Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers.
In episode 6 of the podcast, the topic is: Human-Robot Interaction challenges. Our guest is Kel Guerin, Chief Innovation Officer, Ready Robotics.
In this conversation, we talk about Trends in the robotic manufacturing community, Solutions , Robotic O/S, and The Future including a vision of a world where open robotic platforms dominate and no specialized skills required to operate robots.
After listening to this episode, check out Ready Robotics as well as Kel Guerin's social profile.
My takeaway is that the fact is that human-robot interaction has not developed at the pace of technology is a challenge. We now need to remedy this shortcoming. Change is underway. Is it happening fast enough? Are the interfaces simple enough to bring in scores of existing manufacturing workers or recruit new talent? If robots truly are to make manufacturing cool again, our tools to communicate with them--and our willingness to try--both need to improve. We have a ways to go, but the direction is good.
Augmented is a podcast for leaders in the manufacturing industry hosted by futurist Trond Arne Undheim, presented by Tulip.co, the manufacturing app platform, and associated with MFG.works, the open learning community launched at the World Economic Forum. Our intro and outro music is The Arrival by Evgeny Bardyuzha (@evgenybardyuzha), licensed by Artlist (@Art_list_io). The show can be found at http://www.augmentedpodcast.co/
Thanks for listening. If you liked the show, subscribe at Augmentedpodcast.co or in your preferred podcast player, and rate us with five stars on Apple Podcasts. If you liked this episode, you might also like Episode #2, How to Train Augmented Workers, Episode #3 Reimagine Training, or Episode #4, A Renaissance of Manufacturing.
Each episode dives deep into a contemporary topic of concern across the industry and airs at 9 am US Eastern Time every Wednesday.
Augmented--the industry 4.0 podcast.
Intro: [00:00:00] Augmented reveals the stories behind a new era of industrial operations, where technology will restore the agility of frontline workers. In episode six of the podcast, the topic is human robot interaction challenges. Our guest is Kel Guerin, chief innovation officer, Ready Robotics. In this conversation, we talk about trends in robotic manufacturing, community solutions, robotic OS. And the future, including a vision of a world where open robotic platforms dominate and no specialized skills are required to operate robots. Augmented is a podcast for leaders hosted by futurists Trond Arne Undheim, presented by Tulip.co, the Manufacturing app platform and associated with MFG.works, the Manufacturing upskilling community launched at the World Economic Forum each episode dives deep into a contemporary topic of concern across the industry and airs at 9:00 AM us Eastern time, every Wednesday. Augmented the industry 4.0 podcast.
[00:01:05] Trond Arne Undheim, Host: [00:01:05] Kel!. How are you today?
[00:01:07] Kel Guerin, Co-founder, Ready Robotics: [00:01:07] I'm doing great. How are you, Trond
[00:01:09] Trond Arne Undheim, Host: [00:01:09] it's it's good to have you , Kel let's let's get right into it. You have been exploring these human robotic challenges for a while, and it's exciting to see and hear from you. What you think about the situation right now? I wanted to actually maybe just ask you quickly what is it that got you into this human robot challenge.
[00:01:33] Kel Guerin, Co-founder, Ready Robotics: [00:01:33] So I had actually spent a lot of time working with robots in a lot of different environments. So I've worked on robots that are meant to operate in space and in mining underwater as well as in a surgical setting in a hospital and the sort of. Middle ground of all of those was that all of these robots were very difficult to control.
[00:01:55] A surgical robot was ergonomically very difficult for a surgeon to sit there for 45 minutes or five hours, with the surgery and use it. I'm a mining robot with six legs. It required two people and four joysticks. And it was just this nightmare of how to actually interact with it. So it got me thinking while the technology was there too.
[00:02:16] Put a robot on the moon or put a robot at the bottom of the ocean or in a person's body. The interesting challenge for me was, is how to make the human interface to that robot. More accessible so that the expert, the surgeon, the astronaut, the miner could much more easily interact with this important device that was either helping them in that environment or being their surrogate in that environment.
[00:02:38]Trond Arne Undheim, Host: [00:02:38] And you seem to have straddle the field of innovation from both the academic side and the founder side for quite some time. Tell us a little bit about that journey. It's not uncomplicated, right? A lot of people make the choice. They're either going to be academics or entrepreneurs you, you seem to want to straddled both or have you, are you, do you have to choose now that you're running a company?
[00:03:00] Kel Guerin, Co-founder, Ready Robotics: [00:03:00] I continue to go back and forth. And it's interesting because a lot of a lot of the research that we worked on when I was getting my PhD was very theoretical, right? Not really applicable in the real world yet.
[00:03:14] I however, had an experience during my PhD where we visited a factory we, I was working on human interface technology that was very, lots of math and not really practical. We ended up visiting a factory that showed me how that technology could use in the real world. In immediately.
[00:03:35]And because of that sort of shifted the entire narrative of my my work, because I found that the problems that we were solving, where we were solving them for more futuristic things like working in space and stuff like that They could actually affect real people right now and assist with the problems that Manufacturing was having and continues to have.
[00:03:56] And so that sort of led me from a, to, to waiver a little bit away from the academic side into the entrepreneurial side, because that was the way to get that technology into the hands of others. This was something that was important because of the grants that we were on. People were very interested in seeing the federal money that was funding us, actually do real things in the real world.
[00:04:17] So we had a lot of support from that standpoint the entrepreneurial ecosystem in, at that time, Baltimore surrounding Johns Hopkins was very strong. But that's really what. Pulled me out of academia and and into the world of running a startup, because that's how I could get that technology into the people's hands that needed the most.
[00:04:37]Trond Arne Undheim, Host: [00:04:37] So let's jump straight into some of the most important human robot interaction challenges at the moment. If you look at what the robot Manufacturing community. Currently is struggling with w there, there are there's technology, there's just simply costs, but then there's also the cross-platform issue.
[00:04:55] If you were to summarize what you think are the most important of these challenges, as we look at it today in the industry, what sort of issues come to mind for you?
[00:05:05] Kel Guerin, Co-founder, Ready Robotics: [00:05:05] So it's interesting to frame that. There was really no interesting statistic that came out of McKinsey a couple of years ago.
[00:05:11]And I don't remember the exact number, but it was basically greater than 60% of all Manufacturing tasks can be automated. With technology we have today. So we're not waiting around for a technology to solve the problem. Technology is already able to solve the problem. It's really just getting that technology into the factory and that's being driven by the fact that there's a massive skill shortage in manufacturing.
[00:05:36]There's millions of unfilled jobs that we just can't find people skilled enough or familiar enough with that industrial process to fill. And therefore we. Need to automate to actually put robots in the place of those where there aren't people, because there's, it's an unfilled position to actually meet demand.
[00:05:56]This is something you saw this past year with COVID we've heard from factories making ventilator components who couldn't, couldn't find enough people to work a third shift so that they could make enough ventilators to meet demand. It becomes a very challenging problem very quickly.
[00:06:11] But the result that has is because people want to automate, and there's this desire for that. There's also a shortage of people who are able to actually put that technology in place. And that's really what drives our business is making that barrier and making it, making that barrier less. So that it's easier to put an automated work cell.
[00:06:31] Into a factory put to put a robot into a factory in a way that doesn't require a huge amount of expertise in a way that kind of unlocks automation for for the entire Manufacturing market.
[00:06:42] Trond Arne Undheim, Host: [00:06:42] But give me a sense Kel, of, this why did this problem compound, in other words, I understand that there are different, robot manufacturing companies, but why did it get to this level where the interfaces at least, you know, from the perspective of the worker are still perceived as so difficult? Is it that there really wasn't a focused on usability in individual companies? Or is it largely on the worker side that you just not familiar with any technology interface or is it a combination thereof or are we waiting for the Holy grail of solution to just realize that this is a problem across technologies? In other words, is it just the problem with this one robot that just has this technical interface that someone just needs to figure out?
[00:07:23] And it just does take those skills or is it a much more complex problem that has to do with kind of coordination across platforms and stuff of that order?
[00:07:31]Kel Guerin, Co-founder, Ready Robotics: [00:07:31] It's really that the latter that you're talking about and it comes from the fact that the people who've been deploying automation for the last 20 years have been experts.
[00:07:40] And therefore there was no need for any robot manufacturer to make their software easy to use. They just focused on making a better, faster robot. That's what they spend most of their time on. And the people who in that middle layer who are actually installing that automation. Learned the harder interface because they had to cause that's, that was their business.
[00:08:00]But there are only so many of those people and now we're feeling the fact that we do want to have people who might be more technological layman's somebody in Manufacturing who's been working there for 30 years. They're an expert at what they do, but. They have, a feature phone and they might have an email address, right?
[00:08:18]It's that type of user that now we need to cater to. And there's a huge amount of fragmentation in the robotics market as well because each brand of robot and other devices as well all use their own software. They have their own programming language. So if you learn how to use the orange robot behind me, for instance, and then you decide to go use the green robot, they're completely different. You have to learn basically everything over again, and it takes weeks or months to learn it once one of those. So that's that's really the barrier is that not only is it difficult to use, but that all of them are different. And so the need for a platform that not only makes each of them.
[00:09:00] It's the same in SIM, similarly to how each of our computers is the same, even though it might be a different brand or a different form factor, it's still runs windows, for instance. And each of those devices is easy to use, and is accessible. I can buy a laptop and just use it. I don't have to learn anything new.
[00:09:19] And when I buy a different brand of laptop, I don't have to learn anything new. That's what we've come to expect from technology. That is, couldn't be further from the truth in the robotics space until quite recently with some of the technology that we're building.
[00:09:32] Trond Arne Undheim, Host: [00:09:32] So you were, you're alluding to some of the solutions.
[00:09:34] I could just imagine that there's a myriad of we've talked about a myriad of problems out there. One of the part of the solution seems to be in usability and user interface design for, I guess even just individual robots, let's say green, and orange robot over here. But then I know in the space, there's also a much more ambitious trends.
[00:09:54]One of them I believe is called that low code and then no code is a an extremely ambitious term. But, and please, if you could explain those terms and what they means specifically to you in this robotic challenge, but before you do that, this is not the first time that this challenge has been identified, right?
[00:10:10] So there's something called ROS that I'm familiar with, which is this kind of open source system that has existed out there. I thought to take care of this challenge and then lastly, into throw a last thing into there, right? The issue of sort of standardization and interoperability across platforms, whether or not it is open source, I guess is also, at least in, in the regular computer industry.
[00:10:33] Something that you know is always advocated as a way to to solve and bridge of these gaps. Can you navigate the solution territory for us?
[00:10:43] Kel Guerin, Co-founder, Ready Robotics: [00:10:43] Yeah. Sure. So let's start with what you said about ROS, because really what we're talking about is we're talking about a platform, right? In the computer space, we have platforms that define how we use devices, windows as an operating system.
[00:10:56]We have Android and iOS that are operating systems. Those are also platforms. They have marketplaces, et cetera, but they're fundamentally operating systems in that they let the device underneath be abstracted away so that I don't need to write assembly code or all a bunch of stuff above that, frankly to balance my checkbook or browse the web.
[00:11:17]That's what an operating system does. And then what it enables is that of those applications that I end up using. So let's go back to Ross. So Ross is a collection of libraries that it was designed originally to solve a lot of the reoccurring integration problems that you see in academia when doing robotics research.
[00:11:37]And I had this exact same experience. I use ROS heavily during my PhD for the reason that there were already libraries established so that I could talk to a robot, get the data I needed out of it. And. Getting my PhD, that's really where it was born out of. And it's been slowly trans forming into more of a platform with more of a commercial and industrial focus.
[00:12:00] And that's been, it's been a long road coming and it's not quite there. But when we talk about an operating system, we're not just talking about the layer that allows you to communicate the devices with the devices. We're also talking about the things that let you build on top of it. What's amazing about Android for instance, is that with very little effort, I can download an SDK installed on my computer and build an Android app.
[00:12:27] And then within a day, have it and available to download if people want to download my app everywhere. That's the difference between. An operating system or a collection of libraries and a platform, where not only do I have a place where I can build the things that users use on top of it, but I can also distribute those things.
[00:12:48]And th and that's the difference
[00:12:50]Trond Arne Undheim, Host: [00:12:50] you used the term SDK, and I know, in the industry, that's a very familiar term, but what what does the aggravation Stanford, what does it really mean? Across the robotics community,
[00:13:00]Kel Guerin, Co-founder, Ready Robotics: [00:13:00] so a software development kit and what it really means is that the tool set, the tools are available and well-documented for you to build something on top of that platform. Android. I go to their website, everything's there. I can read about it. I can learn about it. I can download it. I can do it. I need to understand some basics, but all of the tools are there to help me do that.
[00:13:23]And robotics doesn't really have that. Especially when we talk about the industrial market, because building code that will work in a research environment and building an application that will work in an industrial setting in a factory. Are very different. And with our line of products, we're thinking about how do you solve the problem of building an operating system that will work across all of these different robots that solves that same problem, but is also industrially rated and.
[00:13:55] Commercializable, because that's why people want to build these solutions is not only to solve problems, but to monetize those solutions because people will pay for good solutions and all of those pieces have to be there. In order to have a successful platform that developers will develop on create amazing applications.
[00:14:13] Users will end up buying those applications and using them. And that gets more and more developers excited to build more and more applications, et cetera, et cetera. And you get this nice flywheel effect. But you don't have that unless you have all of those different pieces, the piece that enables the developers, the piece that gets what they make to the end user and so on.
[00:14:31]Trond Arne Undheim, Host: [00:14:31] So far though, you have addressed, the developers and perhaps the. The managers, I guess all the robotic process inside of the factory. And let's say they have these development kits. And then with your solution potentially they start collaborating on, can have lesser training time to set up the basics.
[00:14:50] Process across different robots and across different sort of processes on the shop floor. But what about these more ambitious terms then? First off there must be a lot of work there in interoperability because like you pointed out, there are many robots and they are all are quite different.
[00:15:05] So give us maybe, I guess the first is sense of. W what kind of work it has taken to, to actually bridge some of those, the very different, I would assume very different technologies, but maybe they weren't that different. They were all built on the same kind of background or what.
[00:15:20] Kel Guerin, Co-founder, Ready Robotics: [00:15:20] Yeah. So for instance, so the product that we build that does this as called for Jonas, that's our universal robot operating system.
[00:15:28] And the goal with forge was to build a set of tools that takes each robot underneath and also any other industrial device, because it's not just the robot that's doing the work. It's the grippers, the cameras, all of the hardware that's necessary to make the robot actually do that thing. It needs to do.
[00:15:45]But make all of that abstracted away so that the end user at the top doesn't care, which brand of robot it is, they just see a set of generic commands, like move or stop, and they're able to use that robot. So that does a couple of things. One it makes it so that the end user, when they do decide to switch from orange to to green, they don't have to learn anything new.
[00:16:07]If they decide the green is in big enough, they can buy or, an orange robot and they don't have to learn any new software. It's all this very straightforward programming system in order to do that, what we had to do was build the sort of picks and shovels underneath that. Provide this universal layer so that we can talk to each of these robots in the same way.
[00:16:29] And that was a huge challenge. It's something that we've worked on for several years, because each robot is different and how you communicate with them. There are some similarities between them and some follow similar paradigms, but then you'll have another one that's just completely different and you have to account for that.
[00:16:45] So not only did we have to solve the issue of making all of these robots talk a common language. For a lack of a better way of saying it, but then also what the, that common language was from the perspective of the end user. So now let's talk about the end user, right? The person who's actually using this robot on a daily basis and the application that they would use in four GOs is called task canvas.
[00:17:11] And task canvas is a building block based as you said, no code interface. So you're not writing lines of code. That's what you would be doing. If you were using any of the robots behind me natively you'd be writing lines of code in their specific language. So there's no lines of code. You just have these building blocks and each building block represents something that the robot or another component in the system can.
[00:17:33] Do move, stop. If it's a gripper, it can open and close. If it's a camera, it can get the position of a part, all of these complex things underneath, but to the end user, the person who's programming this. In the in the factory setting who might be ideally the person who was previously putting the piece of metal into the machine, right?
[00:17:53] The operator, somebody who is not a expert in automation or an expert in robotics, it's designed to be simple enough so that they can use this building block based structure. And then it's wrapped into a flowchart, which is something that everybody understands and are used heavily in Manufacturing so that now I can have I move and then I see.
[00:18:12] Wait for a second. And then I closed my gripper and then I move again. And that's four blocks that are very readable and easy to understand. And that's what allows an actual end-user to program the robot. So it's everything underneath that's giving you the, that common language. And then that easy interface, a topic that lets the average person have access to end and make these robots do what they need to do.
[00:18:37] Trond Arne Undheim, Host: [00:18:37] I guess my question at this point is first off, the way you explain it, it seems so intuitive that this should have been in place like. 10 years ago. So I guess maybe you could address why no one thought about this. And then secondly, where are we with the rollout of this kind of thing? Your product in its basic form has been out for a little while.
[00:18:56]And I'm just curious, if you look at the shop floor of robust right now and as you pointed out with COVID I understand a lot of projects have gone from like a demo state to like full rollout. So what does this all mean? For for the kinds of people who now can not just assemble this technology, we'd actually operate it.
[00:19:14]We've our operators, are they actually non-programmers or, where are we with the rollout of a truly low slash no code situation?
[00:19:24] Kel Guerin, Co-founder, Ready Robotics: [00:19:24] So we're there. We have a huge number of customers that have done this in exactly the way that I say where it has been, they've decided to put in a robotic cell, they've chosen Reddy's products for Joe S running that robot to do that.
[00:19:40] And they've been able to deploy that robot to the factory floor themselves in a manifest in a matter of. Hours or days and these were systems that took weeks or months to put in place beforehand. Great sort of canonical example. We had a system that was put in place to do machine tending, right?
[00:20:01] So you have a big CNC lave. It's taking cylinders parts and cutting them to, different shapes. And there was one gentleman who was running that machine. There were four other machines. And when I say running, he was. Putting a piece of metal in and taking it out when it was a different shape, right?
[00:20:16] That was, he was an operator. He was also in charge of programming that machine. And that's really where his key value was. There were four other machines that were not seeing a lot of use because any time he spent programming them, he wasn't making the parts on the first machine. So you see the issue.
[00:20:32] So what we were able to do is with our software, he was able to put a robot in place doing that machining task. Himself he's subsequently pro reprogrammed it for different parts, hundreds of times for different skews that they run. And he does that all himself and he, didn't have any robotics experience.
[00:20:52] He didn't have any higher education in the technology space. He's just a machinist. And, but he was able to leverage his knowledge about the product, which was profound. And use the easy to use technology to actually get the robot, to make it in the right way. And now he runs that machine and he runs all five of those other machines at the same time, because he's now freed up to do what he is really good at and what he's really valid before this machine programming tasks, right?
[00:21:19] So that's the type of example we see where a company can very rapidly get one of these systems in and have it up and running in a matter of hours and have it running production tasks in, in days. That's the differentiator from the standpoint of actually getting this stuff into the wild and it's out there right now, making millions of parts.
[00:21:40] Trond Arne Undheim, Host: [00:21:40] But you said something interesting. You said that he clearly had a deep dis operator in your example, had a deep knowledge of the product. I'm just trying to have you specify a little bit when we think about the upskilling challenge. Cause I guess there's two kinds of upskilling challenges. One is existing operators who, if we take your example, he had many years experience in a perhaps inefficient process.
[00:22:03] However he knew it inside and out. Yes. So that part. Changes, in terms of, how quickly he was able to leverage this new interface versus I guess the challenge, which I know you've also been faced with, which is you take workers who have been made redundant from an industry that is in decline, which is, there's plenty of them to choose from.
[00:22:23]They then have a dual problem, they not only have to learn this new interface, they probably actually have to learn. The process and the product the, in the first place, what are you how are you thinking about the kinds of upscaling that's needed in the robotics or manufacturing industry, and, I believe you had an an example that you tried in Kentucky, and I wanted you to talk about as well.
[00:22:46] Kel Guerin, Co-founder, Ready Robotics: [00:22:46] Yeah. That's exactly right. And you bring up a really good point because it is this dual problem of learning the technological tool set, and then learning how to do stuff with that in a factory setting and learning how to make the part. And you bring up the. Pilot that we ran at Academy, which is a training center in Kentucky that their goal is to retrain people who have been displaced by the decline of the mining industry in that region.
[00:23:14]So they have former coal miners who go to the school to learn about CNC technology. We then taught a robotics course using our software. On top of that a two week training course. And the goal of that training course was to Take their CNC skills that they had. And now give them robotics on top of that, what was interesting.
[00:23:37] And what we found was typically when you're learning robotic technology, you're going to spend two to four weeks to learn the basics of using the robot period, making it move around, maybe grab objects, but really the basics. And then you're going to spend a huge amount of time learning about automation.
[00:23:55] How do you actually get the robot to do the thing that it needs to do? Where do you put parts? How are those parts repeatedly located? How do you hold them properly? How do you design the robot? So it can grab the part in a way that because the parts changing, it comes out of the machine a different shape than when it went in all of those different considerations.
[00:24:13] They need to learn as well with our software. They learned the basics of the robot in two days. And then the rest of the two week, and then the rest of the two weeks course was teaching them about automation. Right? The rest of that two week course was as, as you said, spend on turning them into the person who's been there for 30 years, who actually understands the process and how to make it work. So by making the automation, the tool much more accessible, You can very quickly get to the learning about the industry, the process, the task that you're going to have to learn anyways, especially someone coming from a different industry and up-skilling into the manufacturing space.
[00:24:57]And that in other industries, that's not even a thing, right? Like when you go and learn to be a carpenter, you don't spend two months learning how to swing a hammer. You spend five minutes learning how to swing a hammer, and then you learn about how to be a carpenter, right? That is the progression.
[00:25:11] The tool chain in that sense is very easy to learn in robotics. We're making it similar so that once they have that set of tools to, to follow that same analog, they can, once you have a hammer, everything looks like a nail, right? Once they now know how to automate. Once they have the basics of how to do audit robotic automation, they can walk into a factory setting, not only prepared to do that specific task that they may be tasked to do, but they can also look around and go, wow, where else can we use this technology?
[00:25:44] Oh, there's a process over there. That's really interesting. I bet a robot can do that. And they start looking at the entire factory floor through this lens of what's possible. And we've seen that with not only newcomers into the industry, but also incumbents. The people who are already spent 30 years there by giving them an automation automation software that makes it accessible for them.
[00:26:06] You see this ownership that you don't typically see? Normal automation. They were doing the task before and now they're going to go do something else. And there was a robot and now there's a robot there. That's how it's been for the last 20 years now because the worker who was previously doing the task, put that cell in, put that robot there.
[00:26:24] It's theirs. They own it. And they're motivated to keep it running, to put in more of them. They have this empowerment. That they wouldn't have because it's theirs because they understand the tools it's accessible, they can do it. So it's really been transformative to see, not only. People very quickly becoming able to use this technology because of how easy our products are.
[00:26:49] But also once they do know, as I said the gentlemen at that factory, who's reprogrammed the system, hundreds of times, he's found new ways to use the robot. He's designed new gripper fingers himself. He's done all of this stuff because what is he fundamentally. He's a problem solver, right? That's his skill set is solving problems.
[00:27:07] And I've now just given him another set of tools within the form of a robot that he can actually use to solve more problems and to solve a broader set of problems. And that's what we're excited about.
[00:27:20] Trond Arne Undheim, Host: [00:27:20] Kel... I wanted to address one issue, which is that. The industry, manufacturing industry hasn't always been thought of as cool.
[00:27:28] And by cool. I don't just mean like in a colloquial sense, like it's, it's something that, that the young people don't like, that of course is its own issue, but literally there has been created this notion that there's something about this industry that just isn't competitive in the Western world, arguably robotics came in and has somewhat changed that. Where do we stand on that issue? And, to what extent do you think that these new platforms that your company and others are bringing into the, for in the U S and other advanced kind of Western countries is going to actually change the way that. We all have to see this industry.
[00:28:06] It's, there's nothing inherently backward about Manufacturing. In fact, there are a lot of technologies coming into this space, but on the other hand, there's something very complicated about to yet there is mass production, which, perhaps isn't that complicated once you yeah.
[00:28:21]How the machine tools to do it. So how do you see that the balance between, how to really look at the overall manufacturing industry and how this various, this coolness factor changes and doesn't change with the next shiny tool. So I wanted to link it to our previous discussion about this sort of obsession with a shiny tool.
[00:28:40] Now, the Manufacturing industry does have a shiny tool, but you were just saying that. Obsession around the tool itself. It really is clitoral clouding our understanding about how you can actually enact a change. So I guess it's a complicated question, where it goes, the Manufacturing industry and, is the true, cool here, just here to stay on.
[00:28:59] Is that a good thing?
[00:29:01] Kel Guerin, Co-founder, Ready Robotics: [00:29:01] I think it is. And so let's talk about competitive this first, because you brought up a really great point. Especially in the United States, we definitely saw a lot of manufacturing processes move overseas because of labor costs. If you talk to, and I've discussed this With a number of Manufacturing leaders.
[00:29:19] But if you talk to any Manufacturing leader in the United States, they'll say that in order for us to be competitive, we have to automate period. Like it's just not, it's not even up for discussion. So the ability to. More quickly deploy automation into manufacturing in the United States is a large part of bringing more and more Manufacturing to the, you back to the U S and being able to keep up with the trends because.
[00:29:46] The, there are a lot of different trends that are driving, that people want stuff that is made close to home. There's a lot of demand for customization, and rapidly and rapid iteration of design cycles require that Manufacturing is close to where things are designed. Things are designed in the United States.
[00:30:03] We need to manufacture them in the United States. So there's a lot of that desire and automation is the only way to do that at the price point that we can actually we can actually do it in the United States from the standpoint of the landscape larger than that, you're right. That the Manufacturing has had an image problem for the last 30 years.
[00:30:23]And you see that because the there's the labor force in Manufacturing is very top heavy. It's mostly sort of 45 and older. Because that's, when, back in the day, when it was when it was cool to get into Manufacturing that's when people did now that all of those people are retiring.
[00:30:41]The skill shortage I talked about is only getting worse. And, nobody, who's 21 years old. Who's graduating college is going into manufacturing right now for the most part. I think technology, it's not just the fact that we now have some new shiny thing to to attract people to Manufacturing.
[00:30:59] It's the fact that I think this year has, and the events of this past year have taught us how ma how important Manufacturing is taught people who didn't really have it in their mind's eye. Now that Manufacturing is more important, but I think what's interesting is that. Now that we're finally building the tool sets that allow people who were not in Manufacturing, who were not doing it for 30 years, who were not controls engineers.
[00:31:26] We're not so familiar with the space. We're building technology now that makes the entire industry more attractive and it's not more attractive as Oh, look how pretty it is. It's more attracted to is I can solve problems and I can make money. Cause that's what drives anybody into an industry is I see interesting problems that I want to solve and I can make money solving those problems.
[00:31:45]And you saw this sort of in the phone space, right? Nobody in 2001 was sitting there thinking about how great it would be to start a company that makes an app. For a phone, even though there were smartphones. But all of a sudden with Android and iOS, you had the opportunity there, not just the shiny thing, but the opportunity to go, wow.
[00:32:03] I can make a business out of making software for mobile phones. I'm going to go do that. There's really cool problems that I could solve in that space. That's the transformation that we're going to see in the next five years really? Is. Manufacturing being seen as an opportunity, not just something that's not, that's cool.
[00:32:23] But as an opportunity, a place where I being somebody from outside the industry can look at it and go, wow, I know a lot about cameras. Maybe there's some camera problems that I could solve in Manufacturing. Maybe somebody will. By those, because it's a problem that really needs to be solved, right?
[00:32:39] That's why people move into the industry. So creating that opportunity and that's is really important. And that's really where our products are going. The reason that we are building a software development kit on top of our software, so that developers. From outside the Manufacturing space can look at Manufacturing and go, wow, there's an STK where I can build applications for robots.
[00:33:02] That sounds awesome. They can do that. And also on the front end side where people who were former coal miners can go, wow, wait, I can program a robot. I can do that. That sounds a lot better than what I'm doing right now. So that's the idea is creating the opportunity to actually get into the manufacturing space, solve those problems and and build solutions.
[00:33:26]Trond Arne Undheim, Host: [00:33:26] It's exciting and interesting that you mentioned five years as a timeframe, as kind of a. Futurist. That is a timeframe that doesn't seem very complicated. Although I think the pandemic has taught everybody that there are these events that can happen that makes even the next five years become a cognitive challenge to even envision where we're heading.
[00:33:46] So clearly, if you think that this is a lasting change that will transform the manufacturing industry over the next five years. That's important, but if you maybe would entertain the notion of a little longer timeframe, if you look maybe 10, 10, 10 years, or even longer into the future where will we be with robotic platforms with the skills required to operate robots really with.
[00:34:13] The functionality over a robot and that's maybe stick to the, kind of the factory manufacturing space. Do you see that workers will be largely Augmented or will they be largely also I guess, automated away. And is that going to be a good or a bad thing? You long-term. We adjust simply to just finding different tasks that humans can do.
[00:34:35] And then it'll be more clearly delineated where the roles are between machines and humans and how we can collaborate.
[00:34:44] Kel Guerin, Co-founder, Ready Robotics: [00:34:44] Yeah, it's really a question of augmentation because as I said, we're so far behind the curve of having enough people to meet demand that the robots that are putting in place are not displacing anyone because there's nobody there to displace right now and even more broadly, I work with Aaron Prather. He is an executive at FedEx. And one of the things he said was they had a factory that that was processing some number of packages and they had a thousand people working there and that was 15 to 20 years ago. Now they still have a thousand people working at that factor at that processing facility.
[00:35:23] And they do three times the amount of work. That's what automation can do. And what process improvement can do. So it's about augmentation and I see a future where a lot of the tasks that people do right now, where they do have a lot of knowledge about the process, get transformed into automated tasks.
[00:35:44] But those people are still there acting as more of a supervisor capability, right? We've seen at at factories. One of our customers is Stanley black and Decker. We saw this at one of their facilities where they actually created a new class of. A job at that factory, which was basically a robot technician, somebody who had been skilled up with our software to manage the several robots that they had running those processes that person previously was sitting there doing.
[00:36:13]So now it's like an entirely new job that didn't exist. Five years ago. So I think that what people do, I think the people that are in Manufacturing, I think it's critical that they stay in Manufacturing because again, they have all the knowledgeable, how about how to make the, these products.
[00:36:28]But what they do will probably change into a more problem solving role rather than a putting pieces of metal into a machine role. You're going to see a large transition there and I think in the next 10 years, you're also going to see. A lot of new robotic technologies that redefine how these systems operate.
[00:36:49] There's a lot of work right now in the machine learning and artificial intelligence space about how to make robots more adaptive, generally, not just a Manufacturing so that they can handle more a variety of different situations and environments, because that's the main downside of a robot right now is as you program it to do one thing and within, the scope of what it's able to do it, that thing really can't change that much.
[00:37:14] Whereas if you put a person to a new situation, they just figure it out. So you're gonna see smarter robots in that sense, but you're still gonna need people to show them the ropes. And even if they do learn in a sort of scifi futuristic fashion, where you can just tell them what to do, somebody still needs to be there.
[00:37:31] Who knows to tell them what to do. It's it's. It's that. It's that thing. So I think in the near term there's no concern about that. And nobody that I talked to is concerned about about losing employees to automation, they're more interested in how many employees, they will be able to hire because they could expand their business because automation makes them more competitive.
[00:37:50] Those are the type of conversations that I have.
[00:37:53] Trond Arne Undheim, Host: [00:37:53] Fantastic. Lastly, there's the super quickly where should people go? While we've talked about up-skilling where's the best place to get skilled on this. And then lastly for you, where do you sharpen your teeth when you want to discuss about where the industry is moving.
[00:38:07] Kel Guerin, Co-founder, Ready Robotics: [00:38:07] Absolutely. So for people who are interested in getting into automation, we have created a a website called ready.academy. So that's the entire web address, just ready.academy. That we'll show you how, not only how to use a robot, but yeah. How to actually do meaningful things in an industrial setting with that robot, it's all free.
[00:38:28] You can go and sign up and start learning immediately. And that we've seen a lot of people have a lot of success with that because there hasn't been this place, especially very practically oriented towards Manufacturing where you can go and just learn about how to use a robot in the wild.
[00:38:45]It's been like I have to go to a trade school or something like that. So this is again on the note of accessibility designed to be a curriculum that is accessible. As accessible as possible. And it's something that we're also working with educational institutions to continue to develop as well.
[00:39:02] So that's the best place that if you want to learn more about the actual tasks go to ready.academy, if you're interested in learning more about our products ready-robotics.com to learn more about that the places I continue to learn I follow a lot of forums. There are a lot of really great people on social media and YouTube that I listen to because a lot of the academic papers that are out there are now have turned into content creators, which is really awesome.
[00:39:28]So it's been easier to consume, it's. When you're interested in this stuff, there's a lot of people talking about it in a lot of really brilliant minds thinking about it and finding a slice of that, that that you prefer is really, you're the, world's your oyster.
[00:39:42]Trond Arne Undheim, Host: [00:39:42] Thanks, Kel, this has been fascinating. I wish you best of luck with the next few years and hope we can stay in touch.
[00:39:49] Kel Guerin, Co-founder, Ready Robotics: [00:39:49] Thank you so much. Trond it was a pleasure.
[00:39:52] Outtro: [00:39:52] You had just listened to episode six, the Augmented podcast with host, Trond Arne Undheim, the topic was human robot interaction challenges. Our guest was Kel Guerin, chief innovation officer at ready robotics. In this conversation, we talked about trends in robotic manufacturing community. Solutions robotic OS, and the future, including a vision of a world where open robotic platforms, dominate, and no specialized skills are required to operate robots.
[00:40:22] My takeaway is that the fact that human robot interaction has not developed the piece of technology is a challenge. We now need to remedy this shortcut change is underway. Is it happening fast? Are the interfaces simple enough to bring in scores of existing Manufacturing workers or recruit new talent?
[00:40:42] If robots truly are to make manufacturing cool. Again, our tools to communicate with that and our willingness to try both need to improve. We have a ways to go, but the direction is good. Thanks for listening. If you liked the show, subscribe at Augmented podcast.co or in your preferred podcast player and rate us with five stars.
[00:41:04] If you like this episode, you might also like episode two, how to train Augmented workers, episode three re-imagined training or episode four, a Renaissance of Manufacturing. Augmented the industry 4.0 podcast.
Chief Innovation Officer, Ready Robotics
Builder, Ph.D. Roboticist, Co-founder and Chief Innovation Officer at READY Robotics, with more than ten years of experience in robotics, automation, and virtual reality. Kel is an expert in Human-Robot Interaction, usability, and user interface design for robots.