In this episode, Audrow Nash speaks to Matt Robinson, Program Manager for ROS-Industrial Americas at the Southwest Research Institute. ROS Industrial is a group that seeks to help industrial users, for example factories, leverage ROS and its ecosystem. In this conversation, they talk about Matt’s background, the need for the ROS-Industrial group and what problems they’re working to solve, ROS-Industrial’s consortium, and ROS-Industrial’s new working group.

Start

Introducing Matt and ROS-Industrial

Motivation in forming ROS-Industrial

Matt’s background

Getting introduced to ROS

Collaboration before Git

Getting to the Southwest Research Institute

Lowering the barrier to entry

Overview of SWRI

ROS-Industrial’s consortium

Just in time manufacturing

ROS-Industrial’s new working group

ROS-Industrial’s conferences

Links to share

This is a conversation with Matt Robinson, who is a program manager for ROS industrial Americas at the Southwest Research Institute. ROS industrial is a group that seeks to help industrial users for example, factories, leverage ROS and its ecosystem. ROS industrial has many parts, including a GitHub organization for code contributions, regional consortiums, and a newly announced working group. In this interview, Matt and I talk about how industry often solves problems and how those solutions can be improved with more modern tooling like ROS and get Matt's background, ROS industrials consortium and ROS industrials new working group. This is the sensing X Podcast. I'm Audrow Nash. Thank you to our founding sponsor, Open Robotics. And here is my conversation with Matt Robinson. Hi, Matt, would you introduce yourself?

Yes, absolutely. I'm Matt Robinson. I'm the grace industrial America's consortium program manager based here at Southwest Research Institute.

Yeah, would you give me a bit of background on ROS industrial?

Yeah. So. So ROS industrial is an open source project that seeks to extend ROS, robot operating system to industrial uses and applications in industrial relevant hardware. Right. So it was it was kind of conceived around 2011. And then around 2013, a consortium was established to kind of help give guidance to what we should be working on next.

And can you define industrial for me? Like what does it mean to be like, what are we targeting Exactly? With industrial? In this?

Yeah, no, that's a great question. Right. And we get that a lot, right. So there's a lot of sometimes assumptions, when you tag something as industrial in the context of the ROS industrial open source project. We are seeking to provide open source utilities that enable industrial applications on industrial relevant hardware. So that's the mean, the main components of the industrial tag, if you will, right, there's a lot of specific hardware that shows up in the automation space, in factories, and sometimes it's somewhat, they could have like a bit long in the tooth, right. I mean, like, it's very common for certain industrial industrial sectors to put hardware that they expected to be there for 1015 years. And so they're very proven pipelines to facilitate these automated processes that are somewhat unique, right? So we want to provide in your faces, needs to interact and take advantage of this robust ecosystem. And so that's where the extending of ROS into this industrial space was kind of the main component. Now that said, as part of like, kind of like our overriding themes and mission is to think about the, when people hear industrial, where are they sort of these things, I think, are they think of reliability, durability, quality, right? uptime, things of that nature? Right? So what are things we have to do is we think about the capabilities that we seek to deliver, and tools we seek to provide, how do we how do we realize those sort of attributes?

Very interesting. So going back a little bit industrial relevant hardware, how and you mentioned that it should be around for a long time, so people can plan to use it. How do you select your industrial relevant hardware?

Right? That's a good question, too. Right. So let's, let's talk about a couple of examples of what industrial relevant hardware may be right? So it's kind of an it can be somewhat ambiguous. So the industrial manipulator, right, so we think about, if you've seen like the big snapshot of like a place where they make cars and have all of the arms reaching in and there's sometimes sparks flying if it's a video, that's sort of the industrial manipulator of retargeting not like, behind me, we have a number of these other types of manipulators as well that are sort of set up to these in depending on the application can work around people. But that is also a class of industrial relevant hardware in the context of the manipulator. But we also look at things like PLCs, the programmable logic controller, you know, provided by companies like Rockwell and Bradley, and of course, Siemens. And, of course, looking at like different like sort of vision tools, both emerging contemporary 3d cameras, all the way back to Your traditional 2d cameras which have been running in factory lines for like last 30 years. That's sort of the those are just some examples of industrial hardware that we seek to help people be able to bring and merge with the capabilities that are kind of coming forward in the ROS ecosystem.

And what was kind of the problem or something that made it so you or whoever started off industrial? Like, why did it? Why did you begin it what problem kind of led to you wanting to create this organization?

Right, so, you know, my view like, and we can talk a bit about, like the whole layers and Thrall some industrial, the ROS industrial open source project was was started as inspired by actually a little bit similar to my background as well, with the group here at Southwest Research Institute, and also deliver solutions. Now, it's not like a solution provider integrator in the traditional sense, being a not for profit Institute here at Southwest Research Institute, but the group here develops like sort of like unique Hi, Max, one of a kind, oftentimes, prototype solutions that live and operate in factory environments or field environments that have been doing so since the early 80s. Up until or before they adopted ROS, very often, they would develop that advanced application with the industrial tools that were available at the time. Right, so the industrial manipulator and the control platform that comes with the Cuca, robot, or fanic, or ABB, they would develop those solutions, it gets something working that does something new and novel, but lo and behold, they had to do something similar. But someone specified a different mix, if you will, of the industrial hardware, they had to basically rewrite the software from scratch, right, because of the industrial ecosystem. The the whole stack from the hardware all the way back through how you develop applications for that hardware operates in a proprietary chain, if you will. And we'll call it a software stack. Exactly. But but all those communication, the middleware, if you will, as well as like the programming language and environments, they are all proprietary to that hardware set you're selecting. And then even certain vendors, like would kind of team up and have better bridges are complementing those companies. And so yeah, it wasn't like swappable

for all these different. So you'd make a solution. And we'd be like a mobile base, and then there'd be a robot arm on it. And the mobile phase and the robot arm, we both have kind of like their own ways of talking. So it was like a domain specific language often for using either of those. And then you would have to have software that is kind of translating between them, so that you can make them talk and do some sort of application. Is

that correct? Or you'd have to write in that specific domain? Sure, right, in that specific domain. Correct. And that's usually what happened. And that's from as well, I got very adept at scripting and, you know, vendor specific programming languages. And that's where a lot of us who were doing, you know, traditional industrial robot deployments, dating back to the early 90s, that's kind of how we came up. Right. And so, you know, the challenges is like, hey, this industrial robotic solution may offer some advantages. But it brings with it different software, different scripting languages, how how you implement applications, how you set up communications, you have to actually factor that if you were going to actually look at other other other solutions. And so obviously, the advent of this group here in front, Edwards is in the picture behind me when they went out to Willow Garage, and kind of that first discover motivator about somewhere around 2011, he created that first interoperability between Boston and Boston, but there was an Aha. So hey, I can develop an advanced application in a sort of hardware agnostic fashion, and not have to reinvent all this stuff. Because I have to do some other application with a different hardware stuff like that in the industrial robotic space. That was, that was like a real a huge one.

Yeah, yeah. So it was a reuse. real opportunity. Okay.

can you speak a bit more, so it was a big opportunity, because you could make it so that instead of using these domain specific languages for each hardware component, you could instead maybe abstract out that component and then connect to it with ROS or some other like, high level thing that you can use as middleware for this. Okay. And then that gives you the ability to just worry about you so you Your interface for this, whatever the device is, then you use it in a stack. And then you can swap it out with other components. You can swap new things in, as long as they have interfaces, you have one way of talking to them and controlling them. Right?

Yes, that is obviously the goal. Obviously, the devils in the details, always. But But yes, exactly right. And that was definitely new in industrial circles, right. And either became very good at working with like, you know, a Cuca, oriental scholar or offenen,

and maybe their own language in a sense, and a lot of

literally right, in different support. And they encourage people like when I came from industry, I mean, obviously, like, vendor X wanted us to buy all of their stuff, including their software programming environments, they were incentivized to not foster interoperability at the time. So fortunately, like, right, this notion of abstraction, which is obviously very common in the software world, was sort of not a new concept to develop industrial applications.

Now, going back a little bit, I would love to hear about your background, and kind of how you got started with all of us.

You've Right, right. So to catch up for the listeners, right, I have to confess that I'm not a software developer, right. So I came out of like, sort of like materials, joining materials, research, welding materials and metals, domain. In caught on with Caterpillar, the, the heavy industry equipment producer, and engine manufacturer, I worked in our corporate research group, and quickly got into developing the applications on robots, largely focusing in the early phases on specifically welding. Some of it pretty complex welding operations, were trying to control different things to realize very specific outcomes. And we had a lot of success in developing applications, you know, we had these this robot, right, and it was all set up and had all these extra bells and whistles. And we get something working really great. Like, okay, take that and go around the world and make it work. And then very quickly, we learned,

what do you mean, take that and go around the world and make it work? So like, deploy that scale? Or what do you mean,

but it scales relative for a caterpillar is not a, you know, not a Ford or GM, right. And so it'd be like, you know, they may make, you know, a given product, like a wheel loader, they may make it in five or six places. And the robots may be like, maybe three or four per site. Because you're only because you're not making as many wheel loaders as you're like, you know, border states. So, you know, not enough, not enough, let's say buying power to really put pressure on OEMs to play nice, not enough buying power to justify buying an exact same piece of equipment and shipping it around the world. So what would happen is

like this lighter spot, of where you're not able to scale incredibly effectively, because you don't have all the factories lined up for it. So it was fairly custom solutions. But it's also big enough that you want to deploy it 20 times or I don't know, some some larger number of times where it has to be you like all the all the bugs will come out. And it will be unreliable unless you kind of work it out. Well,

yeah, I, you know, if we scale back to just sort of a very manufacturing benefit, in particular for dealing with something that has to do meaningful work in the field, right. So like, we alert, right, it's got to lift heavy stuff. There's a tangible benefit if I can use robots to make it because the consistent quality actually leads to a better performing product that I can sell to people, right, it lifts more, it weighs less. So it consumes less gas, or diesel in the case of big equipment. And so there's a real incentive as a real marketing improved product, I can go out there and sell if I can leverage automation to produce it. Now the challenge was because we weren't we're not you know, that particular group I was working with was not, you know, they can't buy 1000s of robots, right? GM has a real benefit when they work with industrial robot providers, because they buy so many, they can make a lot of, you know, dictate some rules.

They say I want to do custom thing that's going to be a bunch of additional work. And because of the scale of it, the people making the robots are like, Okay, we'll do that. That sounds good to us.

Yeah. And I felt like obviously, obviously, there was a lot of other folks, if you will, in the same boat that I was, right where, hey, these different sites that could justify buying automation, but when it came that they couldn't necessarily buy exactly the same thing due to support like they would buy different brands because that's what was available and how

I could see why this was so funny. because if you're by different parts, because different brands are available in different regions, now you have to hook up to that domain specific thing. And really quick.

Yeah, we had an application running really well on a nice orange robot with this right sensor located on a totally different mix of hardware. And we literally showed up, I showed up in, you know, this other location and had to start from scratch. My, my, my one week trip turned into like a month. So that that ended up being one of the real resume business cases to when I was at Caterpillar to get involved with the ROS industrial open source projects. Well, I learned that aerospace companies, other heavy equipment, manufacturers, oil and gas companies, you know, ticking through a few even even tier one automotive, right? Because they have a slightly different problem than say your GM example.

We're here wanna automotive? Is that like, the really big car companies? Or I don't know what their

tier one whatever, there's automotive or, or any letters? Is anyone who provides the parts to the OEM or the person?

Okay, and OEM is original equipment manufacturing, manufacturing.

So GM, yep. Right? GM, you know, they make the car, they're the OEM and a company that's providing them like, say, the seats or the dashboard, assembly would be a two.

Okay, so the parts that go into the final product, that's the tier one, so it keeps going back. So tier two is the ones that provide the parts to tier one. Is it correct?

Okay, like, right. Now we're getting into supply chain, which is very resident in the pandemic era. Right? Yeah. So, but, uh, but but, uh, sorry, one of my speakers went out. But, but yeah, so So we ended up learning that a lot of other producers, manufacturers, people interested in adopting the benefits of robotics ran on the same challenges. And that was really insightful. And all of a sudden, we're starting to build this little industrial community,

it's like, the challenge was explicitly that most things were not able to talk well to each other because of domain specific languages or like custom hardware setup. So it was like, they were very reliable industrial devices, but they didn't play nice with other things. So developing kind of like custom automation solutions, were a was an extremely difficult task, because of this, the domain specific languages that they were

enrolled in. And I was, I would say, that was obviously very prescient, in your face a big challenge. But obviously, it also drove a lot of like, limited ability for reuse, you know, drove, so a lot of like, you know, hey, we'd fund some research in a university, and we can maybe get it to a point solution, but we couldn't really leverage it properly. Yeah. So, you know, we ended up learning a lot of this other sort of, you know, when you go back and look at, you know, how a lot of software companies have evolved over the years, the presence of open source, how it's able to be leveraged? What do we talk about? What do we mean by pre competitive IP, like all this was sort of new in some of the industrial circles, at least that I ran in? Before, before I got involved with the details with less industrial, and learning that a lot of other manufacturers had these same challenges. It was a learning experience.

Okay, and then so you were at Caterpillar? Where did you go from? So you and then you were building these kind of custom solutions for doing some sort of automation task that would improve a fairly small man, like you're making only? I don't know the numbers, but you had like 20 robots making them or something, some product, but a wheel loader, or whatever you have mentioned? Yeah. Where do you go from there?

So, you know, like I said, I worked in corporate research in we had a little automation team. And so we started basically collaborating with the team here at Southwest Research Institute to identify some potential near term use cases or business cases around like, what what does ROS really offer us? Right? Okay.

So at this time, you had been exposed to ROS or like, how did ROS come into the picture?

We ran into the ROS industrial team at a conference. Okay? And ask them we're like, Hey, what is this? Tell us about it? And my predecessor, Paul Voss, and Shaun Edwards, again, pictured over my shoulder for those watching the video. Their boss, Paul Evans, they came out to caterpillar and explained it to us, right, and then we found a way to kind of get involved and hence there was already this consortium established. And as Caterpillar, we join that consortium, right, so I was kind of the caterpillar face for the ROS industrial consortium. And I started like, kind of collaborating and sharing core stories with other members. But then how do we move the ball forward? leveraging open source and is this is this something we can really do in an industrial setting? That was still a question. Back in like, 20 2015 2014? Wow, I can't be like why we actually saw can we solve industrial problems with with ROS?

Source? Yeah, yeah. And what did to? And then how did that investigating that question go?

Great, right. So obviously, we got involved. The consortium has a bunch of other similar minded folks with similar challenges. You know, and it's not relevant. It's not narrow to like, say, construction equipment or whatever, I rattle off a couple of other industries, the Boeing, Boeing's and others, there was a documentary for our BMW not long ago. And so, you know, we got involved with a couple different pilot initiatives to kind of see if we could prove like, hey, what can we do? You know, to that point, everything we did was very, you know, I grabbed up the user interface, the Teach pendant on the robot, and I, you know, programmed it, I could script it on my computer and then loaded onto the robot. But I was still really, I'd still have to go through and tweak all those positions, like, right, you try their interface

for how to do it. Yeah. Right. So I've heard I've heard some horror stories about that. But I don't know that I really. So that's crazy. You would like it's like this big tablet? And you would like, would it be like a block programming kind of thing on some interface that the company may? Or?

It's it's scripting? Yeah, it's a scripting language. And, and this would be like, if I was more prepared, I would have probably wheeled over one of these robots who could have done it live. But but but no, it was very laborious. And they were introducing things like offline programming, but it was really just sitting at your desk or doing it on a computer. Lab and or on the shop floor?

Oh, yeah. Cuz you couldn't see what I was doing. You could just write the bulk of it from your computer.

Yeah. And you might have like, a visualization perfectly matches the physical system. Right. So that's why when we talk about the utilities that for industrial use cases, one of the ones is all the stuff around calibration. And so we ran some pilot programs during my time at Caterpillar and was like, Oh, wow, like, I could really not do this traditional industrial robot programming with this teaching with the Teach pendant or whatever, at an offline. You know, hey, we can basically do this notion of like, you know, use perception perceive things, leverage the data streams to make decisions, do motion planning, and actually execute processes that was mind blowing at the time, like in this 2013 2014 timeframe. And so we ran a couple pilot projects in parallel, like we'd already been doing work and perception, like, hey, wow, 3d cameras, this is this is really useful. And notions of segmentation, right? Like, oh, work on this and not that. In so we've been doing work with universities in that space. But again, it was really hard to scale. So bringing generalize it

and yeah, you said it was like a point solution. So it's solving one specific problem, but not, it doesn't generalize to other problems very easily.

Okay, we're x. So we started getting into like, what they called at the time, this focus technical project, which are these collaborative projects in the ROS industrial Consortium on blending, and blending is this notion of getting some sanding media. If you think about your, your wood furniture at home, like you're going to refinish it, you want to blend all those surfaces together, right? So you can repaint it, right. That's basically what we're doing with metal parts, we perceive them. If it's a flat surface, I apply some raster patterns. And then you can sit there and visualize the motion plan. And yeah, that looks reasonable go never got it. No teach pendant programming. I don't necessarily like drawing stuff on CAD files, which you know, doesn't necessarily save you time. Those are very legal demonstrations of proof of proof of concepts were able to do it Caterpillar they got really good by. That's awesome. Then from from there and continue to grow. This notion of collaborative projects and things like that. And so now, a handful of years later, I had the opportunity to kind of, you know, streaking it up to the open source Kool Aid and this idea of leveraging ROS 2 solve industrial problems. I had a chance to come here and take over the ROS industrial project here from my predecessor, Paul Voss, and I did that in 2017.

Gotcha. And how does it actually so one thing is when you're saying, like collaborative work on these, you mean basically using something like I don't know, some version control like Git or something so that programmers can work on it at the at different times in different places and kind of all collaborate towards one product. Yes. Is this what you mean? Oh,

my God, like back then, like in our life. Manufacturing Research that was all very new, like get get what? Like right? At the time like, right so that that idea of collaborating on software from different locations, we did that collaborative project and the ROS industrial sort of family, if you will, the consortium we partnered with Boeing was a performer on that particular project, as well as wolf robotics was like the solution provider out of Fort Collins, they're now part of Lincoln Electric, and of course, as Caterpillar, and we offer like little in kind contributions, like we developed our team developed a key driver for this laser line scanner. But yeah, but to your point, right, there was the first time that we had to script up stuff, put it someplace where other people can merge it in. And, and that sort of workflow. workflow is very new to a group that was very used to like, I'm developing right on the robot controller, right? I'm not, I'm not putting it someplace where it's really, truly accessible by others. And can be like, you know, you know, it could be reviewed version of, of that Git workflow, if you will. And that's, that's been a slow process, we still work with traditional industrial stakeholders that are still getting up to speed on that kind of get workflow. And that's been that's been a fun ride. As we talk about software and industrial settings, obviously, here in early 2020s. I mean, right, between the startup communities and the prevalence or emergence of ROS and people looking at industrial applications, it's becoming more commonplace. But like, in the early 2010s, it was non existent, almost. We had to figure out what GitHub was right? We have to get permission to use it. Yeah, right. Because the IRS corporate IT groups are like, Oh, the

internet? Yeah, the internet's bad. Yeah, you're putting your stuff on there. Yeah. It's kind of I mean, so I guess I have most of my background is in software, I would say. And it is shocking to me to hear that it was, it's like 2010 10 years ago, ish. That, like these kind of things that I associate, as modern workflows are not being used. But that's very interesting. And so the pipeline, but how it typically worked, it was you have several people that are working on different things, and you modularize the problem, so that each person can do or we, each entity can work on one thing and have that one thing, do it very well. And then you just combine them and in theory, it works perfectly. Is that is that kind of like the traditional way of doing things?

That's probably Yeah, so you'd have the person who's doing like the robot programming, you'd have a person who's doing like, let's say, there's some sensor on the robot that's gonna do some thinking or processing a lot, the one person who sets that up and programs it. And then you have like, say, an electrical engineer who who slash controls person who might do your PLC and control like electrical panel, and then yes, and then there's an integration sort of period of time, where all three of them will come together and try to like, make sure all their stuffs communicating properly. That's, that's actually, in some regards, still a similar workflow that we use here. And we do advanced systems as we bolted on also the software development piece, right, which, which enables us to kind of at least addressed interfaces, we can test a lot of the interfaces and message passing, you know, in simulation, we have a few more tools at our disposal than we had 10 years ago. And obviously, even though here, we're advanced, say compared to traditional manufacturers, you know, we still have to overcome some of the limitations of the industrial hardware, what it will just support, right, like, every every everyone, like no one has like it, this notion of a documented API. Not nice. Right?

So there's no application programmer interface to, like use the things kind of clearly.

Yeah, I mean, well, because again, we're going their scripting language, maybe exactly, just did not stay in our ecosystem,

right. That's kind of in our ecosystem. And that's kind of

a mantra, if you will, right. So but that's, it's making progress, right? Like, you know, we were at a conference one time, and this guy stood up and raised his hand, and he's lying. There was this time, I downloaded Solitaire and my computer got a virus. And now you're telling us to download download software off the internet and run our robots with it. And so that's where we were starting. The industrial sector is, I mean, they've been they've been doing what they do for an automation for 50 6070 years and so cases PLCs been around a long, long time. So it's right it was a real disruption to think about, you know, over and over again, some open source pieces layer on kind of just like the stuff of novel stuff to do this specific thing. But then like not reinvent the wheel. And like, Hey, we're gonna maintain it and make contributions back to the stuff in the open source. Because right rising tide lifts all boats. And there are some people that are just like, Wait, you're going to download stuff off the internet and run an industrial robot. I mean, we, it took a long time to just define open source get a consensus of understanding in the industrial community. And it was funny, I sat with a peer in Germany, he's like, You know what? Like, the whole, like, you can put open source on an industrial piece of equipment and have it do something meaningful in a factory and the whole place not melt or break down. We want that, like, we're doing that. And we are and lots of people, lots of great startups over the years, was it there's that one article, like 80% of new startups, whatever the robot they're putting out there. Like there's, there's ROS, there's a ROS something on Yeah, it's

crazy. I don't know the number either, but it's quite high, which is nuts. And it's

great, right? And that and that. And that was if we didn't done nothing else, we brought the industrial sector to the party, right, and generated some general acceptance for open source and like, Hey, you can do this, right. And this can work. And that's, that's been fun. It's been great to see that change over time, compared to where we were, we were like in the early teens, 20 times.

Yeah, I imagine it's pretty exciting to see kind of it coming along in this. And you can probably move a good bit faster when you adopt some of these kind of these different development paradigms like version control, and you can collaborate and then you can tie it with simulation, and you have all the parts integrated. So you can test them all together. Even if it is limited in like, say a simulation or something, but you still don't it's not like this one part. We're only going to test that. And then we're going to connect it to something that's also only tested by itself. Whereas you can like say all of these things are in the the gazebo simulator, and we're just going to run this control code on it and see if it does what we intended to do.

So you were at Caterpillar? Now, did you go? How did you end up at?

Southwest Research Institute? Yeah, so you know, I've been doing my job at Caterpillar, like 10% Was this open source? You know, motion planning, you know, no more teach better programming robot stuff. Like that was like, Okay. And that was the funnest part of my job, right? And I had all this other stuff. And I was like, I was kind of like, yeah, looking at different opportunities, right. So I mix it up. And the guys here heard, and they're like, Hey, why don't you come down here? And like, you know, I'm like, oh, like, run the ROS Industrial Program. Like, you got to be kidding me. I don't know anything about this stuff, right? I'm just some guy, like running some projects. Now. Like, no, no, you have that perspective of the person who hates programming. Okay, I definitely have plenty of that. And so, so yeah, I, we talked, and they found a role for me. And I was like, alright, we'll give it a shot. And so I came down and middle of 2017. And obviously, I brought a little different perspective, right? I mean, you know, I, I was putting robots on the factory floor and commissioning them and, and then like, trying to replicate successes on on certain hardware or development configurations, and trying to replicate that and really struggling. So I brought that in. So when other people had that pain, I was like, oh, yeah, we had that pain, too. And then like, obviously, I come from a pure group where, you know, when someone brings up a terminals, and they're like, bouncing between the terminals, I'm like, yeah, like people in the industry community can't do that now. Right? Because we're not software developers. Right? So there was this idea of like, what can we do to to lower the barrier to entry? And obviously, we've seen a lot of progress on that front, right between nice IDE ease between, you know, other, like just more Python, right, lowers the barrier to entry. You know, there wasn't a ton of Python stuff. When we first started poking around, but all of that helps, right? And so that the whole lower the barrier to entry is obviously, part of our mission is

just, I'm sure people know, mostly but so IDE is integrated development environment. And so that's like where you code. Often it makes things a lot easier. If you have a good IDE And then Python, maybe I don't need to define it, but just a programming language, which, for ROS, we are a lot of C++, which is low level. And we have some Python, which is like a nice scripting language. And so that's higher level easier, you can say like print, quotations Hi, and then close it, and it will print that out. And so it's like it's easier. So it makes it nicer for working, because people can just kind of see the logic right there. And it's almost like a human readable, like, paragraph kind of thing. Although it's death, almost. Okay,

so one of the big parts of ROS industrial, you're saying is lowering that barrier of entry? How are you doing that? Or like, what are some strategies you guys are working towards to try to lower the barrier of entry?

That's a great question. Right. So obviously, one of the things we do in our little consortium family is we provide training, right? And the training is constantly evolving, based on the feedback from the membership, right? So they want to they want more examples, and helps them there's like, sort of templates to do certain classes of things. Obviously, we've tried to give an example. Yeah, maybe, right. But setting up what a good example is like, we have a training on setting up a perception pipeline. Okay, right. And then we have a training class, where we leverage the perception pipeline to say, like, do a pick and place down, right, so you perceive this object, and you identify and grasp when you go get it? Right. So we have this whole lab exercise that takes place on the top, one of the pieces of hardware that are behind me. And then, so they get to like kind of actually build an application, but they have some skeleton to start with. Right? We went through an example, right, which can become sort of the template.

Yeah, that's how we can work with some something that kind of already works

correctly, obviously, like, sometimes the feedback is, well, this is a lot of copy and paste. I don't know what I'm copying and pasting. But so it's a continuous journey. And that, but that feedback only makes it better. But obviously, you know, the more you know, obviously, the issue is, you know, I mean, the tech world is rapidly evolving all the time. So new things are always coming out. And of course, what legs is the documentation that we're in the same boat where where we've been doing a lot of interesting new work and in reconstruction and different types of motion planners, we have an optimization based motion planning framework that's out there. So

are you for all these things? are you leveraging things that are in Rosu? For your navigation? Are you using like nav two, for your motion planning are using like move it? Or is it kind of custom solutions for industry things?

So where we want to, we want to stick with, with what's out there, emerging out of the community, right? We really want it's extending ROS into industrial applications. So creating like homegrown stuff kind of defeats the purpose. Now, obviously, there are cases where something special needs to emerge. And thereby, you will create that, in a lot of cases, we open sourced. Right, so one great example that comes up in our community is the emergence of Tesseract, which is motion planning environments very similar to move it, it was born out of a very specific use case. And it was chosen to open source it, because why not? Right. And it's still it's still we we leave, all of our training is still built on move it we start with movement. But then for those interested or specific applications, we have this alternative called Tesseract that, in certain situations offers some benefits. But we don't necessarily offer like, say training on it. It's sort of like, if your application sort of would benefit from some of the things here, you know, we can do some use on demand, right? But But in general, we start with, to your point, right, the NASDAQ move it and the tools they're in, we want people to because the benefit is the whole benefit of this whole open source idea is that once we start using them, we make contributions back. Right. So if we made a bunch of replicates of stuff, well, then we just spread out the contributions and they're less impactful. Right? So we want to start in use the most common tools as well. And so yes, so hence we've migrated our training over to ROS 2 as well we're trying to as I described earlier, right the in the industrial crowd is slow to move, right because they like what works. So we've been having to be very judicious and how we manage rolling out in the direction of ROS 2 but but but we're getting right. Most recently we also are trying to revisit our We're gonna phases because in the industrial side that's really lagged. But it's a good opportunity to revisit for consistency purposes, you can talk more about that. Yes, for

sure. Yeah, that's very interesting. I want to talk about that have you got before have you is one approach that you guys may do abstracting things further. So if, say, I want to move something from here to here, and from one location to another, maybe I abstract what you need to do in that to or subtract what you need to do and move it or something so that it's easier at kind of like, like, instead of like, I'm gonna do all like, I want to run this specific thing, or this set of commands in NAB to maybe like, more at a behavioral level or something like something that's, that's

like, that's actually it's interesting. Right? So that's some of the that sort of like, just kind of give a higher order kind of instruction. Yeah, exactly assist or empower the system to make the optimal decision. Yeah. Because like, let's say we have a mobile manipulator to your right, we're now getting involved and move it. I don't necessarily want to have to like, push out commands the boat, right? It needs to be a higher order. And then let the system's intelligence sort of figure out a bunch of

smart programmers figure it out once and then everyone gets to benefit from it

correct. And we are we are trying to bring to some proof of concept capabilities in that space to present to like, say the manufacturing engineer knows process, they know what they have to do in their factory, but is it going to, to your point, command driven or math, right, they're gonna have to tell it like, hey, you need to do it like this, just go do that. Right? When abstract away, if you will, that move that voice level, but that level. Next level down, we have some proof of concept initiatives going in that direction, we have put out some material on those, and some of the progress we're making. So for those interested, you know, if you when you share the LinkedIn stuff, you'll see posts about some of the outcomes from some of those group meetings that talk about some of the work going on what we call our development environments for industrial applications. And that's something we're looking to hopefully find some people to poke holes at and and try. And so we're looking for some beta testers now, we're hoping that help some of our industrial stakeholders lower the barrier to and again, that whole idea of lowering the barrier, particularly as the systems get more complex, of course, you'll not just mobile, but we'll do we do a lot with gantry based systems. And that's where a manipulator maybe inverted up that upside down. And it's an a huge gantry that has x, y, z. And it can take that manipulator through an entire volume.

I'm imagining a 3d printer with an arm instead of the printing spot.

Yeah, absolutely. Something like that. That's, that's a great example. And so obviously, of all the redundant axes, there's lots of solutions. How do you how do you search that space? Right. And so what are the tools for that? How do you prioritize using the axes? Sorry, gantry axes versus the manipulator axes? I mean, so, you know, we're trying to bring tools to kind of enable end users to

take advantage of that thing. That's interesting. I don't I don't know much about use cases for gantries with the robotic arms on them or anything. That seems quite cool. I have you. I don't. I did an interview earlier with Brett Aldrich. From Smak. Have you thought of there? Like, have you looked at SMAC for kind of like a higher level way of controlling robots for specific tasks? It kind of seems like their use case.

Yeah. So it's interesting. You mentioned Brett and snack. I had to today's Friday. So yesterday, I was at a Technical Steering Committee meeting and talking about hardware interfaces. And and how we'd like to do a new reference implementation to kind of herd the cats on hardware interfaces. In Brett Pinkney after that particular meeting, said like, Hey, we should we should talk about Smak. I was like, That's a great idea. So other than like reading, reading, like three lines about it, I have immersed myself derelict on catching up on some of my reading. I've only caught wind of Bratton his work since he was getting engaged with the Technical Steering Committee.

correct. Yeah. And obviously, like when I read his application, I was like, Yeah, this guy. This guy's awesome. For sure. So we're excited. And I'm glad he reached out to me and I look forward to learning more smack Yeah, it's probably it could be, again much. You know, we've had folks like Brett, come speak to our industrial audience. And so that those opportunities are existing and we're just trying to I have a hard time keeping up and I'm like in the ROS world more than I thought

so right. So where it makes sense. I tried to, in some of our organizations though, like stodgy or right kind of old school, they do have people that really are looking for solutions. And like to hear from these types of people, right, so we try to we do a lot of that matchmaking. Obviously, if there's a chance to collaborate with you, we'd love to see them.

Awesome. Yeah, if you maybe some help with the background, but if you're speaking with him anyway, there's a previous podcast interview with where we went into like, pretty deep detail on how SMAC works and where it might be useful. But so now you're at Southwest at the Southwest Research Institute, sweary. And you're leading ROS industrial from there, and you have a bunch of projects and a team, or what's the setup? And how does it work? And how does the organization

for great, great, right, so we have this manufacturing robotics department, here at the Institute. And they leverage all these tools in their day to day problem solving. Right? So they're kind of like, the ROS industrial developing team, if you will, are contributors. So the rest of us are open source project, but their users as well. And we try to walk the talk, right? So we take all these things, and we go solve problems with that. Now, how large

is the business model? And is it tied to a company and a bunch of things like this, they don't quite understand.

Essential, essentially, the Institute at a high level, right, which has about 11 operation operating divisions. One of the most well known is the Space Science Division, right? Because they actually have a mission control here and lead missions for NASA. There was a couple different the New Horizons was one where they kind of went by and did some shots of Pluto. Space Science, and then here in our division, right, so I'm in a department or division is three of us what unmanned ground systems are applied sensing. And then critical systems does a lot of NASA software. And of course, we collaborate with them as well to share tips and practices and where ROS makes sense. But anyways, so there's, it's all applied engineering contract r&d. Actually, when I was at Caterpillar, we spent a lot of time here doing dyno testing. Right, so about half of caterpillars dyno testing occurs here at Southwest Research Institute. It's totally vital. Sorry, yeah. So it's really taking the engine. And they basically try to run it, like so they put all these they feel they pump fuel into it and make sure the exhaust is handled effectively. But it just sits there on a stand and runs, they put it through its paces, they may, they may make the room, they may make the room very cold, and they make

very hot so they can test all the different conditions while running. I see

my anywhere. Correct, I was supporting on Highway tear three emissions at the time for modeling trucks. Tier three was at the time they were trying to address diesel particulates. So I was the materials person involved with a lot of the creation of some of the components for the that particular exhaust system at the time. And so they were running a lot of those tests here. So but it's but it's multi discipline, right? So I mentioned space science, obviously, we're manufacturing robotics, we have unmanned ground systems. So we have all these different groups. And so

an effective thing around these. Yeah, you have like, cuz i You say different domains, but I assume it's like, fairly similar competencies between the different domains or at least complementary in some sense.

Yeah. So you know, I mean, you're there's a lot of computer science across the Institute, a lot of material science folks like myself, mostly in the mechanical engineering division. A lot of mechanical engineers, a lot of chemists, we have a whole chemistry, division as well. So so but we basically think back to my group at Caterpillar, I worked at corporate research. This group had unique skills that I didn't have software skills in my Manufacturing Research Group, explicitly, I had some people could do some Python. So we would work with this team, we'd write a little contract, then they worked as like an extension, corporate r&d team. I had worked to some statement of work and help my team out. And in very much like I like to describe it, we work with somebody, we want to lead them, not just with something we give them, but their staff is a little bit better using the tools than they were before we show them. Right. So we don't just deliver them something we teach them while we work with them as part of the delivery to teach them as ons. Yeah, I mean, here we are using all these open source tools we want. We don't want to just give you a software that we will but ideally you have someone in your team You can learn it as well and be self sufficient. So you don't necessarily have to us. Oh, definitely, that's that's sort of the model here and proliferates around the institute. Right? The whole there's a tagline about benefiting science in humanity. So we try to walk that talk, right? We try to help our partners teach our partners, as well as like deliver novel solutions. The cool thing about unique about our department specifically, and our division is we don't just deliver the novel solution, but we also try to make contributions or offer things in the open source. So hence, a lot of the robot drivers, some of the calibration utilities, they they're born out of this group, specifically, as well as some of our partner groups. ROS industrial is stewarded by three organizations you've mentioned Southwest Research Institute, but I'd be remiss not to mention Fraunhofer IPA in Stuttgart, Germany and the advanced remanufacturing Technology Center in Singapore, Stuart ROS, industrial Europe and ROS industrial Asia Pacific, respectively. Those organizations also make great contributions to open source and of course, ROS ROS, too, and ROS industrial.

Can you tell me a bit about the consortium? Around ROS industrial?

Right. So in 2013, and 2013, is when it first got started, like, there's a lot you can work on, right, like so we had all these problems, just getting the robot like getting my application to work on all these different robots. But there's all this other stuff like right, should we be doing motion? To be What about perception, what to focus

on, basically, writers out there early on things that you could possibly focus on?

Okay. Yeah, my apprentice, my predecessor, my predecessor, Paul Voss, now and plus one. He, he basically was like, started, like, basically, surveying industry is like, Hey, what are some of your pain points and work? What's really working on it just naturally, sort of like, like, hey, what if we started a consortium, and you chip in a little bit, and we start building up this repository and maintain it. And for tools to enable you

to chip in a little bit, you mean, you fund a little bit so that, like, you have some sort of stake, and it funds like a few people to work on this full time, most of their time.

That's the intent of the consortium, right. So there's some level of maintenance, to keep things at least running to a degree. And so our membership dues are different. Yeah. And then, and then at enables, like some level of technical support. So one of the benefit benefits for people who are involved in the consortium, is they get some call, like, hey, help me like tech support. As well as like, you know, we do a lot of maintenance. And, of course, obviously, pushing out some new stuff fixes, new versions, etc, we maintain the Qt plugin for ROS. And different functions like that. And put on obviously, the training, it supports the training events. But that's really what the dues cover any sort of collaborative project is separately specked out and if people want to contribute income, and software or, or just fun labor, they can do that with veggie spun out separate. So the consortium seeks to provide the direction for what we do in the open source. The first thing, sorry,

its direction in a sense that they inform you of what they're working on what their needs are. But it also comes with these added benefits of you, you can you support them. And then you also provide these training things. Drink training, I don't know the courses or we may refer to it

to training events, right? Yeah, we enable them to sort of like kind of influence the agenda, like, oh, it'd be nice to have more more on navigation. Right? Oh, we generally, like we've started pushing out ROS 2 training and we got a lot of feedback that like, Hey, this is fine. But like, how do we make it run with our ROS 1 stuff? Right. So we ended? Yeah, add in like, yeah, added, like best practices with the bridge, pulling exercises, and hey, what are some things for to help us port stuff? And so that's, and that that's a key role, right? I mean, Oh, for sure. consortium, the membership, like provides this sort of, well, and because they are paying membership dues, they will definitely express their opinions. And that's right. I mean, we're sure

if it's the best match desires of industry, represented by the consortium.

Yeah. So we have like this, like, baked in voice of voice of the customer. Right. So that's been really good. And then shortly after we started the Americas consortium, Fraunhofer IPA stood up a ROS industrial consortium in Europe. They have a subset of members and Asia Pacific. Like I said, let a Singapore RTC Singapore. Were there one of your colleagues, a couple of your colleagues in Singapore I think just down the road from RTC. They support the Asia Pacific console issue and when we work all off, like a common agreement, so we have reciprocal benefits. And it's really very uniform from either outside, as well as inside. We tried to make it consistent, uniform experience, like very often often Asia Pacific member who has someone sitting here in the States, and they'll attend our training events. That's okay, that's nice. How do you?

How does it work when companies join the consortium? Is it? So is it like a fixed do or can companies though? Like, if? I don't know, I like say it's a $5,000 for one seat, or something? Does it is Can someone contribute a whole bunch and basically monopolize how it works? Or how does all I guess how do you balance different companies?

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