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Robot Heroes 32 Bit Crackl


Emerging from the dust cloud is a humanoid robot called Valkyrie, NASA's only hope. With the right programming, Valkyrie can patch that air leak, deploy a new solar panel, and realign the antenna. But this level of robotic finesse has never been attempted.




Robot Heroes 32 Bit Crackl



The disaster scenario you just heard was imagined by NASA, back in 2015. They laid it all out as part of their space robotics challenge. Then they invited anybody and everybody to try and solve it. How do you program Valkyrie to execute all those fixes? It sounds like the kind of challenge only huge teams of people can tackle, but that stay-at-home dad I mentioned, Kevin Knoedler, he really figured it out. He won NASA's challenge.


And Knoedler never had access to a Valkyrie robot. He figured everything out from his kitchen desk while taking care of two kids. He could do that because robotics has opened up. It's now a software-first field, a field where anybody with a laptop and the right know-how can be a hero.


This season, we're exploring the difference between robot fiction and robot fact. What did we imagine our robots would be, and what did they turn into in reality? In the movies, robots are often designed and controlled by a secretive elite. We imagine that you need endless resources and powerful institutions to bring something like WALL-E and Johnny 5 to life, and that's not entirely wrong, but we've discovered that a leap forward in robotics doesn't always require expensive hardware and giant labs. It can happen in the free and open world of software.


Kevin Knoedler lives in Newbury Park, California. When he won NASA's space robotics challenge, his kids were 9 and 11. When they were younger, he could only do robotics work when they were asleep. Now that they're in school, he's got the bandwidth to save a colony on Mars.


In between helping with homework, Knoedler is able to take part in major robotics challenges because he can take advantage of new software that's revolutionized the field, opening it up to people like him.


It really is a common standard that a lot of robotics packages are built on. And so, rather than having to integrate and find what you need, a lot of that is already integrated and working within ROS.


Just as important as that toolkit though, there's a powerful new simulation software. That NASA contest, for example, was a simulation contest. Meaning, nobody had to build a physical robot. You didn't even need to have access to one of NASA's Valkyries. You could solve the whole thing using simulation software for the desk in your kitchen.


When you're talking humanoid robotics, for example, every time you run the humanoid robot into something or fall over, you can do tens of thousands, or hundreds of thousands of dollars of damage. In Gazebo, you can rack up those damage charges and not actually have to pay that bill. You can get that learning without having to pay all the costs in terms of breaking things.


You might be wondering, how real are these simulations? If it works in simulation, do we know it works in real life? Or are we just playing video games? Well, Knoedler had the opportunity to go to the New England Robotics Validation Location, where he ran his award-winning code on an actual Valkyrie robot.


And it actually ran. We got it running within the first day by the support of the staff there, and the quality of the simulation from Gazebo. And so rather than taking weeks or months to bring up a task like that on a humanoid robot, it was done in a day. And so that's really one of the big powers of Gazebo.


Now, before I paint too rosy a picture, I should point out that Knoedler is a graduate of MIT. He's got skills. He's put in the work. And as much as robotics is opening up with tools like ROS and Gazebo, it's not all the way there.


ROS is certainly accessible to anyone who's willing to put in the time and effort. It's just that if you're doing it by yourself, it's not intuitive. I think that the general problem is that ROS is a community project and it's designed within the community, for the community, and that community is people who generally are already robotics experts.


If you're actually a beginner and you just want to have a good starting point, there are all kinds of robotics companies and products who are happy to help you with that. LEGO, for example, has a really robust education program.


That's LEGO, as in colorful building blocks. They have a robotics line for the uninitiated. And Ackerman has another warning for those who want to get into robotics. Even while you capitalize on all that software, don't forget that hardware isn't obsolete. The real physical world still matters, and that real world is full of chaos.


We can't simulate that. Our physics simulators just aren't good enough. So, no matter how well your robot does in a simulation, the simulator itself is just not a good representation of the real world.


There is certainly a huge gap between simulation and actual hardware. Hardware, it's a little bit of a cliche, but people say that hardware is hard, right? And no matter how much work you put into your simulation, there is still going to be a gap there, and the size of that gap really governs how much you can learn from the simulation, how useful it is to keep doing stuff in simulation before you say, "Okay, we really need to get on a real robot before we can make more progress than we have."


Hardware does matter. And that's why Ackerman has been so happy to discover something called the TurtleBot, a low-cost physical robot that uses ROS and lets amateurs like Ackerman run their software in the real world.


It moves, it thinks, it senses. And it's a great way for a university course, or even a high school course, to say, "Look, we have this hardware now, and our students can work in simulation, then actually test out what they've been simulating on the real robot and learn about that gap."


Devices like the TurtleBot show you in a visceral way whether your slick algorithm is as slick as you thought. Students can learn more, entrepreneurs can prototype their inventions, and every robotics simulation gets a chance to prove that they're not just strings of abstract code, they're blueprints for a revolution.


Hardware in robotics is almost like a fact checker. A way to prove that our software stands up to the endlessly complicated world that we actually live in. But that doesn't mean simulations aren't practical. Sometimes, they're the most practical, the most effective approach you can take.


If you're trying a new algorithm, you may just break that robot. It can cost you millions of dollars if you make a mistake on your algorithms, right? So you really don't want to be trying new, crazy things in a physical robot.


Louise Poubel is the technical lead for ignition over at Open Robotics, where they help people simulate before they build. And she's been finding that simulation is not just for indie robot enthusiasts like Kevin Knoedler. Every player in the field, no matter how large or how well funded, has come to rely on simulation software. I mean, think about how simulation levels up your work.


If you are developing a robot that is very expensive and you have a large team, not everybody can have access to the robot at the same time, but virtual robots are free. You can duplicate them, each developer can have their own copy of the robot running, and they're multiple copies, right? Running on the cloud, running in their own computer.


Imagine if you're developing algorithms for a fleet of quadcopters. Imagine trying that in the real world. Every single time you have to start up 50 different robots, and one of them doesn't do the right thing and breaks, and then you have to go and fix it. In simulation, you just restart. And you start from zero. It's so much more convenient.


Now imagine you're trying to develop a helicopter that can fly on Mars. When NASA created a flying robot called Ingenuity, the sidekick to their Perseverance Rover, they needed it to fly in the Martian atmosphere, which is way thinner than the atmosphere on earth. By testing their helicopter in simulations, NASA scientists could see how it would fly "on the red planet." And it worked. Ingenuity made the first Martian helicopter flight on April 19, 2021. But whether the robots are an earthling or a Martian, they're going to encounter something that a simulation couldn't prepare them for.


Things in the real world... they are not perfect. They have faults. Parts are not exactly the size that they are supposed to be. One common thing that people always talk about is how hard it is to make a robot with two wheels just go straight in the physical world. Because you would say, "Give both wheels the same speed," and the robots are just going to go straight. But the wheels, they never have the exact same size, the exact same friction.


So, there will always be a step of fine tuning for the physical robot. That's often becoming shorter and shorter to do this fine tuning, especially with people doing things like domain randomization in machine learning where in simulation, you don't test just one scenario. You can test thousands of scenarios.


So say you're working on that two wheeled robot she mentioned earlier. By simulating a hundred different levels of friction, you can quickly try those wheels out on 100 different surfaces, making sure your algorithm applies to each one.


That's another win for big organizations, because when crowds of amateurs come join the party, their breakthroughs, their best practices, their hundreds of tiny advances, push everybody further. An open-software-focused robotics field isn't just cheaper and faster than a hardware focus field would be. And it's not just handy for amateurs. It's actually more powerful across the board.


The worst thing that could happen is that a small group of people, all similar to each other, develop robots and they ship these robots to everybody else in the world, and just impose this view and the needs of these small groups of people onto everybody else. I think it's really important to democratize it a little bit more.


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