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The Most Advanced Robots in the World
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Duration: | 08:02 |
Uploaded: | 2015-07-22 |
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MLA Full: | "The Most Advanced Robots in the World." YouTube, uploaded by SciShow, 22 July 2015, www.youtube.com/watch?v=djKNh503jPU. |
MLA Inline: | (SciShow, 2015) |
APA Full: | SciShow. (2015, July 22). The Most Advanced Robots in the World [Video]. YouTube. https://youtube.com/watch?v=djKNh503jPU |
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SciShow, "The Most Advanced Robots in the World.", July 22, 2015, YouTube, 08:02, https://youtube.com/watch?v=djKNh503jPU. |
The most advanced robots in the world might not be exactly what you’re expecting. But they’re shaping humanity’s future.
Hosted by: Michael Aranda
SciShow has a spinoff podcast! It's called SciShow Tangents. Check it out at http://www.scishowtangents.org
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Dooblydoo thanks go to the following Patreon supporters -- we couldn't make SciShow without them! Shout out to Justin Ove, Chris Peters, John Szymakowski, Peso255, Fatima Iqbal, Justin Lentz, and David Campos.
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Sources:
http://spectrum.ieee.org/automaton/robotics/medical-robots/new-da-vinci-xi-surgical-robot
http://investor.intuitivesurgical.com/phoenix.zhtml?c=122359&p=irol-newsArticle&ID=1914477
http://www.medgadget.com/2013/09/intuitive-surgicals-firefly-fluorescence-imaging-vision-system-fda-cleared-for-gallbladder-surgery.html
http://www.nasa.gov/press/2014/july/nasa-announces-mars-2020-rover-payload-to-explore-the-red-planet-as-never-before
http://www.bbc.com/future/story/20120928-controlling-curiosity
http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/nasa-mars-curiosity-rover-autonomous-driving-mode
http://www.theroboticschallenge.org/
http://www.theverge.com/2015/6/8/8745143/darpa-robotics-challenge-winner-pictures
http://spectrum.ieee.org/automaton/robotics/humanoids/how-kaist-drc-hubo-won-darpa-robotics-challenge
http://spectrum.ieee.org/automaton/robotics/humanoids/darpa-robotics-challenge-amazing-moments-lessons-learned-whats-next
http://static.googleusercontent.com/media/www.google.com/en/us/selfdrivingcar/files/reports/report-0615.pdf
http://news.harvard.edu/gazette/story/2014/08/the-1000-robot-swarm/
Hosted by: Michael Aranda
SciShow has a spinoff podcast! It's called SciShow Tangents. Check it out at http://www.scishowtangents.org
----------
Dooblydoo thanks go to the following Patreon supporters -- we couldn't make SciShow without them! Shout out to Justin Ove, Chris Peters, John Szymakowski, Peso255, Fatima Iqbal, Justin Lentz, and David Campos.
----------
Like SciShow? Want to help support us, and also get things to put on your walls, cover your torso and hold your liquids? Check out our awesome products over at DFTBA Records: http://dftba.com/scishow
Or help support us by becoming our patron on Patreon:
https://www.patreon.com/scishow
----------
Looking for SciShow elsewhere on the internet?
Facebook: http://www.facebook.com/scishow
Twitter: http://www.twitter.com/scishow
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Instagram: http://instagram.com/thescishow
Sources:
http://spectrum.ieee.org/automaton/robotics/medical-robots/new-da-vinci-xi-surgical-robot
http://investor.intuitivesurgical.com/phoenix.zhtml?c=122359&p=irol-newsArticle&ID=1914477
http://www.medgadget.com/2013/09/intuitive-surgicals-firefly-fluorescence-imaging-vision-system-fda-cleared-for-gallbladder-surgery.html
http://www.nasa.gov/press/2014/july/nasa-announces-mars-2020-rover-payload-to-explore-the-red-planet-as-never-before
http://www.bbc.com/future/story/20120928-controlling-curiosity
http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/nasa-mars-curiosity-rover-autonomous-driving-mode
http://www.theroboticschallenge.org/
http://www.theverge.com/2015/6/8/8745143/darpa-robotics-challenge-winner-pictures
http://spectrum.ieee.org/automaton/robotics/humanoids/how-kaist-drc-hubo-won-darpa-robotics-challenge
http://spectrum.ieee.org/automaton/robotics/humanoids/darpa-robotics-challenge-amazing-moments-lessons-learned-whats-next
http://static.googleusercontent.com/media/www.google.com/en/us/selfdrivingcar/files/reports/report-0615.pdf
http://news.harvard.edu/gazette/story/2014/08/the-1000-robot-swarm/
Michael: When I say 'robot', what do you picture? If it's a humanoid collection of metal and wires stomping around as it cleans your house or offers drinks to your guests, well, yeah, that would probably be considered a robot. And if you're imagining the opposite, with a Skynet style intelligence destroying or enslaving humanity, well, they'd be robots, too. But like we've pointed out before, the word 'robot' is about as vague a term as you can get, at least in engineering. They really are just machines designed to accomplish a task, which could describe pretty much anything, but outside of the dictionary, we often take the word 'robot' to mean one of those humanoid computers cooking you dinner. The thing is, there's a whole lot more to robots than that. What we call a robot tends to have some combination of two elements: mechanical flexibility and artificial intelligence or AI. That's what it uses to accomplish its tasks. Depending on what they're designed to do, a robot might need more flexibility or a weirdly specific type of AI, and some, well, some are more successful than others. With such loose terminology, picking out the most advanced robots in the world is tricky and probably also kind of impossible since there's no universally accepted test for how advanced a robot is. It's subjective, and your list might be different, but I'm going to give you my list anyway.
Some of these are robots that already exist and are doing amazing things, and others are just proofs of concept, hints of what the future will look like. The Da Vinci Surgical Robot, for example, gets a lot of attention because it's used all over the world, but it's actually kind of weird to think of a Da Vinci machine as a robot, because it doesn't have much in the way of artificial intelligence. If you've seen that video of it stitching a grape back together, though, you know that it sure does have mechanical flexibility. With adjustable arms that can bend in ways that would break a human's wrist, Da Vinci is an incredibly flexible robot. It's also a robot in the sense that it's doing something that previously could only be done by humans. It works by using two main parts: a station with a few arms that actually operate on the patient and a place for a human surgeon to sit and control it remotely. You don't just tell a Da Vinci bot, 'okay, go remove the patient's gallbladder now', a surgeon controls every part of the actual surgery. But the Da Vinci's arms are designed to scale down the surgeon's movements to be much more precise, and they're equipped with special cameras that allow the doctor to see what's going on at the surgical site, even through a tiny incision. It's the kind of thing a human surgeon would never be able to accomplish, because there are limitations to what human hands can do, but Da Vinci's capabilities have made some surgeries, like gallbladder removal, a lot less invasive than the used to be. Over the last decade, it's changed the world of medicine and new versions are just getting better at what they do, giving surgeons greater control and flexibility. For example, newer models can be combined with fluorescence machines, where you dye the patient's blood with a compound called indocyanine green. When it's lit up by a laser, the dye emits green light, letting the surgeon more clearly see where the blood vessels are. But even though Da Vinci has lots of programming to make sure it's accurately translating the surgeon's movements, it doesn't need much AI and in this case, you probably don't want the robot to be making decisions on its own.
For the next robot on our list, which is really just the latest in a long line of robots, AI is a lot more important. I'm talking about Curiosity, the rover that's been exploring Mars since August 2012. Like Da Vinci, rovers aren't necessarily the first thing that might come to your mind when you think 'robot', but they're jam-packed with artificial intelligence plus plenty of flexibility. Mars is far away. Depending on where Earth and Mars are in their orbits, it takes between three and 22 minutes for light to travel between the planets, so information isn't being transmitted any faster than that, and it takes double the time to get a response since you have to send a signal both there and back. That's why modern rovers aren't just incredibly expensive remote controlled toys, it would be like trying to guide a remote controlled car but having to wait half an hour every time you pressed a button, a huge waste of everybody's time. Instead, every day, the mission scientists send Curiosity a new sequence of tasks to do, and it goes ahead and does them, mostly on its own. One thing that the rover has to be able to do really well on its own is navigate. The team can tell it where to go, but it needs to be able to avoid obstacles like dangerous rocks or cliffs along the way. Curiosity uses no less than eight cameras to map out the shape of the terrain three meters in front of it to plot out a bunch of different possible paths, and then it chooses the safest one. One of NASA's future rovers, called Mars 2020, is being designed on Curiosity's specs, so it must be an effective system.
But when it comes to navigating through hazardous terrain, some robots are designed to do a lot more than just roll over rocks. After the 2011 Fukushima disaster, DARPA started a challenge to motivate the best roboticists from all over the world to design robots that would be useful in natural disasters. In the DARPA Robotics Challenge, teams compete to have their robots quickly complete a series of tasks, one of which is a surprise. They have to do things like climb over piles of debris, open doors, and drive a car, which, let's face it, some humans don't do all that well either. Mechanical flexibility is important, obviously, but they need some AI, too, because the contest organizers figure that in a real disaster situation, communications won't be too reliable. So the teams have to plan to lose contact with their robot at any time. The tasks are so hard that some robots don't even complete the course at all. Some fall down and can't get back up, and others just take longer than the time limit, which for this year's challenge was an hour total for eight tasks. But the robot that took home the $2,000,000 prize did complete the course, in under 45 minutes. The robot called DRC-HUBO was designed by a team from the Korean Advanced Institute of Science and Technology. Their strategy was to have the robot transform. It can walk on two legs if you want it to, but it can also scoot along on wheels embedded in its knees. This way, when it was working on things that might have knocked it off balance like opening a door or drilling into a wall, it was a lot more stable. It also came equipped with plates on its legs, kind of like a bulldozer, so when it had to get past a pile of debris, it could just plow through it. Getting up a flight of stairs is also usually tough for a robot, because it needs to be able to see the stairs, but its knees get in the way. That's why HUBO walked up backward, spinning its torso all the way around so that its cameras had a clear view of where it was going. AI was important, but it was creative solutions in the flexibility department that won this robot the competition.
Self-driving cars, though, those are all about AI. Companies are developing fleets of them, and the mechanical part is mostly figured out. They're basically just regular cars, except with spinning sensors on top that make them look kind of like submarines with whirling periscopes. The challenge is getting them to navigate highways and crowded city streets without banging into things or people, and for that, you need lots of programming. The cars know all the rules of the road and they're programmed to apply them to different situations while avoiding hazards like pedestrians, bikers, and other cars. Google's fleet has already logged over a million km on the road, and it turns out, they're much safer drivers than humans, with only 14 minor accidents since the project started six years ago, and none of them were the car's fault. It helps, of course, that these robot cars have split second reaction times, never get tired or distracted by text messages, and they can share all those kilometers of driving experience, and you might be able to buy one as soon as 2017. Self-driving cars use a type of AI that analyzes a situation and then decides what to do based on an incredibly complicated set of rules in its programming. Each car does that all on its own. They use a combination of cameras, radar, and lasers to keep track of objects on the road, plotting the trajectories of other cars, bikes, and pedestrians. That's a lot more sophisticated than say, a Roomba.
But then there are robot swarms which decide what to do together, using something called Collective Artificial Intelligence, and in 2014, researchers at Harvard created the first real working versions, 1024 of them. They're a little more futuristic than the other robots we've talked about, because robot swarms are still very much a new thing. They're a totally different way of approaching artificial intelligence and robotics, and now we know that it works. In Collective AI, the programming is deceptively simple. Like some colonies of biological organisms, the robots are coded so that they follow a series of simple rules. This particular swarm was designed to organize itself into shapes, so the rules were basically just to figure out where you are, and if you're on the edge of the swarm, move along until you find a spot where you're allowed to be that helps make that shape. That makes each individual bot a lot simpler to program, and all of them can work together without having to actively communicate. Eventually, this kind of technology could be used in fields like construction or medicine. If someone had an infection, for instance, you could just send a fleet of tiny robots into their blood stream and have them seek out and destroy the virus or bacteria.
A swarm of tiny simple robots or a set of surgical arms might not quite fit in with The Terminator, but when it comes to the most advanced robots in the world, they're on my list. Which robots would you have included in your list? Let us know in the comments below.
Thanks for watching this episode of SciShow, which was brought to you by our Patrons on Patreon. If you want to help us keep making videos like this, check out Patreon.com/SciShow, and don't forget to go to YouTube.com/SciShow and subscribe.
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Some of these are robots that already exist and are doing amazing things, and others are just proofs of concept, hints of what the future will look like. The Da Vinci Surgical Robot, for example, gets a lot of attention because it's used all over the world, but it's actually kind of weird to think of a Da Vinci machine as a robot, because it doesn't have much in the way of artificial intelligence. If you've seen that video of it stitching a grape back together, though, you know that it sure does have mechanical flexibility. With adjustable arms that can bend in ways that would break a human's wrist, Da Vinci is an incredibly flexible robot. It's also a robot in the sense that it's doing something that previously could only be done by humans. It works by using two main parts: a station with a few arms that actually operate on the patient and a place for a human surgeon to sit and control it remotely. You don't just tell a Da Vinci bot, 'okay, go remove the patient's gallbladder now', a surgeon controls every part of the actual surgery. But the Da Vinci's arms are designed to scale down the surgeon's movements to be much more precise, and they're equipped with special cameras that allow the doctor to see what's going on at the surgical site, even through a tiny incision. It's the kind of thing a human surgeon would never be able to accomplish, because there are limitations to what human hands can do, but Da Vinci's capabilities have made some surgeries, like gallbladder removal, a lot less invasive than the used to be. Over the last decade, it's changed the world of medicine and new versions are just getting better at what they do, giving surgeons greater control and flexibility. For example, newer models can be combined with fluorescence machines, where you dye the patient's blood with a compound called indocyanine green. When it's lit up by a laser, the dye emits green light, letting the surgeon more clearly see where the blood vessels are. But even though Da Vinci has lots of programming to make sure it's accurately translating the surgeon's movements, it doesn't need much AI and in this case, you probably don't want the robot to be making decisions on its own.
For the next robot on our list, which is really just the latest in a long line of robots, AI is a lot more important. I'm talking about Curiosity, the rover that's been exploring Mars since August 2012. Like Da Vinci, rovers aren't necessarily the first thing that might come to your mind when you think 'robot', but they're jam-packed with artificial intelligence plus plenty of flexibility. Mars is far away. Depending on where Earth and Mars are in their orbits, it takes between three and 22 minutes for light to travel between the planets, so information isn't being transmitted any faster than that, and it takes double the time to get a response since you have to send a signal both there and back. That's why modern rovers aren't just incredibly expensive remote controlled toys, it would be like trying to guide a remote controlled car but having to wait half an hour every time you pressed a button, a huge waste of everybody's time. Instead, every day, the mission scientists send Curiosity a new sequence of tasks to do, and it goes ahead and does them, mostly on its own. One thing that the rover has to be able to do really well on its own is navigate. The team can tell it where to go, but it needs to be able to avoid obstacles like dangerous rocks or cliffs along the way. Curiosity uses no less than eight cameras to map out the shape of the terrain three meters in front of it to plot out a bunch of different possible paths, and then it chooses the safest one. One of NASA's future rovers, called Mars 2020, is being designed on Curiosity's specs, so it must be an effective system.
But when it comes to navigating through hazardous terrain, some robots are designed to do a lot more than just roll over rocks. After the 2011 Fukushima disaster, DARPA started a challenge to motivate the best roboticists from all over the world to design robots that would be useful in natural disasters. In the DARPA Robotics Challenge, teams compete to have their robots quickly complete a series of tasks, one of which is a surprise. They have to do things like climb over piles of debris, open doors, and drive a car, which, let's face it, some humans don't do all that well either. Mechanical flexibility is important, obviously, but they need some AI, too, because the contest organizers figure that in a real disaster situation, communications won't be too reliable. So the teams have to plan to lose contact with their robot at any time. The tasks are so hard that some robots don't even complete the course at all. Some fall down and can't get back up, and others just take longer than the time limit, which for this year's challenge was an hour total for eight tasks. But the robot that took home the $2,000,000 prize did complete the course, in under 45 minutes. The robot called DRC-HUBO was designed by a team from the Korean Advanced Institute of Science and Technology. Their strategy was to have the robot transform. It can walk on two legs if you want it to, but it can also scoot along on wheels embedded in its knees. This way, when it was working on things that might have knocked it off balance like opening a door or drilling into a wall, it was a lot more stable. It also came equipped with plates on its legs, kind of like a bulldozer, so when it had to get past a pile of debris, it could just plow through it. Getting up a flight of stairs is also usually tough for a robot, because it needs to be able to see the stairs, but its knees get in the way. That's why HUBO walked up backward, spinning its torso all the way around so that its cameras had a clear view of where it was going. AI was important, but it was creative solutions in the flexibility department that won this robot the competition.
Self-driving cars, though, those are all about AI. Companies are developing fleets of them, and the mechanical part is mostly figured out. They're basically just regular cars, except with spinning sensors on top that make them look kind of like submarines with whirling periscopes. The challenge is getting them to navigate highways and crowded city streets without banging into things or people, and for that, you need lots of programming. The cars know all the rules of the road and they're programmed to apply them to different situations while avoiding hazards like pedestrians, bikers, and other cars. Google's fleet has already logged over a million km on the road, and it turns out, they're much safer drivers than humans, with only 14 minor accidents since the project started six years ago, and none of them were the car's fault. It helps, of course, that these robot cars have split second reaction times, never get tired or distracted by text messages, and they can share all those kilometers of driving experience, and you might be able to buy one as soon as 2017. Self-driving cars use a type of AI that analyzes a situation and then decides what to do based on an incredibly complicated set of rules in its programming. Each car does that all on its own. They use a combination of cameras, radar, and lasers to keep track of objects on the road, plotting the trajectories of other cars, bikes, and pedestrians. That's a lot more sophisticated than say, a Roomba.
But then there are robot swarms which decide what to do together, using something called Collective Artificial Intelligence, and in 2014, researchers at Harvard created the first real working versions, 1024 of them. They're a little more futuristic than the other robots we've talked about, because robot swarms are still very much a new thing. They're a totally different way of approaching artificial intelligence and robotics, and now we know that it works. In Collective AI, the programming is deceptively simple. Like some colonies of biological organisms, the robots are coded so that they follow a series of simple rules. This particular swarm was designed to organize itself into shapes, so the rules were basically just to figure out where you are, and if you're on the edge of the swarm, move along until you find a spot where you're allowed to be that helps make that shape. That makes each individual bot a lot simpler to program, and all of them can work together without having to actively communicate. Eventually, this kind of technology could be used in fields like construction or medicine. If someone had an infection, for instance, you could just send a fleet of tiny robots into their blood stream and have them seek out and destroy the virus or bacteria.
A swarm of tiny simple robots or a set of surgical arms might not quite fit in with The Terminator, but when it comes to the most advanced robots in the world, they're on my list. Which robots would you have included in your list? Let us know in the comments below.
Thanks for watching this episode of SciShow, which was brought to you by our Patrons on Patreon. If you want to help us keep making videos like this, check out Patreon.com/SciShow, and don't forget to go to YouTube.com/SciShow and subscribe.
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