算方法的优势。
02:29
Suppose that we want this quad to not only hover
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假如，我们想让飞行器不仅在空中悬浮，
02:31
but to also balance this pole.
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而且还能平衡这支杆子
02:34
With a little bit of practice,
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只要稍加练习，
02:36
it's pretty straightforward for a human being to do this,
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对人来说，轻易就能让杆子平衡
02:38
although we do have the advantage of having
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我们的优势是，
02:40
two feet on the ground
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我们以双脚支撑平稳地站立，
02:41
and the use of our very versatile hands.
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及我们灵活的双手。
02:44
It becomes a little bit more difficult
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这样就会比较困难，
02:47
when I only have one foot on the ground
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当我只用一只脚站立，
02:49
and when I don't use my hands.
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也不用手来掌握平衡。
02:52
Notice how this pole has a reflective marker on top,
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注意，这支杆子顶上有个感应器，
02:55
which means that it can be located in the space.
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意味着杆子能够被电脑定位。
03:04
(Applause)
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（掌声）
03:10
You can notice that this quad is making fine adjustments
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你可以注意到四轴飞行器在进行微调，
03:13
to keep the pole balanced.
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来保持杆子平衡。
03:15
How did we design the algorithms to do this?
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我们如何设计运算法来完成这个任务呢？
03:19
We added the mathematical model of the pole
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我们把杆子的数学模式
03:21
to that of the quad.
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加入到四轴飞行器的数学模式上。
03:22
Once we have a model of the combined quad-pole system,
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一旦得出四轴飞行器与杆综合系统的模式，
03:25
we can use control theory to create algorithms for controlling it.
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我们就可采用控制理论设计运算法来控制它们。
03:30
Here, you see that it's stable,
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你看到它已经稳定了，
03:32
and even if I give it little nudges,
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就算我稍微触动它一下，
03:34
it goes back to the nice, balanced position.
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它也会回到平衡位置。
03:40
We can also augment the model to include
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我们还可在该模式中加入
03:41
where we want the quad to be in space.
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操控决定飞行器在空中的位置。
03:44
Using this pointer, made out of reflective markers,
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使用有感应器的指示器，
03:47
I can point to where I want the quad to be in space
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我可以决定飞行器，在离我一定的距离内
03:49
a fixed distance away from me.
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在空中停留的位置
04:07
The key to these acrobatic maneuvers is algorithms,
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能够让飞行器做到这些动作的关键是
04:10
designed with the help of mathematical models
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借助于数学模式
04:13
and control theory.
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和控制理论设计的运算法。
04:15
Let's tell the quad to come back here
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我们让这个四轴飞行器回到这里，
04:17
and let the pole drop,
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把杆子取下来。
04:19
and I will next demonstrate the importance
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我接下来将演示
04:20
of understanding physical models
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理解物理模型
04:23
and the workings of the physical world.
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和物理世界运作的重要性。
04:37
Notice how the quad lost altitude
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注意在我把这杯水放上去时，
04:39
when I put this glass of water on it.
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这个四轴飞行器怎样降低高度。
04:41
Unlike the balancing pole, I did not include
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不像平衡杆子，这个系统里我不包括
04:44
the mathematical model of the glass in the system.
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玻璃杯的数学模型。
04:46
In fact, the system doesn't even know that the glass of water is there.
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事实上，这系统甚至不知道有杯水在那儿。
04:49
Like before, I could use the pointer to tell the quad
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像刚才那样，我可以用指示器指令四轴飞行器
04:52
where I want it to be in space.
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停在任何一个我指示它去的位置。
04:55
(Applause)
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（掌声）
05:05
Okay, you should be asking yourself,
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好， 也许你们会问
05:07
why doesn't the water fall out of the glass?
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为什么水不会从玻璃杯里洒出来？
05:09
Two facts: The first is that gravity acts
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有两个事实：第一个是引力
05:12
on all objects in the same way.
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以同样的方式作用在所有物体上。
05:15
The second is that the propellers are all pointing
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第二个是螺旋桨都指向
05:17
in the same direction of the glass, pointing up.
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玻璃杯的同一个方向，朝上。
05:20
You put these two things together, the net result
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把这两个事实和在一起，最终结果
05:23
is that all side forces on the glass are small
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是玻璃杯上的所有侧力小，
05:25
and are mainly dominated by aerodynamic effects,
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又主要受空气动力学效应控制，
05:28
which as these speeds are negligible.
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因此这些速度是微不足道的。
05:35
And that's why you don't need to model the glass.
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这就是为什么不需要给玻璃杯建立模型。
05:37
It naturally doesn't spill no matter what the quad does.
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不管四轴飞行器怎样飞行，玻璃杯里的水自然不洒。
05:50
(Applause)
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（掌声）
05:57
The lesson here is that some high-performance tasks
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这里的教训是一些高性能作业
06:01
are easier than others,
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比其它作业更容易。
06:03
and that understanding the physics of the problem
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而理解这个问题背后的物理学，
06:05
tells you which ones are easy and which ones are hard.
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你就会知道哪些容易，哪些困难
06:08
In this instance, carrying a glass of water is easy.
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在这种情况下，放一杯水很容易
06:10
Balancing a pole is hard.
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平衡一个杆子很难
06:14
We've all heard stories of athletes
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我们都听过这样的故事，
06:15
performing feats while physically injured.
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运动员身体受伤时表现出的壮举。
06:18
Can a machine also perform
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四轴飞行器外形极端受损时，
06:19
with extreme physical damage?
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是否也能飞？
06:22
Conventional wisdom says that you need
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传统观念认为
06:24
at least four fixed motor propeller pairs in order to fly,
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至少需要四对固定电机螺旋桨来飞，
06:28
because there are four degrees of freedom to control:
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因为要控制四个自由度：
06:30
roll, pitch, yaw and acceleration.
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滚转、俯仰、偏摆 和加速。
06:33
Hexacopters and octocopters, with six and eight propellers,
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六轴飞行器和八轴飞行器各带有带六个和八个螺旋桨
06:36
can provide redundancy,
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可以提供冗余。
06:37
but quadrocopters are much more popular
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但四轴飞行器更普遍，
06:39
because they have the minimum number
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因为它们的固定电动螺旋桨数量最少：
06:41
of fixed motor propeller pairs: four.
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四个。
06:44
Or do they?
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是吗？
07:01
If we analyze the mathematical model of this machine
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如果我们分析一下只带两个工作螺旋桨的
07:04
with only two working propellers,
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飞行器的数学模型，
07:06
we discover that there's an unconventional way to fly it.
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会发现有一个非常规的飞行方式。
07:19
We relinquish control of yaw,
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我们不控制偏摆，
07:21
but roll, pitch and acceleration can still be controlled
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但利用这个新配置的算法
07:24
with algorithms that exploit this new configuration.
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滚动、俯仰和加速仍然可以得到控制。
07:33
Mathematical models tell us exactly when
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数学模型确切地告诉我们什么时候
07:36
and why this is possible.
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和为什么这是可能的。
07:38
In this instance, this knowledge allows us to design
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在这种情况下，这方面的知识使我们能够设计
07:40
novel machine architectures
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新颖的机器架构
07:42
or to design clever algorithms that gracefully handle damage,
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或设计巧妙的算法，妥善处理损害，
07:46
just like human athletes do,
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就像人类运动员一样，
07:48
instead of building machines with redundancy.
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而不是建造具有冗余的机器。
07:52
We can't help but hold our breath when we watch
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我们禁不住屏住呼吸观看
07:54
a diver somersaulting into the water,
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跳水运动员翻腾入水，
07:57
or when a vaulter is twisting in the air,
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或撑杆跳高运动员快速下落时，
07:58
the ground fast approaching.
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在空中扭转身体。
08:00
Will the diver be able to pull off a rip entry?
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跳水运动员能压水花入水吗？
08:03
Will the vaulter stick the landing?
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撑杆跳高运动员会平稳落地吗？
08:05
Suppose we want this quad here
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假设我们让这个四轴飞行器
08:06
to perform a triple flip and finish off
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在同一地点
08:09
at the exact same spot that it started.
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开始并完成翻转三圈。
08:11
This maneuver is going to happen so quickly
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这个动作会发生得很快
08:13
that we can't use position feedback to correct the motion during execution.
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以至我们不能使用位置反馈信号
来纠正执行过程中的运动
来纠正执行过程中的运动
08:17
There simply isn't enough time.
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只是没有足够的时间。
08:19
Instead, what the quad can do is perform the maneuver blindly,
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相反四轴所能做的就是盲目执行操作，
08:23
observe how it finishes the maneuver,
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观察它完成操作的方式，
08:25
and then use that information to modify its behavior
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然后利用这信息修改它的行为，
08:28
so that the next flip is better.
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以便下一个翻转做得好些。
08:30
Similar to the diver and the vaulter,
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类似于跳水运动员和撑杆跳高运动员，
08:32
it is only through repeated practice
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只有通过反复练习
08:34
that the maneuver can be learned and executed
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才能学会这个动作
08:36
to the highest standard.
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并最高水平地来完成它。
08:46
(Applause)
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（掌声）
08:51
Striking a moving ball is a necessary skill in many sports.
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击打运动中的球是许多体育项目中的一个必要技能
08:54
How do we make a machine do
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我们如何让一台机器做
08:56
what an athlete does seemingly without effort?
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对一个运动员来说看似毫不费力的事呢？
09:15
(Applause)
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（掌声）
09:22
This quad has a racket strapped onto its head
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这个四轴飞行器顶上绑有一个球拍
09:25
with a sweet spot roughly the size of an apple, so not too large.
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差不多苹果大小的最佳击球位置，不能太大。
09:28
The following calculations are made every 20 milliseconds,
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每二十毫秒进行下面的计算，
09:31
or 50 times per second.
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或每秒50次。
09:33
We first figure out where the ball is going.
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我们首先搞清球的去向。
09:36
We then next calculate how the quad should hit the ball
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然后计算四轴飞行器应该怎样击球
09:38
so that it flies to where it was thrown from.
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使它飞回被抛出的位置。
09:41
Third, a trajectory is planned that carries the quad
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第三，计划一个携带四轴飞器的轨道
09:46
from its current state to the impact point with the ball.
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从目前的状态到球的落点。
09:49
Fourth, we only execute 20 milliseconds' worth of that strategy.
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第四，我们只执行值20毫秒的战略。
09:53
Twenty milliseconds later, the whole process is repeated
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二十毫秒以后，重复整个过程，
09:56
until the quad strikes the ball.
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直到四轴飞行器击到球。
10:07
(Applause)
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（掌声）
10:10
Machines can not only perform dynamic maneuvers on their own,
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机器不仅可以自己执行动态操作，
10:13
they can do it collectively.
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还可以一起来进行。
10:15
These three quads are cooperatively carrying a sky net.
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这三个四轴飞行器在空中共同支起一张网。
10:28
(Applause)
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（掌声）
10:33
They perform an extremely dynamic
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它们执行一个非常动态的
10:36
and collective maneuver
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集体行动
10:38
to launch the ball back to me.
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将球回传给我。
10:40
Notice that, at full extension, these quads are vertical.
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注意网完全伸展时，这些四轴飞行器是垂直的。
10:48
(Applause)
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（掌声）
10:50
In fact, when fully extended,
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事实上， 完全伸展时，
10:52
this is roughly five times greater than what a bungee jumper feels
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这大约是五倍于
10:55
at the end of their launch.
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蹦极者跳到最低点的力量。
11:03
The algorithms to do this are very similar
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计算这个的算法非常类似于
11:05
to what the single quad used to hit the ball back to me.
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用单个四轴飞行器击球回传给我。
11:09
Mathematical models are used to continuously re-plan
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使用数学模型不断重新规划
11:11
a cooperative strategy 50 times per second.
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一个每秒50次的合作策略。
11:16
Everything we have seen so far has been
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目前我们所看到的一切
11:18
about the machines and their capabilities.
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是机器和自己的能力。
11:20
What happens when we couple this machine athleticism
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当我们把机器的运动天赋
11:23
with that of a human being?
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和人的运动天赋连接起来会发生什么呢？
11:25
What I have in front of me is a commercial gesture sensor
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我面前的是一个商业用的姿势传感器，
11:29
mainly used in gaming.
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主要用于游戏。
11:30
It can recognize what my various body parts
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它可以识别我身体的不同部位
11:32
are doing in real time.
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实时地在做什么。
11:34
Similar to the pointer that I used earlier,
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类似于我前面用的指示器，
11:36
we can use this as inputs to the system.
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我们可以用这个作为系统的输入。
11:39
We now have a natural way of interacting
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我们现在有一种自然的方式，
11:41
with the raw athleticism of these quads with my gestures.
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让这些四轴的原始的运动天赋和我的手势交互。
12:22
(Applause)
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（掌声）
12:35
Interaction doesn't have to be virtual. It can be physical.
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交互不一定是虚拟的，它可以是物质的。
12:39
Take this quad, for example.
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例如这个四轴飞行器，
12:41
It's trying to stay at a fixed point in space.
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它正设法呆在空间里的一个固定点上。
12:44
If I try to move it out of the way, it fights me,
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如果我试图让它离开，它就抵抗我，
12:48
and moves back to where it wants to be.
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回到它想呆的地方。
12:52
We can change this behavior, however.
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然而我们可以改变这种行为。
12:55
We can use mathematical models
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我们能利用数学模型
12:57
to estimate the force that I'm applying to the quad.
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估计我正施加在四轴飞行器上的力。
13:00
Once we know this force, we can also change the laws of physics,
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一旦知道了这个力，我们也可以改变物理定律，
13:03
as far as the quad is concerned, of course.
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当然就四轴飞行器而言。
13:07
Here the quad is behaving as if it were
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这里四轴飞行器表现得好像它
13:10
in a viscous fluid.
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在粘性流体中。
13:14
We now have an intimate way
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我们现在用一种亲密的方式
13:16
of interacting with a machine.
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来和机器进行交互。
13:18
I will use this new capability to position
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我将用这个新的能力来把
13:21
this camera-carrying quad to the appropriate location
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这个带有摄相机的四轴飞行器定位在合适的位置
13:23
for filming the remainder of this demonstration.
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拍下剩下的演示。
13:36
So we can physically interact with these quads
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这样我们可以实际与这些四轴交互
13:38
and we can change the laws of physics.
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并能改变物理定律。
13:41
Let's have a little bit of fun with this.
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让我们从中得到一点小小的乐趣。
13:43
For what you will see next, these quads
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你们接下来要看到的，这些四轴飞行器
13:45
will initially behave as if they were on Pluto.
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会最初表现为好像它们在冥王星上。
13:48
As time goes on, gravity will be increased
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随着时间的变化，引力会增加
13:51
until we're all back on planet Earth,
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直到我们都回到地球上。
13:53
but I assure you we won't get there.
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但是我向你们保证我们不会的。
13:55
Okay, here goes.
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好，开始 。
14:05
(Laughter)
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（笑声）
14:34
(Laughter)
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（笑声）
14:37
(Applause)
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（掌声）
14:41
Whew!
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呼！
14:46
You're all thinking now,
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你们现在都在想，
14:48
these guys are having way too much fun,
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这些家伙太有意思了，
14:50
and you're probably also asking yourself,
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你们大概也在问自己，
14:52
why exactly are they building machine athletes?
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他们到底为什么建造机器运动员？
14:56
Some conjecture that the role of play in the animal kingdom
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一些人猜想，在动物王国中发挥的作用
14:58
is to hone skills and develop capabilities.
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是磨练技能和发展能力。
15:01
Others think that it has more of a social role,
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其他的人则认为它有更多的社会作用，
15:03
that it's used to bind the group.
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可以用来组织团队。
15:05
Similarly, we use the analogy of sports and athleticism
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同样，我们使用体育和运动的类比
15:08
to create new algorithms for machines
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创建了机器的新算法
15:11
to push them to their limits.
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使它们达到自己的极限。
15:13
What impact will the speed of machines have on our way of life?
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机器的速度对我们的生活方式会有什么影响呢？
15:16
Like all our past creations and innovations,
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像所有我们过去的创造和创新一样，
15:19
they may be used to improve the human condition
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它们要么可以用来改善人类生存条件
15:22
or they may be misused and abused.
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要么可能被误用和滥用。
15:24
This is not a technical choice we are faced with;
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这不是我们正面临的技术选择，
15:26
it's a social one.
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而是一个社会选择。
15:28
Let's make the right choice,
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让我们做出正确的诀择，
15:29
the choice that brings out the best in the future of machines,
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这个选择带来未来机器最好的东西，
15:32
just like athleticism in sports
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就像体育中的运动
15:33
can bring out the best in us.
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能给我们带来最好的东西一样。
15:36
Let me introduce you to the wizards behind the green curtain.
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让我来给你们介绍一下这个绿幕背后的奇才们。
15:39
They're the current members of the Flying Machine Arena research team.
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他们是飞行器竞技场研究队的现任成员。
15:42
(Applause)
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（掌声）
15:47
Federico Augugliaro, Dario Brescianini, Markus Hehn,
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Federico Augugliaro, Dario Brescianini , Markus Hehn,
15:50
Sergei Lupashin, Mark Muller and Robin Ritz.
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Sergei Lupashin, Mark Muller 和 Robin Ritz。
15:53
Look out for them. They're destined for great things.
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留心这些人，他们注定要成就大事。
15:54
Thank you.
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谢谢。
15:56
(Applause)
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（掌声）
ABOUT THE SPEAKER
Raffaello D'Andrea - Autonomous systems pioneerRaffaello D'Andrea explores the possibilities of autonomous technology by collaborating with artists, engineers and entrepreneurs.
Why you should listen
Raffaello D'Andrea combines academics, business, and the arts to explore the capabilities of autonomous systems. As part of his research as professor of dynamic systems and control at the Swiss Federal Institute of Technology (ETH Zürich), he and his collaborators enchant viewers with works like the self-destructing, self-assembling Robotic Chair, or the Balancing Cube that can perch itself on its corners.
D’Andrea and his team created the Flying Machine Arena to test the gravity-defying abilities of their athletic flying robots. Building on research in the Flying Machine Arena, ETH Zürich partnered with its spin-off company Verity Studios and with Cirque du Soleil to create “Sparked,” a short film showcasing the unexpected airborne dexterity of quadcopters. D’Andrea is the co-founder of Kiva Systems, a robotics company that develops intelligent automated warehouse systems and that was acquired by Amazon in 2012.
Raffaello D'Andrea | Speaker | TED.com