Philip English: (25:50)
Okay.

Thomas Andersson: (25:58)
Okay. So let’s kick off then. Um, I think we’ll get a few more attendees as we go along. Um, and like comments can also take part of the recording. So this is a recorded, um, webinar. We’ll put it on YouTube after this session, so you can also, um, look at it after them. So hello and welcome to the second, um, TLA webinar. Um, my name is Thomas Andersson. I’m the co-founder of TLA robotics, and one of the six group leaders I’ll be very brief so we can get on to the exciting part, which is then the company presentations. So a little bit about tech, London advocates. So TLA for short, it’s a voluntary organization, uh, that was originally set up to promote the tech ecosystem in London, but the group has now expanded. It’s got several different working groups. Um, it’s called, uh, chapters across the world as well. So, um, it’s a really big group. That’s about 10,000 members in the UK alone. Don’t know if you want to join the group it’s pre um, um, I should share my screen as well. I just remembered,

Thomas Andersson: (27:12)
Um, where is my sorry guys? It’s coming up. I would go, yeah.

Thomas Andersson: (27:30)
All right. I’ll go on. I will share that in a bit later, so you can see the email address as well. So actually the email address is T L a dot robotics@gmail.com. So joining is free as well. Um, so the TLA robotics working group was set up in April, 2020 with the purpose of encouraging and promoting the robotics and automation equity system with a focus on the UK and Europe. Um, we have three aims to encourage investment in robotics and automation to increase adoption of robotics and automation, um, in the UK and Europe, especially in the UK and also thirdly, to improve the gender balance that we see across the, um, um, robotics and automation, um, uh, sectors as well. So when it comes to investments, um, so what I’ve seen in my work, I work a lot with, uh, investors. We see that, um, most of the investments in robotics actually is going to US and, um, to Asia as well right now. Uh, let’s see if I can share my screen here. Oh, there we go. Um,

Thomas Andersson: (28:42)
So in one recent project I’ve done it’s we found that, um, 80% of the companies or 60% of the companies were based in Europe, uh, 14% of the companies were based in the U S but us companies take an 80% of all the investments or they attracted that investment. Um, so yeah, I should also add that our medium to long term aim is to organize physical events, but that’s obviously been hampered by the, um, uh, COVID as well yet. So, so what we can see here is then on the screen here, here’s the team, uh, that makes up, um, TLA robotics. Uh, I should make a note that we can, um, we do questions, uh, during this, um, the presentations as well. So our team members, they will be able to answer any of the questions. If it’s a question with particular focus on one of the companies, we can feel that as well to the company, just so you know, uh, with that, um, I really want to say big, thanks to Philip at, um, robot center who are sponsoring the zoom hosting for this event. And without this, we wouldn’t really be able to do this, um, these volunteer. So with that, I’ll stop sharing. Um, sorry. I had some problem with that, um, over to you and then Philip.

Philip English: (30:08)
Cool. Thanks, Thomas. Uh, thank you very much. Now. I always a big fan of these events. Uh, I’m just gonna share my screen as well. And uh, let me just go presenter mode.

Philip English: (30:29)
Okay. Right, can everyone see my screen? Perfect. Let me just move this as well. Cause that’s in my way. Brilliant. Um, right. Yeah. So, um, my name’s Philippine English. I am a chief operations officer at robot center, um, a collaborative robotic integrator. Um, I’ve personally been fascinated with robotics ever since I saw my first movie when I was a young child at the cinema, uh, which was uh short circuit. If some of you guys can remember that one, uh, Johnny five. Um, so, uh, since then I’ve, uh, I’ve always had a passion for, uh, RO robots and, um, as we getting closer to the real life, uh, Johnny five, um, so a big part of that would be to do with software. Um, and this is why I’ve put together the five software trends. Um, so with software being famed for being fast pace and an innovative, uh, the future of robotic software is started wanting to see unfold. Uh, so these are the five trends that we’ll put together for you guys.

Philip English: (31:37)
Okay. One second.

Philip English: (31:50)
The cloud starting with the cloud trend one. So the cloud will only get bigger over time. Uh, the, the use of computing with cloud storage and other technologies that allow for higher levels of human robot interaction and learning, uh, is contributing to the robotic transformation of companies. A more powerful robot solutions are growing thanks to cloud technologies. They give the ability to handle heavier computing processing task, which basically enables a more powerful, powerful and cognitive collaboration. And this greatly increases the available data to share with machines and shamans. Uh, so always know, um, it should mean that prices should drop for consumers and a software functionality is expanded and refined. So that’s trend number one, trend. Number two, we’ve seen is a Python is still the dominant, uh, in coding road realm. And, um, basically Python is on a roll right at the moment.

Philip English: (32:48)
And according to statistics, um, it’s grown rapidly to become one of the top languages in robotics, uh, mainly because, uh, both Python and C plus plus. So the two programming languages found in Ross, um, partly has a huge number of free libraries. So you’re not gonna have to reinvent the wheel. And, uh, it’s generally easy to use and save time programming. Uh, and then with, with more and more robotic friendly electronics now supported Python, um, out of the box CG Rossi PI what going to continue to see a lot more Python software and robotics, uh, from the new generation of developers around the globe,

Philip English: (33:28)
Trend three Is artificial intelligence will only get better over the next few years, um, with, uh, artificial intelligence and robotics proven to be a powerful combination for automating tasks and processes. Um, AI and robotics gives flexibility in steps and actions and enables the robots with learning capabilities in various applications, uh, artificial intelligence and robotics market expenses register a compound annual growth rate of a 28% for the forecast periods of 2020 to 25. So that’s interesting to figure. And so all in all artificial intelligence in robots offers companies new opportunities to increase productivity, make work safer, and save people valuable time.

Philip English: (34:12)
Okay, Is the internet things, um, is set to grow and grow. And with the internet of robotic things, IOT set to be a $20 billion market by 2024. Um, I found a great description of, uh, IOT from ABI research, which is, um, internet robotic things as a concept where intelligent devices can monitor a fence few sensor data from a variety of sources, use local and distributed intelligence to determine best course of action and then act to control or manipulate objects in the physical world. And in some cases while physically moving through that world. So, uh, Sony see what the, uh, incident robotics thing we’ll have a bit slave to 2021.

Philip English: (34:58)
Last one is trend number five. So, uh, mixed reality, um, might be something to keep an eye out on. Um, industrial industries uses of augmented reality and virtual reality in conjunction with robotics continues to grow, uh, manufacturers, militaries and healthcare providers all look to find new uses of this technology. Uh, as a rate of growth is projected to continue over the next coming five years with practical uses of the technology, continue to develop an existing users, move into further maturity and interesting fact, found by this one is that as executive that 75% of mixed reality, and we’ll be due to be on mobile by 2026.

Philip English: (35:40)
So that was just a quick overview of what we’re seeing on the market. Um, if anyone is interested or wants to know more, then please feel free to reach out to me. Um, we are keen to get people on our first step of our ROI methodology to find out and research what’s possible. And, uh, lastly, um, the Robot center team, uh, we, we all grew up watching Scifi films this both seeing envisions of utopian features and dystopian features. So we want to be architects of real positive future that is apparent supported by robotic technology. And so we aligned the global goal number nine, which is to build resilient infrastructure, promote sustainable industrialization and foster innovation. And we support charities that are aligned to this. And for that, I will pass it back. So the first speaker.

Thomas Andersson: (36:33)
Excellent. So, yeah, thanks Philip for that. Um, without, so we move quickly on to alias robotics and, um, Endika from Spain.

Endika Gil-Uriarte: (36:44)
Hello everyone. Hello, Tom. Thanks very much for raising the invitation and in particular to Philip for sponsoring this opportunity. So very quickly, may I try to share my screen and please do confirm that you can see me and hear me properly.

Endika Gil-Uriarte: (37:07)
That’s okay. Can you hear me? Can you see me? That’s fantastic. So there we go. So, um, it’s Endika Gil Uriarte CEO of alias robotics and alias robotics is a robot cybersecurity company. We are a company focused in these market niche and we take these, uh, from the robot B6 proxy to cybersecurity of robots and robot components in particular, abs robotics was founded upon previous stories in robotics, and we do have the experience and we do have the niche expertise that it takes to tackle the cybersecurity of these robotic systems. Now it has been came very clear from Phillips. Um, talk before that we live in the era of robots and these one hub on the is happening. Although we must say that the, these are very early days in robotics with these, uh, down of an industry that will, uh, follow up in the coming years and decades and probably millennia.

Endika Gil-Uriarte: (38:13)
We see robots every day working with us in our homes, um, performing professional tasks, but more particularly and more let’s say intensively, we see robots in our industries industry that is now trying to position in towards the industry for paradigm where the connectivity is key and we’re older components. So just cyber security becomes critical. Now there’s some public case studies that we’ve been publishing as alias, robotics vaccines, 2018 showing, um, the big thing, we’ll say the landscape that is happening right now in robotics. We normally say that it is happening the very same note learned lessons that happened in other IT industries at the very round of them. And the let’s say cybersecurity lessons are not learned. And the cybersecurity status of robotics is a thing that needs to improve, but it’s better to see something rather than saying it. That’s why I brought to you some videos with this little bottom line of do not trust robot, that they want you to take us and advice.

Endika Gil-Uriarte: (39:32)
Um, let’s say, um, for the fault, and this is something that we have been able to do through manipulating remotely, the safety system of a very popular autonomous mobile robot. Now, alternatively, an attacker could exploit, present vulnerabilities, as you can see in the top, right, to retrieve the map of a sensitive industry. In this case, you can see in there the headquarters of Alias, robotics, but in [inaudible] States, Spain, alternatively, um, the industrial manipulators are not at attack free entities and attacker could exploit the network attack vectors to Ramtion or alternatively use High the robot by using a simple USB via, exploiting the vulnerabilities persent on these industrial colaborative manipulator. Now this is why alias robotics has built the robot immune system, our robot endpoint protection platform for robots. This is robot software that acts like a next generation antivirus that these installed directly into your industrial robots. We do support the top sales industrial robots, and there’s a list that these public in our web, but please do ask us if you, um, find, uh, if you want certain information for your robot, this is how you operate. Ris Ris gets installed into the teach pendant or in this case of this universal robots, industrial robot, and you train it for a certain period of time. So it learns about the usual pattern of life within this robot, outside these training phase, then you have a fully intelligent detecting system to monitor your robot section.

Thomas Andersson: (41:35)
That’s a second slap.

Endika Gil-Uriarte: (41:37)
Okay. So the biological inspiration behind the race, you can find these out there and there’s a flexible licensing associated to it. Uh, following research and development, professional and certif licenses, according to industrial security standards, we do provide some security services as well, so we can help throughout the security process to companies. And please do contact us in our locations in Spain or in Boston. And, uh, I would like to thank you again and stay safe, stay secure.

Thomas Andersson: (42:14)
Excellent. Thanks for that. Uh, and they can, can I just remind all the attendees that, um, taking screenshots, it’s a really good way of, um, capturing if you want to contact anyone with emails and so on as well, that’s going onto the screen, um, with that, uh, we’re moving on to Owen and slam core from the UK. So over to you Owen.

Owen Nicholson: (42:39)
All right. Thanks Thomas. Awesome. So let me just share my screen and we’ll jump straight in. So, uh, okay. I’m looking for sums up from people. Is that, is that coming across? Okay. Can I jump between the slides? That’s the question. Okay, cool. Okay. So, hi, um, my name is Owen. I’m the CEO at slam core. Now robots, uh, struggled to cope with change. So w when the lighting starts to vary when the structure changes and when there are too many people walking around, it’s essentially when the world gets a bit too real. Um, even today, robots struggled to answer the following three questions. Where am I, how far away are things and what are they, and these others, the three questions of spatial understanding and the biggest cause of robotic failure is when a robot gets the answer to one of these wrong. Now, this is a problem that nature has already solved.

Owen Nicholson: (43:35)
And there’s a reason why nearly every animal in the planet uses vision as it’s called sensing modality. If we take a camera and fuse together, simple data such as from a low-cost sensors, gyroscopes, and accelerometers, and we optimize that software to run on low level, uh, low level, uh, Silicon, then we can deliver commercial grade spatial understanding on hardware that’s actually available today. And this is exactly the approach that the AR VR industry has taken already. We here, we actually see three of probably the most advanced spatially aware consumer slash early stage industrial products on the market today. And they all fuse low-cost gyroscopes and accelerometers with vision to tackle these three questions. Um, but these tech giants have all heavily optimized that algorithms to only run on their specific industry, uh, for, for their specific hardware. Sorry. So the, the robotics industry is made up of thousands of niche verticals all with their own technical and commercial requirements.

Owen Nicholson: (44:34)
We don’t need a single solution that works well on one hardware platform. We need solutions that are flexible configurable, and allow us to try different hardware combinations to find the one that works for us. Well, unsurprisingly, that’s exactly what we’re doing here at SLAMCORE. So we actually span out quick bit of history. Uh, we span up from Imperial college about four years ago, um, founded by absolute world leaders in the field of machine vision. And after multiple funding rounds led by top investors, we’ve now built an incredible team of, um, 25 staff from 17 nationalities around the world together have produced 50 patents, 500 papers and 50,000 citations during that time. So, uh, they’ve been busy and after four years of development, um, I’m extremely proud to tell you that the slam core spatial AI SDK is, is hitting the market. So developers can use this, create their own vision based solutions with our proprietary algorithms at the core.

Owen Nicholson: (45:28)
So our public SDK is available for free, and we’ve teamed up with Intel to make it out of the box compatible with the real sensitive 435 isensor, if you’ve ever used that. And through our pay to play vision with program, you can also gain access to other sense of configurations and build for arm architectures, such as the Qualcomm Snapdragon, Nvidia Jetson. Um, what I’m super proud of is the raspberry PI to get this running on that is a huge achievement. Um, but let’s just take a bit of a closer look at what, where we’re providing. So the first thing as I said is the robot needs to know where it is in space. So our algorithms analyze each frame from the Intel sensor. And, uh, you use that to build a centimeter accurate map of the key points in the environment while simultaneously calculating the position of the robot relative to those points.

Owen Nicholson: (46:12)
That’s what slam stands for in slam core. So here we actually see it running on a remote control car, building a point cloud outdoors while positioning that car in space to send to centimeter accuracy all in real time on an arm CPU. Now, second, a robot also needs to know what the shape of the world is, so it can navigate effectively and not crash into things. So our solution answers this by using the same Intel sensor fuse and the depth information generated by the infrared depth camera and fuses that into a 3d map, again, in real time on an arm CPU, which can be used for path planning and obstacle avoidance, but for truly Spatial and machines, robots need to not just know the shape and the position of the world, but they need to know what the objects are. They need context.

Owen Nicholson: (46:56)
And is that a person? Is it a chair, a wall, a ceiling, um, we’ve actually developed a proprietary pan optic neural network, which segments out to the objects and categorizes them all in real time. Ultimately, as we fuse the three levels together, this will allow the robot to identify objects and position them in 3d space and time. So this will really get full level, um, spatial understanding to the robots. Um, and the great thing about what we’ve done is in the past, it could take months, maybe years to build a great vision based system, if at all. And we’ve actually reduced this month, this from months to minutes, if you head to our website, sign up for an account, you can download the SDK and be off. We will need to approve you first. So please request access on our website. Um, as long as you’ve got the hardware we support, you can be up and running in less than 30 seconds.

Owen Nicholson: (47:41)
So, and actually you can see for yourself and the time it’s taking me to present this slide, that was not an edited, not sped up. That was actually me going on a fresher printing machine, installing it from scratch. So in my last kind of slides, um, I really do believe that we’re in a new era for autonomous machines. We’ve already heard that, and we are actually committing to open up this, uh, technology to that, to the world, um, from hackers to tech giants, from small companies to multinationals, the more companies we have playing in this space, the more this will drive innovation and ultimately allow us to see the true potential of robots for a force for good in the world. And we want to be a huge part of that. So if you want to join us on that journey, please reach out. I’m happy to talk anytime.

Thomas Andersson: (48:22)
Excellent. Thanks a lot. for that one um, quite a condense, uh, presentation, uh, interesting. Um, without an way we move over to Fizyr and, uh, Herbert, uh, in, um, Poland, Netherlands.

Herbert ten Have: (48:37)
Yes. Good afternoon everybody. Let me share my screen. Can you see my screen? Yes. Sums up. Okay. We’re a, scale-up in the Netherlands founded by professor Martin Visha robotics professor. He has an academic, a few of the world, and I started this company Delft robotics a few years ago. And we were in the business of logistics, enabling robots to cope with variation, variation of items in shapes and sizes. So everything you buy a line currently is being picked by humans. So if fulfillment order picking, et cetera, then it’s, it’s spec gets into a box or back. And it’s also handled by humans. I’ve got a short video to show this, and this is it.

Herbert ten Have: (49:33)
So this happens all around the world, seven times 24 hours, where humans have to pick parcels. These are big parcels, which you can imagine all sorts of small parcels from China are all being picked by humans day in, day out on average, a parcel from DHL is being picked at least eight times by human up until 16 times. So in this case, they’re all be placed on the sorter, and then the sorter is being scanned in scanning tunnel. And then it’s being delivered to a, to C area where they need to go. So this is up till now. And you can imagine that, um, in times of Corona, uh, it only increased. So why this, this has not been, uh, automated so far because of the variation variation in shape, in size and color and material and how it’s stacked. Just in this example, if I drop this a small towel, a thousand times, the robots will see a thousand different, uh, let’s say tiles, but it’s the same one.

Herbert ten Have: (50:43)
So what we’ve done, we trained the neural network with supervised learning to enable the robot to generalize and to see the item and knowing where to cross. And so that’s what we do. We show, we built this algorithm and it’s being used in, uh, in both an order picking and in a partial hemming. Uh, just as an example, uh, you see your roll cage where we pick from, or in a, an older store we pick from the bin. Um, and maybe this an example, you see the camera, what it does, uh, takes the image, or we take the point cloud. So the 3d data, we do the segmentation, you see the, uh, green bounding boxes. Uh, we find all kinds of classifier. So we can see, for instance, if it’s a box or if it’s a back, et cetera. So all kinds of classifiers that are relevant and we give it the, we propose the cross processes, six degrees of freedom, X Y set, plus the rotation.

Herbert ten Have: (51:38)
So that’s all done by the neural network in less than 300 milliseconds, to give an example, you see a drinking cup from a little, from a baby. And if you see the point cloud left above you, you see, we are looking for a surface, uh, big enough and flat enough to attach a fact fact can cup to simulate it, to pick it up. And so that’s, that’s generating a six degrees of freedom brass posts, which you also see in the groceries, in the, in the bin on the right. So the, the angles green, red, and blue represent the angle where the suction cup shoots apply, uh, apply force. So, um, so this is just an example of the work that we’ve done with, uh, picking from this, uh, this bin. So, um, we were in logistics, which is really, uh, growing very fast. So our systems are being used in production in all of, of course, in Europe, in the, in North America and up till China.

Herbert ten Have: (52:36)
Uh, so we, uh, we have integrators using our software and it’s not totally for item picking and partial handling, but also for the palletizing for a truck and loading. And we even picked towels. So we have an algorithm that picks, finds the corners of towels and then feeds it in a, in a folding machine. So, um, we used to be, uh, bootstrapped the first year. So we really grew, and I think we are an exception in field. Uh, so, uh, now we got funding beginning of this year. We growing foster, um, re uh, we did use ROS in the past, but we stopped at, uh, due to quality. We, uh, we, uh, we had everything in C plus plus would be moved now to, uh, to rust. So with our newer environments. So we really, the we have production systems, so

Herbert ten Have: (53:26)
They really rely on the, on performance. So we have to get the best systems for, for us. Um, this is our timeline. Let’s start with your previous winner of the Amazon Picking challenge. And we’re based in Delfin, uh, uh, close to the university in the old university building. That’s it.

Thomas Andersson: (53:46)
Excellent. Thanks a lot for that. Um, Herbert, it’s very exciting days for logistics, uh, robotics, for sure. We keep hearing about lots of people being interested in investing in it. So, um, with that, uh, we’re handing over to Sebastian from, uh, how robotics in the UK.

Sebastian Andraos: (54:08)
Hello? Um, yes, I am sorry. There we go. Okay. That’s whatever. Um, so my name is Sebastian. Um, I’m one of the co-founders of Hal Robotics, um, Hal robotics is a software company, uh, based here in London and in Paris. Uh, we provide solutions and substance to model programs, simulate, and increasingly communicate, uh, with applications involving industrial rentals. Um, as I mentioned, we have, uh, offices here in London and Paris, but we have funds absolutely all over the world and in all sorts of different industries, um, from food and beverage to aerospace, uh, arts and crafts to construction, um, and the ones I’ve picked out here in particular are those that I think best exemplify what we do, um, is that currently undocumented, um, they tend to work with very small batches or even one of pieces. Um, and the operators that work in these fields are more often than not non-expert users, or at least we have to cater for non-expert users in these, in these fields.

Sebastian Andraos: (55:25)
Um, and we do that by striving for simplicity and flexibility. Um, it’s obviously an approach that will work for any other industry. Um, but for some seekers it’s particularly preschool. Um, so on the simplicity side, we offer robotic programming solutions tied directly into cut packages, uh, with which our users are already familiar. The solutions themselves are actually built on top of our robotic framework, which is a flexible cross compatible, lightweight, and highly extensible software library that allows us to develop custom software, which will run on PCs, embedded systems or in the cloud with bespoke user interfaces to suit any skill.

Sebastian Andraos: (56:10)
To me, there are three major benefits of flexible digitized automation, and this project by seater got a bridge too far. Um, I think embodies them all perfectly, firstly, the tendency to use simulation and the fact that they have robots tied to optimize the structure, not only for performance, but also taking into account manufacturing constraints like production time, two-path visibility, and a few other, a few other parameters. They also make you solve automated Two-path generation to push the normal process much further than it could be a program by hand. There are something like 10,000 different targets on each of their panels. Um, and I can tell you, you’re never going to do it’s too long. It’s too boring. Um, and finally they use the fact that CAD and tool paths are adaptive. They say the robot is reprogrammed automatically when a part changes to make each part in a structure, unique at no extra cost with minimal variety of time per piece, and the complete freedom of design to end up with a truly mass customized and highly performative product.

Sebastian Andraos: (57:28)
These themes, Just studies can be applied regardless of the industry or material being used. And they can be tied in with sensors to perform more complex adaptive processes. Uh, here, for example, we have, uh, glassblowing or glass bending actually in this particular case, uh, steam bending of woods, and even robots on our construction sites that we’re working on at the moment. Um, and just cause it’s fun. Once you’ve got sensors in the mix, you can tie people in and have a bit of emotion and interaction going on. Um, so this was a student at a workshop we did a couple of years ago now. Um, who’s controlling a robot with his right hand and the gripper with his left. Um, and it appears that I raced through that. Um, but I’m gonna leave it at that. So please feel free to reach out and ask any questions you may have.

Thomas Andersson: (58:22)
Well, that gives us a spare minute for us. Well done, Sebastian, thanks a lot for that very interesting solution you have there. Um, I’ll say it again, feel free to field any questions through the Q and a tab to any of the attendees, um, and away with that we should move on to, Miranda software in France and Logan.

Laurent IRAI: (58:45)
Yep. Adam, thanks again. I’m gonna share my screen. Okay. So I’m Laurent from, uh, the IRAI company based in France. So we are all developing software for the industry in the education, uh, since 1988. Uh, so today I will show you a software, uh, that we developed for students to learn programming language. Uh, that’s called Miranda. So this is a simulator, um, for robots, small robots, uh, that you can find in some schools that you can program either in a stretch I beta. Uh, so let me show you directly inside the software. So we developed this, uh, the tools because, uh, particularly in schools, they don’t have access to a lot of robots. Uh, this is, uh, budgets. Uh, so with this tool, they are about to walk together, uh, at the same time, either in simulation and then work with the wheel robot or make a test, uh, before, uh, producing their own robots.

Laurent IRAI: (01:00:04)
Some schools do that with their children. So with me that can do all that. So they can simulate their own robots, test a challenge inside Miranda, then transfer your program to the robot to status through test it. There’s also a digital, so you can, uh, make your own remote before for the, seeing it and testing every, uh, aspect of the participants. And so et cetera. So to do that, uh, we propose, uh, challenges for the students. So we propose one challenges about our robot. So for example, is, uh, is a smaller robots. That’s pretty common in the schools.

Laurent IRAI: (01:00:51)
So robots can be programmed as you see in scratch by python. So for example, there’s the challenge is to program the robot to go to the each gate. So for example, I can simply make it not programmed to go back the, it feels great. So it’s, uh, it will be a good way for the students to learn programming without, uh, imaging, uh, or so the, the rail robots. And then what’s. So is that the, as a teacher or as a parent, you can follow the probation. So you have, uh, your students that, uh, I made inside this account, so I can follow their probation. You say each, uh, changes and also see their progression. They’ve done, uh, 12 of them. So they are, this is the program editor earlier. So I can just test it and was with me on that. So, so this is a predefined, uh, changes who is also get [inaudible] given, but you have access to an editor so you can create your own changes or modify, uh, changes are given so that you can better 3d from the library or 3d from the, uh, CEO, uh, software to create your own simulation. So if you have more questions, if you, if you want to be able to test, uh, the software you have, uh, access, you can access to go to website. Uh [inaudible] you have, uh, you can, uh, ask for three months, uh, to, to test the software or you can also go our website the area in France. So we linked in the chat when you can see also all the other products and based in the industry side and the automation, uh, you can see the robots simulation also. Thank you.

Thomas Andersson: (01:03:10)
Excellent. Thanks for that. Um, with that, we moving on quickly to Austria and, uh, Christian from incubated over to your question. Yeah.

Christoph Zehentner: (01:03:33)
Uh, thank you very much. Thanks for the invitation. Um, my name is Christoph Zehenter and I’m product owner, and one of the seven founders of Incubed IT, uh, yes, you heard right. We are seven founders and actually already 30 people working here at, incubed IT. And as you can hear from my lovely accent, I’m from Katz, Austria. Um, I think incubedIT believe that, um, autonomous mobile robots will become a commodity in every warehouse and, and every, um, production shop floor within a couple of years from now. And we believe that software will be, um, the key aspect to, um, for robots to become actually part of every warehouse, every production line. And that’s why we developed over the last nine years, a robotics platform, um, that turns any vehicle, any HPV into an autonomous mobile robot and, um, how that actually works. You can see in a nice little YouTube video, um, and I will let it run while I’m, I’m, I’m going to speak, um, over the last nine years, um, we invested in innovative lot, uh, in, in areas like localization. So, uh, let there open awareness, um, navigation, natural obstacle of widens, all this stuff that makes the robot go from a to B naturally. Um, and we have seen that this technology.

Philip English: (01:04:58)
Oh, I think there’s a, um, can they extend guys, um, not share their screen? So request off, please. Could you share your screen again?

Christoph Zehentner: (01:05:06)
Doesn’t matter. Um, and we’ve seen over the last year, statistic technology has become robust enough to, um, actually serve, uh, 24 seven industrial applications and what is needed now to get large fleets into, into the real world is easy use and, um, what is easy use for us? Um, on the one hand it’s easy hardware integration. So we need to get our software as easy as possible onto new hardware models. Um, it’s easy implementation of customer project. So, um, the top needs to be applied as a consumer like product. We often compare it to TV. You’re going to select the TV in the shop, and then you just use it,

Thomas Andersson: (01:05:50)
Uh, just to, um, can you share your screen again? Some of the attendees are really keen, so, sorry, sorry for that.

Christoph Zehentner: (01:06:01)
And it’s, um, on top of that, it’s easy kind of activity. So, um, I’ll flip management server, for example, can be instilled in the cloud, making it possible to attach it to multiple add on services, such as, um, analytic platforms, other host systems, ERP systems, whatever. Um, and in the end, easy usage on the sock shop floor itself. So it’s not only about a usable or easy to use user interface. It’s much more so the whole robotic solutions must be, um, easy to integrate and smooth to use. We always say smooth is the new smart. Um, and on top of that, um, we’re to do that, actually we developed a software platform that consists of three main parts. On the one hand, it’s the smart shat on navigation tool kit us with tend to call it it’s the navigation localization stack the drones within the robot.

Christoph Zehentner: (01:06:56)
It’s the second part is the fleet management server, which coordinates a fleet of heterogeneous robots. And on top of that data monitoring and analytics. So, um, the customer is getting inside. What is actually going on on the shop floor, um, cell numbers towards set them. We have more than 300 shadows deployed worldwide, currently running on our software platform. And for example, the biggest fleets consisting of 40 shuttles runs more than a thousand kilometers, the 24 seven and since 2014. Um, but there’s more than just robots driving around and robotics projects consists of multiple steps and the whole life cycle can be covered by our digital twin. So going from the planning phase where you can simulate a site upfront without actually having robots there, you can see how the process will look like how many shuttles do it, do I need, um, going through the development and testing of, of this, um, installation frugal life.

Christoph Zehentner: (01:07:58)
So you take the data that came from planning that you adopted during the development and actually put it in production. So, um, it’s a nice thing to take such a solution, um, in real production, from home, even from your home office, it’s much more convenient than sitting in a four degrees cooler warehouse. Um, and when you have the support case, for example, we just looked at data from the life installation back into our digital twin simulate. Um, how could that happen? Um, how could maybe a buck fix, um, fix the thing or changed in the configuration and so on and last but not least when you have processes that should, you can ride it up front in the digital twin, see how your KPIs vary and you can even suggest changes to the customer upfront before him knowing that he has maybe something to do tune to improve. Yeah. Um, that’s basically that I somehow hurry through it. If you have any questions, please feel free to contact us. Um, I’ve given the contact information here and once again, thank you for, for organizing that opportunity. Um, I’d love to hear from you guys. Thank you.

Thomas Andersson: (01:09:10)
It’s crystal. So just two quick notes there. So that’s a question for Fizyr in the Q and a, and there’s also one for you, Christoph, but that was in the chat. If you can just look at that. So anyway, uh, thanks for that. It’s very exciting. And kind of the solution that you developed, um, that’s way we’re moving over to extend robotics in the UK as well. And, uh, Ji long, I believe I pronounced that, right?

Chang Liu: (01:09:45)
Sorry. Uh, yeah. Chang Liu to hello everyone. Uh, my name is Chang Liu, I’m the founder and CEO of extend robotics. Uh, we are a human, a human focus, uh, robots, uh, startup in the UK. So, so our vision is really to extend human capabilities beyond physical presence. So we build affordable robotic arm capable of remote operation from anywhere in the world using a cloud-based teleoperation software. Uh, so our, our technical phoners are, uh, uh, post-docs and PhDs from Imperial college, uh, and, uh, commercial leadership from huawei. So, so really the background is not, uh, the, the new trend of digitization and automation is transforming almost oil industries and new technologies are, are approaching, uh, the slope of enlightenment and the, uh, and the new technology, uh, new challenges, like a labor shortage, uh, Asian society. And the pandemics are forcing our society to, to, uh, to look for new technologies and adopt and adopt them faster.

Chang Liu: (01:10:54)
And all of these contribute to the exponential growth of, uh, robotics. Uh, as we see today, so sale, um, sales of a service robot and succeed, uh, uh, 17 billion and, uh, 29 tens on the forecast to reach a 40 billion in 2023. So as a, yeah, as a big market, of course, I cannot avoid talking about COVID, uh, 65%, uh, UK, uh, office workers believe working remotely. It will becomes more common, uh, even after the pandemic. Um, and in many traditional industries are really like showing the need for remote working, even for physical, um, tasks. Uh, so it’s, it’s, it’s the worst time for human, but maybe, maybe the best time for robotics. Um, the fact is that, uh, still over 50% of the jobs can not be easily automated by today’s, uh, robots, um, due to the limited, uh, dexterity and the intelligence of autonomous robot and, uh, the low scalability and high cost of the traditional teleoperation, uh, robots.

Chang Liu: (01:11:58)
However, uh, now, um, many, many of these operations have a strong desire for, uh, to avoid human human presence. Um, but, uh, but how, but how can robotic, uh, help with this since 90, Nineteen fifties, uh, teleoperation robots and autonomous robot are kind of con complimentary in terms of balancing the cost and the dexterity. Uh, however that, uh, what people really need is, uh, in this background is a robotic system that is, uh, that is suppose affordable and can, uh, can provide flexible dexterity. Uh, they need to complete the job remotely and reliably. So, already. Uh, our solution is that, uh, we’re building a next generation, uh, teleoperation robots, which is an affordable VR controls, uh, Mo multi-purpose robotic arm accessible from anywhere in the cloud. So this works as the physical avatar of the user to perform, um, manipulation or teleoperation task remotely.

Chang Liu: (01:12:59)
Uh, so we call it the all-star twin. Uh, so after is a robotic, uh, manipulation module to be in, to be integrated into your existing robots, like, uh, re uh, um, uh, mobile robots. So technically is includes three parts, uh, robot toolkit, uh, of advanced mechanical assistance systems, AMS, and, uh, um, and, uh, imitation learning engine. So, so our robot toolkit is a versatile, uh, on module, uh, with human-like dexterity and the perception. Um, it is, um, it is an affordable. Multi-purpose robotic arm optimized for mobile teleoperation. So it features, uh, remarkably, uh, high power to mass ratio, um, with six degrees of freedom utilizing their power, power, high power density, uh, quasi quasi direct drive, uh, partially smallers and, uh, and lightweight optimized, um, uh, design was advised the parallel mechanism. So it was also integrated, uh, RGBD sensors and powerful computer unit for data processing and control.

Chang Liu: (01:14:07)
Um, yeah. Um, I’m gonna still manage, uh, everything in one package, you know, and quite low cost. So, so our aim as, uh, is a powerful, uh, VR software, uh, which provides, uh, immersive 3d perception and intuitive control, uh, for high dexterous, uh, teleoperation, uh, with, with low cost, uh, consumer equipment. So, so, yeah, so the, uh, is, is developed in a efficient point cloud streaming pipeline and the gesture based control graphic user interface, and, and really utilizing the, uh, 3d 3d point cloud perception gives user the accurate sense of depth, uh, flexible view, uh, viewpoint and avoid motion sickness, uh, while the digital twin based adjust gesture control, uh, gives user an intuitive interface to, uh, to send complex control signals effortlessly. Yeah. So yeah, our invitation engine is the, as a cloud-based imitation pep light enable anywhere access, uh, on flexible data-driven AI. Yeah. So, yeah, so, uh, I I’ll, I’ll just quickly jump through that. The, the, yeah, so if you’re interested, you can, uh, you can go online and YouTube to, uh, to check out our, like a portal, a walkthrough video, and, uh, yeah, thanks for listening. I’m sorry to the expense.

Thomas Andersson: (01:15:36)
Thanks &for that. Um, very interesting, but that’s anyway, we, we jump over to the last presentation. It’s a note from ARS recruitment, if we have any, um, people looking for work these days in the robotics sector. Uh, so without over to you, Sam,

Sam Robinson: (01:15:54)
Thank you. Uh, let me just share my screen. Can we all see that? Okay, cool. So thanks for the invitation. Um, my name is Sam Robinson. I am the owner.

Thomas Andersson: (01:16:10)
You haven’t shared anything yet. Oh, no.

Sam Robinson: (01:16:14)
Two seconds then,

Thomas Andersson: (01:16:18)
Just to note again, feel free to field any questions in the Q&A tab, and we will try to read them out later or on to the main screen. There you go.

Sam Robinson: (01:16:29)
Okay. Lovely. Sorry. So yeah, I am Sam Robinson. I’m the owner of automation and recruitment solutions. Uh, I set the business of pen February this year, just before COVID struck, um, really specializing in automation and robotics recruitment. Um, just want to talk about a few things today. Um, mainly the client top tips for hiring. Um, the market is picking back up now and some people are after, you know, specialized stuff. So I just want to put a few points out to stress us specifically being competitive. There’s a lot of people within automation, robotics that are looking for the same type of talent, same type of skillset. Um, um, really you need to start thinking about what separates you from the other people. It’s not always regarding salary, uh, candidates in the market these days. They’re looking for more benefits in terms of flexibility, career development.

Sam Robinson: (01:17:22)
Um, and then think about the interview methods that you are actually using while hiring, uh, are they formal interviews now, are you now switching over to zoom meetings, team meetings, um, and streamlining going to be processed? So the Canada is fully transparent with how many stages that they interview is going to take. And as I just touched on, there’s not a great load of talent out there at the moment, and it is spread thin within many companies. So there’s different options to consider. Are you taking the graduate routes, or maybe not so much on the technical roles, but on senior management and director roles, taking people out of the industry that bring different methodologies, different ideas. Um, it found that the couple of clients that I currently work with, it’s a great way of bringing in new ideas into the business. Uh, just want to talk about the candidate side of thing very quickly.

Sam Robinson: (01:18:10)
And if you are looking for work at the moment, it’s very important that you are making your CV very clear and very precise to the type of skills that you have and to why somebody should want to hire you. I would include hiding, uh, including your achievements onto your CV and making it very clear what you can bring to the business. And then if you are selected for interview, I think preparation is very important. You need to be doing the research on the business. It’s one of the interview questions that are asked every single time. What do you know about us? And you’d be surprised how many times that catches people out even today, um, which is bizarre. Uh, you also, I would recommend doing some interview research on the managers that are going to be actually interviewing you for the role. And on top of that, I also suggest potentially doing a route planner, a Google maps to see where the interview is, how long it’s going to take.

Sam Robinson: (01:18:57)
You even do a practice route, and it’s only a short presentation, but the, I saved the last important part to last. And that’s your LinkedIn profile? So it’s a public platform where everybody is on or should be on if they’re looking for work, or if they’re looking to hire a, your, your profile should include your contact details, a picture of yourself and making yourself visible. So people can contact you for opportunities, uh, recruiters like myself, users, the number one go-to to find talent. And if you’re not on there, and if you’re not making yourself visible, um, there are other people out there that are, so if you need any support or any help with anything regarding your LinkedIn preparations for interview or your Germany, just looking around, um, I’d love for you guys to get in touch and more than happy to help, even if it’s just the guidance. Um, so with that, it was only a short one. Thank you very much for the invitation, um, back over to you, Thomas.

Thomas Andersson: (01:19:49)
Yeah. So thanks. Lots of that. So kind of concludes, um, all the presentations. So we can now go over to Q and a session and, um, let’s see here, I’ll share my screen. So this all, so first of all, if any attendees you want to contact us, just take a screenshot now. Um, we, there is one question for, um, for Fiyer. Um, if you’ve worked on any application where it’s necessary to pick up items using a robotic arm located on a mobile robot, if so, what, uh, experience and challenges have you found? Okay. Yeah,

Herbert ten Have: (01:20:35)
I can also that, um, uh, actually a lot of people think, uh, think of it that way, replacing a human, both walking around and picking, but it’s not an interesting application for a robot for economic reasons, because if you will, you want to have the robot continuously picking to have a decent ROI, a return on investment. So let’s say every few seconds of robots should be picking. So ideally you have a goods person or a good robot situation where the robot can continue picking if you have to run around and apart from navigation and it becomes harder, but then picking would be, let’s say once in 30 seconds, max, maybe once in a minute. So it doesn’t, uh, uh, support the investment of robots.

Thomas Andersson: (01:21:21)
Interesting. Thanks for that. Um, so, and feel free to field any questions I have, um, a question myself, perhaps. Um, what, um, if anyone wants to pitch in, what has your kind of impact been from the pandemic? How has business changed for you? Some must’ve had quite a positive impact, some perhaps a slightly negative or any, any type of impact that you want to talk about? Perhaps a Herbert wants to answer it.

Herbert ten Have: (01:21:54)
Yeah, sure. Um, so first we’re were shocked, of course, and we, we, uh, had an estimate for all project being, being put on hold. Uh, and so we had to survive for a year, but soon after, I think less than two months, we saw that our key clients like a fabric and Tel afif, and then New York, they are picking groceries for delivery at home. They said, full-blown we go ahead. And so it’s, uh, so, uh, they increased their, uh, their speed and so we work harder for harder for them. And then in the, I would say the last three months or partial handlers, uh, they, they have so many increases and so they want to have more picking shelves. So, um, if it’s DHL ups, federal express to ups, so all of them have a shortage of people, all of them want to have picking shelves, uh, in the near future.

Thomas Andersson: (01:22:47)
Interesting. Anyone else? Uh, Christoph, perhaps.

Christoph Zehentner: (01:22:55)
I would say it’s the same story here. Um, at the beginning we have seen that everybody puts, put, has purchased projects on health because fear maybe, um, but actually, um, it’s rising again and rising much more than it was before.

Thomas Andersson: (01:23:13)
Yeah. Interesting. What about, um, Owen, and I know you haven’t had any, um, it kind of out with your bedtime, but how do you see the pandemic?

Owen Nicholson: (01:23:25)
It was, um, so obviously it was a shock, uh, and it’s, uh, it was a big shock to the system and had to, I think we all had to rethink a bit about how we were going to actually run the companies,so, uh, moving to working remotely. Um, I actually wrote a, an open letter to the, to the robotics industry, um, at the start, which got picked up by the kind of robo tech and broker business use. And we’ve got quite a lot of PR, um, essentially saying to a lot of the bigger companies and the investors. Um, this is going to be a hard time for the robotics industry, but we are also part of the solution for the future. So let’s make sure that we, we, we will get through it to the other side because, and actually that’s what we’re starting to see now, ourselves, we’re seeing a huge, uh, inbound interest coming from our side. Um, investors are starting to, to see that robotics is, um, is something which is going to be, I’d say it’s even been accelerated by all of this because a lot of the larger companies have been thinking of how do we make ourselves more robust into the future. So absolutely wish it wasn’t happen. I wish it wasn’t, it wasn’t a hair, but I think the net benefit might actually be positive for the robotics industry, which is quite bizarre to say

Thomas Andersson: (01:24:30)
Interesting. What about, uh, from alias side Endika in Spain, how did you, um, what was your experience of the pandemic?

Endika Gil-Uriarte: (01:24:39)
So I, I do share what, what most of the previous speakers on the content that you guys serve, um, it has pretty much become the same for us. So we had to move to, let’s say to fully working remotely for a while, and most of our customers have suffered the same. Now we’re back to the new normal. We have a witness, not some of our customers do have, let’s say reduced themes within the shop floors. They do have, they have a lot of constraints when it comes to say physical contact with people and so on, and why not. They have moved to wireless, remote monitoring station of their robotic processes and so on. And they have identified increasingly security as we’re on for business continuity. So it’s up to us as when said before to be safe, being in this very new future and to be able to adapt effectively to these new conditions that will very likely stay for awhile.

Thomas Andersson: (01:25:41)
Interesting. Thanks. What about, um, extend robotics? What, um, so having remote, um, from remote control of yourself, or must’ve been quite an interesting business to be in during the pandemic or,

Chang Liu: (01:25:55)
Yeah. Uh, I guess we are, we’re, we’re being quite lucky because, because our whole solution is around remote working. Uh, some, especially in being able

Chang Liu: (01:26:04)
To have a, like an intuitive, uh, user interface to allow anyone to control, uh, at least a robot arm, uh, remotely. Uh, so we’re, we’re hoping that, uh, I mean, as clear now, there’s a, there’s a huge need now, uh, not only of for remote work and not only, and like, uh, uh, ICT, uh, um, demand, but also like extending that into our physical to men. And that’s, that’s exactly what we could do. For example, if some, uh, so many, many like, uh, university labs that just closed and people can not continue doing testing, um, you know, like, uh, yeah, uh, uh, any company labs that just just require physical work and that has to be closed and no one can access the location. Uh, but, uh, but just imagine if someone could just remotely control robots working on a work camp continuously working on their product. Um, yeah, that’s, that’s exactly what we can, we can offer

Thomas Andersson: (01:27:02)
Sebastian is how any, any impact at all? Uh, any, um, interesting.

Sebastian Andraos: (01:27:08)
So, I mean, as a software company working from home is, uh, is a bit easier than working for a hardware company. Um, but yeah, everything is slowed down, um, a bit, I think, I think we’re going to see everything got, particularly, we’ve heard a bit of contact from our SME manufacturers struggling to keep as many people in, in their cities, um, and would like to automate out some of the, some of the less interesting jobs, um, which is something that we saw before the pandemic is just, uh, I’ve spurred some of those people back into action. Um, but yeah, I mean, it was relatively easy to move between locations. It’ll be okay,

Thomas Andersson: (01:27:48)
Lauren, um, France.

Laurent IRAI: (01:27:51)
Yeah. So fortunately for us, it was a, uh, critical, uh, opportunity, but, uh, it’s unfortunate that, uh, as we work in the simulation side, uh, in industry that doesn’t change anything for us, but, uh, in the education, uh, as you make so many shows, uh, Miranda is a product that we, uh, came out in February. So just before the pandemic and, uh, so students, uh, were actually using the software, uh, we gave it for free during the pandemic for them to work from home on the programming, the robots that they couldn’t do in, uh, in school was, uh, granted. Um, so we really became popula] in the, in the schools Mirada and, uh, uh, so it was fortunate for us to

Thomas Andersson: (01:28:57)
Interesting. Yeah. I mean, it’s, it’s been a health problem. So there’s one question from, um, robots online, again, about, uh, how, and it’s kind of talking about the pandemic impact as well, but specific, uh, specifically relate to how customers or end users have, um, reevaluate the way they access and they deploy capital, uh, with the perhaps. So looking at CapEx versus OPEX type investments for robotics, perhaps, um, how about, do you want to, um, have a stab at that as well?

Herbert ten Have: (01:29:36)
Um, yes, I can. Um, we, we actually, we support both, uh, construction, both CapEx and OPEX. Uh, we even can, uh, invoice per pick, uh, that’s really up to the client. So we’re, we’re flexible on that. Uh, so, uh, um, but we haven’t seen a big change in that. So there are integrators and end users that want to have CapEx and other one to have an OPEX model. So we are just flexible, I would say.

Thomas Andersson: (01:30:02)
Okay, what about, so Philip, we have, so Philip, um, it’s obviously sponsoring the events, but it’s also a system integrator working quite a lot with end customers in the UK. What’s your kind of, yeah. Okay.

Philip English: (01:30:19)
Yeah. Yeah. So, I mean, from, from our side, we we’ve seen, um, a lot of consultancy. Uh, so especially for the bigger guys that are looking into the new types of robotics, but they’re, um, a bit hesitant with the actual, uh, placing orders and placing POS. I think they’re sort of, they’re getting the consultancy, they’re getting the understanding of what they need to do, uh, ready to hit the order button. Um, and then for the, for the SMEs, um, depending on the industry, uh, if it’s a or C uh, aerospace and have gone quite quiet right at the moment. Um, but yeah, there’s definitely got some solvency, so I just don’t see it. Everyone’s in interesting to see how, how this technology is going to help them. So

Thomas Andersson: (01:31:03)
Interesting. Anyone else on the OPEX versus CapEx kind of, um, or let’s say, um, um, preservation of cash, so, or otherwise I can, I mean, I’m just, I’m just writing a really big report on the AGV sector. So AGVs, um, um, an AMR, so autonomous mobile robots and have interviewed about 55 to 60 companies. Um, so what we’ve seen is that, um, there is, in, in the past years, like two or three years ago, people talked about Rust models and, uh, leasing models, but no one really kind of entered into that, but now we’re seeing that customers are coming back and asking for these models. Um, you know, um, sorry, you, you, you talked about this before. Can we rediscover that? Um, we kind of the rust type models, one of the, is that, um, not many of the customers or the end users allow, I’ll say robotics, uh, fleet managers, or a controller software on a kind of own cloud. So the business models look slightly different. It’s only the least that’s really, uh, available in most cases anyway. Um, I’m not sure if that’s true for everyone. Um, anyone else on the OPEX versus CapEx cash preservation. Otherwise we have one very specific question as well. Um, which I can’t see now. Um,

Herbert ten Have: (01:32:40)
I think I remember the question was through us, it, wasn’t hard to work to migrate from C plus plus the rest,

Thomas Andersson: (01:32:47)
That’s it? Yeah.

Herbert ten Have: (01:32:49)
Um, and the, the least person to answer this question in my team, but, uh, what I’ve witnessed is that, uh, of course it’s a big, big change because you invest in something to replace. It, it doesn’t bring you direct benefits. It’s really long-term for your clients. So it was a, it’s this really strategic decision to go for the highest quality. And, uh, as you know, Microsoft decided to also migrate to rust instead of C plus plus. So that’s really indication now how important they see this decision. Uh, so we had to train people. We had to make, uh, you planning all the stuff. So we invest a lot in this migration. Yeah. It’s, uh, it’s tough, but we believe we want to go for staying the best. And this is one of the, uh, the key elements.

Thomas Andersson: (01:33:35)
Okay, excellent. Thanks for that. It also brought in, um, um, Microsoft into the question. So we have a few other Q and A’s as well, but I think we’re running slightly over our time now. So we have, uh, had the webinar for one hour, 10 minutes. We, um, I think that’s it, unless there are any really pressing questions. There is a question for IRI regarding the simulator. Perhaps you can answer that.

Laurent IRAI: (01:34:05)
Yeah. There’s a, in the software, so you can, uh, edit, uh, existing, uh, robots, so, or plants or something, but you can also create your own robots in portraits really. And the build, uh, blogs or the Python command, uh, to come on the inside miranda so you can test it, uh, inside the changers or, uh, see the difference between the robots, uh, we have, uh, installed between the yours. Yep.

Thomas Andersson: (01:34:43)
Yeah. I recommend also anyone, any of the attendees, just to remember that this will be online as well on YouTube, so you can, we’ll be able to see the links and so on. Again, I think with that, we’ll, we’ll close down this webinar, big, thank you to all panelists. Um, who’ve given their time for this and, uh, hopefully we’ll get something out of this. Some nice connections, um, or whatever. So to everybody from Europe have a real continued, a nice evening from everybody from the U S so hope you have a nice day. Thanks everyone. Thanks guys. Thanks everyone.