This article and video are part of theTechXchanges:ROS：机器人操作系统andWomen in Science and Engineering (WISE). Y你也可以看看TechXchangeTalksvideos.
Building robots isn't an easy task. One of the platforms that makes the job easier is theRobot Operating System (ROS).Open Robotics支持ROS以及Gazebo，机器人模拟环境。
I spoke with Open Robotics' Katherine Scott, Developer Advocate at Open Robotics, about ROS and her work in the robotics arena, as well as what she has seen develop over the years.
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黄：Robots are a lot of fun and they've been going on for quite a while.
Katherine, you've actually been working with robots for probably almost your whole career. Could you tell us when you started working with robots?
Scott:好吧，所以我大概在2001年开始学习本科生时就开始使用机器人。一直以来，这一直是一个偏离的事情。
I kind of tend to focus on computer vision, but always that usually leads back to working with robots. I started with Open Robotics coming up on three years ago, but I've known them basically from the start. I was friendly with a lot of people at Willow Garage prior, you know, the original creators of ROS and Gazebo or ROS and OpenCV.
A couple of years ago, they kind of approached me and said, “Hey, would you be interested in working here?” I'm like, “heck, yeah.”
因此，我住在旧金山，我从未真正对在南湾和硅谷工作。我说我在硅谷工作过的唯一地方是开放机器人。他们终于来了，说他们要我开放机器人技术，我们会让您留在旧金山。这对我行得通。我卖了。出色的！
黄：Well, could you tell us a little bit how the field of robotics has progressed since you started with it? What kind of things have you seen.
Scott:Well, it's changed a lot. Right. It's changed from early 2000. It was big, if you think about it. There's a big wave in the eighties and nineties. A very, very specific, very, very regimented robot that did like one thing. They did one thing. They did it fast. They did it well. They cost a lot of money. They took a while to install. You had a lot of subject matter expertise to do it.
这就是很长一段时间的情况，我们已经看到的是，尤其是过去，我不知道，假设五到六年，情况发生了很大变化。机器人变得更便宜。它们变得更加易于使用，并且他们变得更适应于现实世界中的情况。
So, for example, you've gone from the sort of example in the eighties and nineties that you had a car or (you were) building a car, you got a robot that, picked something up in one box and that's fixed. It's in a very specific orientation. It doesn't move. It picks it up. Moves it over. Puts it on the thing in a very particular location. You know, it screws in five bolts and you're done.
我们已经从它转移到诸如AMR（自动移动机器人）之类的东西，在这里您给机器人提供了非常通用的说明，我需要您从仓库中的a点到B。机器人可以通过此环境。
It's not fixtured. It can kind of deal with stuff happening. I can deal with someone walking in front of a box, falling on the ground that it has to go around. It has its flexibility and that flexibility has enabled a lot of new applications, new domains.
其他的例子将农业。机器人agriculture weren't really a thing other than maybe like an assembly line. We have this robotic assembly line and you toss a bunch of apples on it. Maybe, if you're lucky, it can get rid of the bad apples. Now we're looking at robots that go out in the field and we're starting to see people trying to send robots out to pick the apples and put them in the box. Then another robot takes that box to somewhere else and they get washed and then sent out to market and stuff.
And so lots and lots more flexibility and a lot, lot, lot cheaper.
黄：即使在过去的10或20年中，有很多事情正在发生变化，但是您认为机器人技术中发生的一两个最具影响力的事情是什么？
Scott:Impactful?
您的计算增加。计算机变得更快。他们可以同时做更多的事情，并且表现和速度的增加使人们能够做更多复杂的事情。我们发现了所有这些新的计算机视觉事物。
When I started my career in early 2000, it was really, really difficult. Like the unsolved problem was, I have a room, I have a camera. I want to basically be able to build a 3D model of that room. That was not a thing that was possible in 1999.
We've gotten to the point now where you can go into a room with a camera around and it builds a 3D model. The robot can understand the space it's in.
Then with some of the deep-learning stuff it's gone to, I have the space. I know what the space looks like and I know what the things are in the space and I can find different things.
I think another big change has been the big use of simulation, which was around in some capacity for quite a while but robots are hard to work with. If you're a software developer, maybe you'd write a bunch code. Press compile and the thing works or doesn't. You write a bunch, you fix it, you do that over and over again. You get stuff done really quickly.
With robots, it's harder because you got to load the code on the robot. Run the robot for it to do the thing. Check that it did the thing, did it do the thing correctly, and then try again.
因此，当您使用模拟器时，在计算机上运行虚拟机器人时，您可以更快地关闭该循环，但是从理论上讲，您也可以同时运行十个不同的机器人，以查看它是否确实有效。
It's kind of like an imagination for robots, like they can see it in their head. You can see if something's going to work before you actually do it.
So I think those sort of dual things like more advanced perception to figure out rooms, figure out things, being able to map a room and then the ability to sort of have a mind's eye to figure out where and what you're going to do before you're going to do it and whether it's going to work.
Those are probably the biggest.
也有一些硬件创新和东西。一切都变得更好，更便宜。
黄：好的。So what are you doing now at Open Robotics? And what did you do when you started?
Scott:我做很多社区外展工作。我保持网站的前进。我保持我们的论坛继续前进。之类的东西。
Open Robotics, broadly speaking at this point, has not changed that much. We're pretty consistent.
I was actually just talking to somebody about this. It's kind of diversified. So we do everything from these big grand robotics competitions we helped put together. We built the simulations for them. We built the like infrastructure to conduct the simulator or conduct the competitions. We do other stuff, too.
We make ROS, the Robot Operating System, and Gazebo. People on occasion come to us and say, I'd really like this feature or I'd really like you to help us build this part of the robot.
你是专家,你建造它,你是专家in it. Can we get your help?
We do smaller contracts sort of things where cool startups come in and they say: Hey, we're working on this thing. You guys are kind of experts. You've seen a lot of these. Can you do like a design review for us?
So we'll show you the robot. We'll let you guys poke around the code and you give us recommendations on how we can improve what we're doing. That was a really fun.
我们还有其他客户。我们在这里和那里进行一些机器人安装。我不一定要谈论所有这些，但是我们进行了更大的机器人部署。实际上，我们最近一直在研究该系统。
So one of the things that's changed fairly recently is it used to be, other than a factory, you'd have one or two robots doing very boring things.
For example, I have a robot mop and a robot vacuum. A lot of other organizations, like a hospital, might have a cleaning robot, a sterilization robot, a gofer robot, and food delivery robot. So you have all these different robots, all these different fleets, like a bunch of the same kind and they all have to work together.
他们来自不同的供应商。他们以不同的方式工作，人们需要一些编排软件，以使机器人彼此相同。它使其容易部署。这使他们很容易在环境中工作。
说你在医院里，有电梯。机器人需要能够上下电梯。好吧，您如何实现这一目标？
It was like kind of an unsolved problem and another one is you have these eight different kinds of robots and you put them in a hallway and they just do whatever they want, right?
They're going to clog up the hallway. People are going to get mad. So you have to tell them to go on this side of the street only. You yield to this robot and this robot yields to this robot and they all yield to the people and that sort of thing. Solving all those like problems that you encounter once you have a bunch of different robots.
黄：出色的。好吧，您以前提到了Ros和凉亭。你能告诉我们那是什么吗？
Scott:好的。因此，ROS代表机器人操作系统。
这是哪个？这是一个错误的名称，因为它不是操作系统，但也是一种操作系统。
Really, at the end of the day, what it is is a collection of all of the algorithms and infrastructure and tools that you need to build a robot.
因此，您在机器人中拥有所有这些不同的部分。您有摄像头和激光镜头，如果您的移动底座在地面上都带有轮子。您可能有一只必须四处走动的手臂。
It's the glue code that has to move all the communication between them. There's primitives for building basically a program that ties all that together. There's primitives for building those primitive or just primitives for building that integration between the components. There is visualization tools and logging tools. People build packages that make it easy to deploy machine-learning models on your robot.
It's all of those sorts of bits and pieces. So it's a toolbox, really. You take all the tools and bolt them all together and you build a robot.
Gazebo is a simulator. Really, what it is at the end of the day, it's like a video game that's very, very tailored to a robot and when I say a video game, I mean that you can visualize things with physics and then you can put a fake robot in that video game and have it run robot software in a realistic way and see what happens.
我们对机器人在移动的盒子和东西上绕着仓库环境进行了模拟，因此您可以拿起盒子，它们具有重量，它们喜欢分布在不同斑点的重量。
You have to pick them up in a very specific way and the lights might go out or the floor might get slippery in spots. You can kind of simulate all these different parts and see how the robot behaves.
黄：那么现在有什么热门研究领域？
Scott:The hot research areas? There's always that the deep-learning side of things because, like I said, the perception side of things has been pushing the envelope for quite a while.
So initially it was, can we build a map? How can we build a map? What does that map look like? Can we recognize things? How many things can we recognize? How well can we recognize them?
There's a lot of work now on making that process easier and more robust. There's crazy, crazy stuff going on right now. It's like I take a picture of something and then I can basically build a 3D reconstruction of it which is really an important problem to solve. So that's important.
在机器人技术中，有所谓的SIM到现实问题。您有模拟，您拥有现实世界，它们的匹配度并不完美。就像世界的复杂模拟一样。这很简单，我们如何在模拟中构建内容，以便我们知道它在模拟中起作用时，它将在现实世界中完美运行。
一系列的问题,like making that whole thing run really easily, is important. Otherwise in robotics, there's also just the field of control generally.
所以当我还是一名本科生。我实际上是在腿部机器人技术中工作的。这不是波士顿动态机器人，但非常相似，有点像六足机器人。那是非常非常研究的。
You just trying to get it to work and now you're starting to see people build real ones.
Oh, it's downstairs. So I have toy one sitting around here. So that's all control theory and so making those sorts of motions happen, particularly in stuff like picking stuff up, we sort of neglect how difficult it really is to pick things up.
Humans are really good at it and it's one of those things that is really hard to teach a machine to pick something up.
So those are fields that are actively being researched right now.
And what's cool about ROS in general is that it's cool that we can see that a student, like a grad student, build something and then somebody will sort of take that initial kernel of working code and iterate on it and fix it up and clean it up and work on it, and work on it, and work on it.
It provides this sort of pipeline to move that thing from the academic world where it's not necessarily perfect. It just kind of works to getting it all the way up to the point where it works for something like a business and that's the really cool part of our job is that we get to see that whole process of going from research and development, like academic stuff, to putting stuff out there in the real world at scale, and it's really satisfying to see that whole process happen.
黄：出色的。Well, thank you for filling us in and your work in Open Robotics and what's been going on for the past few years. It was really interesting.
Scott:别客气。
