The astounding athletic power of quadcopters | Raffaello D’Andrea

The astounding athletic power of quadcopters | Raffaello D’Andrea

Translator: Joseph Geni
Reviewer: Morton Bast So what does it mean
for a machine to be athletic? We will demonstrate the concept
of machine athleticism and the research to achieve it with the help of these flying machines
called quadrocopters, or quads, for short. Quads have been around for a long time. They’re so popular these days
because they’re mechanically simple. By controlling
the speeds of these four propellers, these machines can roll, pitch, yaw, and accelerate
along their common orientation. On board are also a battery, a computer, various sensors and wireless radios. Quads are extremely agile,
but this agility comes at a cost. They are inherently unstable, and they need some form
of automatic feedback control in order to be able to fly. So, how did it just do that? Cameras on the ceiling and a laptop serve as an indoor
global positioning system. It’s used to locate objects in the space that have these reflective
markers on them. This data is then sent to another laptop that is running estimation
and control algorithms, which in turn sends commands to the quad, which is also running estimation
and control algorithms. The bulk of our research is algorithms. It’s the magic that brings
these machines to life. So how does one design the algorithms
that create a machine athlete? We use something broadly
called model-based design. We first capture the physics with a mathematical model
of how the machines behave. We then use a branch of mathematics
called control theory to analyze these models and also to synthesize
algorithms for controlling them. For example, that’s how we can
make the quad hover. We first captured the dynamics
with a set of differential equations. We then manipulate these equations
with the help of control theory to create algorithms
that stabilize the quad. Let me demonstrate
the strength of this approach. Suppose that we want
this quad to not only hover but to also balance this pole. With a little bit of practice, it’s pretty straightforward
for a human being to do this, although we do have the advantage
of having two feet on the ground and the use of our very versatile hands. It becomes a little bit more difficult when I only have one foot on the ground and when I don’t use my hands. Notice how this pole has
a reflective marker on top, which means that it can
be located in the space. (Audience) Oh! (Applause) (Applause ends) You can notice that this quad
is making fine adjustments to keep the pole balanced. How did we design
the algorithms to do this? We added the mathematical
model of the pole to that of the quad. Once we have a model
of the combined quad-pole system, we can use control theory to create
algorithms for controlling it. Here, you see that it’s stable, and even if I give it little nudges, it goes back — to the nice, balanced position. We can also augment the model to include where we want
the quad to be in space. Using this pointer,
made out of reflective markers, I can point to where I want
the quad to be in space a fixed distance away from me. (Laughter) The key to these acrobatic
maneuvers is algorithms, designed with the help
of mathematical models and control theory. Let’s tell the quad to come back here and let the pole drop, and I will next demonstrate the importance of understanding physical models and the workings of the physical world. Notice how the quad lost altitude
when I put this glass of water on it. Unlike the balancing pole, I did not include the mathematical
model of the glass in the system. In fact, the system doesn’t even know
that the glass is there. Like before, I could use
the pointer to tell the quad where I want it to be in space. (Applause) (Applause ends) Okay, you should be asking yourself, why doesn’t the water
fall out of the glass? Two facts. The first is that gravity acts
on all objects in the same way. The second is that the propellers are all pointing in the same direction
of the glass, pointing up. You put these two things together, the net result is that all side forces
on the glass are small and are mainly dominated
by aerodynamic effects, which at these speeds are negligible. And that’s why you don’t need
to model the glass. It naturally doesn’t spill,
no matter what the quad does. (Audience) Oh! (Applause) (Applause ends) The lesson here is that some high-performance tasks
are easier than others, and that understanding
the physics of the problem tells you which ones are easy
and which ones are hard. In this instance, carrying
a glass of water is easy. Balancing a pole is hard. We’ve all heard stories of athletes
performing feats while physically injured. Can a machine also perform
with extreme physical damage? Conventional wisdom says that you need at least four fixed motor
propeller pairs in order to fly, because there are four degrees
of freedom to control: roll, pitch, yaw and acceleration. Hexacopters and octocopters,
with six and eight propellers, can provide redundancy, but quadrocopters are much more popular because they have the minimum number
of fixed motor propeller pairs: four. Or do they? (Audience) Oh! (Laughter) If we analyze the mathematical
model of this machine with only two working propellers, we discover that there’s
an unconventional way to fly it. We relinquish control of yaw, but roll, pitch and acceleration
can still be controlled with algorithms that exploit
this new configuration. Mathematical models tell us
exactly when and why this is possible. In this instance, this knowledge
allows us to design novel machine architectures or to design clever algorithms
that gracefully handle damage, just like human athletes do, instead of building
machines with redundancy. We can’t help but hold our breath when we watch a diver
somersaulting into the water, or when a vaulter is twisting in the air, the ground fast approaching. Will the diver be able
to pull off a rip entry? Will the vaulter stick the landing? Suppose we want this quad here
to perform a triple flip and finish off at the exact same
spot that it started. This maneuver is going
to happen so quickly that we can’t use position feedback
to correct the motion during execution. There simply isn’t enough time. Instead, what the quad can do
is perform the maneuver blindly, observe how it finishes the maneuver, and then use that information
to modify its behavior so that the next flip is better. Similar to the diver and the vaulter, it is only through repeated practice that the maneuver can
be learned and executed to the highest standard. (Laughter) (Applause) Striking a moving ball
is a necessary skill in many sports. How do we make a machine do what an athlete does
seemingly without effort? (Laughter) (Applause) (Applause ends) This quad has a racket
strapped onto its head with a sweet spot roughly the size
of an apple, so not too large. The following calculations
are made every 20 milliseconds, or 50 times per second. We first figure out where
the ball is going. We then next calculate
how the quad should hit the ball so that it flies
to where it was thrown from. Third, a trajectory is planned
that carries the quad from its current state
to the impact point with the ball. Fourth, we only execute 20 milliseconds’
worth of that strategy. Twenty milliseconds later,
the whole process is repeated until the quad strikes the ball. (Applause) Machines can not only perform
dynamic maneuvers on their own, they can do it collectively. These three quads are cooperatively
carrying a sky net. (Applause) (Applause ends) They perform an extremely dynamic
and collective maneuver to launch the ball back to me. Notice that, at full extension,
these quads are vertical. (Applause) In fact, when fully extended, this is roughly five times greater
than what a bungee jumper feels at the end of their launch. The algorithms to do this are very similar to what the single quad used
to hit the ball back to me. Mathematical models are used
to continuously re-plan a cooperative strategy
50 times per second. Everything we have seen so far has been
about the machines and their capabilities. What happens when we couple
this machine athleticism with that of a human being? What I have in front of me
is a commercial gesture sensor mainly used in gaming. It can recognize
what my various body parts are doing in real time. Similar to the pointer
that I used earlier, we can use this as inputs to the system. We now have a natural way of interacting with the raw athleticism
of these quads with my gestures. (Applause) Interaction doesn’t have to be virtual. It can be physical. Take this quad, for example. It’s trying to stay
at a fixed point in space. If I try to move it
out of the way, it fights me, and moves back to where it wants to be. We can change this behavior, however. We can use mathematical models to estimate the force
that I’m applying to the quad. Once we know this force,
we can also change the laws of physics, as far as the quad
is concerned, of course. Here, the quad is behaving
as if it were in a viscous fluid. We now have an intimate way
of interacting with a machine. I will use this new capability to position this camera-carrying quad
to the appropriate location for filming the remainder
of this demonstration. So we can physically interact
with these quads and we can change the laws of physics. Let’s have a little bit of fun with this. For what you will see next, these quads will initially behave
as if they were on Pluto. As time goes on, gravity will be increased until we’re all back on planet Earth, but I assure you we won’t get there. Okay, here goes. (Laughter) (Laughter) (Applause) Whew! You’re all thinking now, these guys are having way too much fun, and you’re probably also asking yourself, why exactly are they building
machine athletes? Some conjecture that the role
of play in the animal kingdom is to hone skills
and develop capabilities. Others think that it has
more of a social role, that it’s used to bind the group. Similarly, we use the analogy
of sports and athleticism to create new algorithms for machines to push them to their limits. What impact will the speed
of machines have on our way of life? Like all our past creations
and innovations, they may be used to improve
the human condition or they may be misused and abused. This is not a technical choice
we are faced with; it’s a social one. Let’s make the right choice, the choice that brings out the best
in the future of machines, just like athleticism in sports
can bring out the best in us. Let me introduce you to the wizards
behind the green curtain. They’re the current members
of the Flying Machine Arena research team. (Applause) Federico Augugliaro, Dario Brescianini, Markus Hehn, Sergei Lupashin,
Mark Muller and Robin Ritz. Look out for them.
They’re destined for great things. Thank you. (Applause)

Comments (100)

  1. prepare for new world…

  2. He was not alone, steering the Quadros.

  3. Ik dacht dat je hem bent man!
    Edit: ik vind dit gaaf!

  4. What pointing device is he using and how is it called?

  5. I’m a fpv drone pilot and the drones I fly can do pretty amazing things like flipping through a gap or diving down a waterfall. And speeds up to 120 miles per hour. Drones truly are an amazing new thing.

  6. this is outstanding.woooow

  7. Lovely and inspired. ROS has Hector drone to simulate. ROS Melodic with Ubuntu installation step is here

  8. 2019 and still want to cry…. awesome

  9. All I can think of watching this is those copter things from Half Life 2 lmao

  10. Can't wait till THE MOST HIGH destroy these PEOPLE 💯⭕⚰

  11. He said skynet, guys. It's over

  12. What makes me laugh is …. everyone ride bikes with a helmet, or use safety glasses with a weed whacker etc…then this guy staring inches into spinning blades @ 1:05

  13. Him: These are all physical models. The drone won't hit you in the face!
    Them: I hear you, but lets set up nets just in case.

  14. Mathematical modelsssss

  15. 11:48 WOW! He's a Jedi

  16. Incredible ❤️ Human are getting crazy with these drones


  18. Beyond amazing. Pizza delivery without getting lost!

  19. Learn how to make it at:

  20. Watch dog fan here haha

  21. Hello, Well done ………….

  22. "How did-"
    "Mathematical models."


  24. Impressive demonstration

  25. excelente drones congratulations !!!!

  26. Почему без перевода?

  27. This is amazing!

  28. 2019 That is very normal

  29. Gracefully handles damege=spins like a mad dog. Good luck fling fpv with that lol.


    2019: (flyable multirotor aircrafts anyone can buy with no pilot liscense) people: yawn.

    Eventually there will be mid air collisions EVERYFRIGGINWHERE

  31. 👌👌👌👏👏

  32. Imagine what they can do know in 7 years after this was filmed 2020

  33. I love my blade theory xl racing quadcopter

  34. Thanks to those who are playing their role in constructing this world rather than distructing it

  35. Skynet!!! They're coming for you humans. They'll destroy the human race because they dislike your nature. The things you see in movies are things to come in the future. Open your eyes.

  36. its cool isnt it?

  37. it's so interesting

  38. 1970: Well have drones and flying cars in 2020!

  39. WTF is an algorithm?

  40. This sumbitch would make a good preacher

  41. 10:17 – wer das gesehen hat, der ist Zeitzeuge einer der "Sternstunden" der Menschheit (Entschuldigung für "Sternstunden" , weil für diesen Ausdruck vielleicht die Astrologie Pate stand).

  42. Take away the net around and show the same over a field in nowhere …

  43. Surface looked kinda sticky when he pulled that glass off.

  44. Очень и очень круто.

  45. 6:11 i concur…. hahah

  46. Drink every time you hear mathematical

  47. This is what SkyLink by SpaceX will be used for with the future implementation of Automated Drones into the police force of the police state to be used for surveillance and etc coupled with the data collected by defense contractor Lockheed Martin to build AI drones that can fly like human pilots. They collected our flight data from a competition here in Vegas with over 300 pilots. Now they are using that data to fly against human pilots in a competition in September in Phoenix AZ hosted by DRL (Drone Racing League). Remember me when you see this in the next few years..

  48. i like nets and nylon string…. hanging around my yard….didnt batman have a net gun ….. to catch the criminals..joker penquin …

  49. 2

  50. That was OUTSTANDING.

  51. Việt nam yêu flycam đâu:))

  52. Хм, ничего интересного по крайне мере для человека 2019 года, дешёвые фокусы с дорогим оборудованием( таким как камеры фиксирующие положения белых шариков в пространстве, закреплённых на дронах, благодаря им это всё так "красиво и чётко" Сами дроны и самая малость софта)

  53. '
    what country make this R/C drone quadcopter

  54. Niente di nuovo tecnologia già presente dagli anni 1984

  55. omg, it's six years ago

  56. This drone is too smart

  57. It's six years now and my country still has ridiculous regulations to own and operate a quadcopter privately? This is outrageous!

  58. Top da hora em amigo

  59. 새로운모델인가 처음보는드론이네.

  60. I see Drones For Human Transportation coming.

  61. Drone. End of the world

  62. Ich bin sprachlos 😮👍👍👍

  63. Tjakepzzz 👌👍 Sangatzzz
    Awesome 👌👍

  64. Можно в цирке выступать 🙂

  65. Wrap me two, or at least one poor guy whose blades were cut off…

  66. Nope, “The key” is fast computers and miniaturized components. These algorithmes (obviously in a simpler form) are older than Leibniz wig. Almost all current progress is technical, I guess this is why is so deceiving. With the exception of AI :D, wich is also being used on Drones with strong moral challenges. Just saying 🤷‍♂️

  67. a ball catching drone…..zzzzzzz…….AMAZINg…….z…..and it FLIPS

  68. Liked this video until I head skynet.

  69. Trash technology or quadrotrash

  70. 유익한 영상이었어요.

  71. 6:11 "yeeeeah" noding xD

  72. Well, you morons, you used to train tigers, and now you train like quadrocopters, but you're nobody and the one who controls them is handsome and you wave your dumb parasite

  73. The birth and rise of sentinels

  74. You can not change the laws of physics, but you can simulate different environmental parameters (air density, gravity).

  75. Повелитель квадриков

  76. Теперь я знаю, откуда DJI взяла такие технологии. Они просто их скопировали .

  77. Круто. Приятно видеть там русского. Сергей Лапшин если не ошибаюсь… Чем там занимаешься?

  78. that was 6 years ago…
    where are we now?
    the future is bright, the future is dangerous

  79. Ovviamente due di loro sono italiani! Povera Italia come sta cadendo in basks

  80. … É muita Viadage … Tenho um primo que tem ropinha pra ir brincar com drone …. Pura Viadage .

  81. these are gonna be "fun" to try to defend agaisnt.. Make them huge and we have terminator

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