In this episode, we talk about how a fashion company spun-off from MIT has developed the world’s first truly one-size-fits-all garment.

Podcast: Novel Fabrics + Robots -- Sustainable One-size-fits-all Fashion Revolution

A pick and place robot in an industrial setup

Understanding the inception, evolution, composition, and types of pick and place robots and their impact on various industrial sectors 

Pick and Place Robots: An In-Depth Guide to Their Functionality and Applications

This article was discussed in our <a href="https://www.wevolver.com/profile/the.next.byte" rel="noopener noreferrer" target="_blank">Next Byte podcast</a>.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/7a6ed573-f46a-40bb-b396-d38d1207aa2e?dark=false" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> The full article will continue below.<hr>Until recently, bespoke tailoring — clothing made to a customer’s individual specifications — was the only way to have garments that provided the perfect fit for your physique. For most people, the cost of custom tailoring is prohibitive. But the invention of active fibers and innovative knitting processes is changing the textile industry.“We all wear clothes and shoes,” says Sasha MicKinlay MArch ’23, a recent graduate of the MIT Department of Architecture. “It’s a human need. But there’s also the human need to express oneself. I like the idea of customizing clothes in a sustainable way. This dress promises to be more sustainable than traditional fashion to both the consumer and the producer.”McKinlay is a textile designer and researcher at the Self-Assembly Lab who designed the <a href="https://selfassemblylab.mit.edu/4d-knit-dress" target="_blank">4D Knit Dress</a> with Ministry of Supply, a fashion company specializing in high-tech apparel. The dress combines several technologies to create personalized fit and style. Heat-activated yarns, computerized knitting, and robotic activation around each garment generates the sculpted fit. A team at Ministry of Supply led the decisions on the stable yarns, color, original size, and overall design.“Everyone’s body is different,” says Skylar Tibbits, associate professor in the Department of Architecture and founder of the Self-Assembly Lab. “Even if you wear the same size as another person, you're not actually the same.”<iframe width="640" height="360" src="https://player.vimeo.com/video/893959788" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;&nbsp;&nbsp;&nbsp;</iframe>4D Knit Dress: Transforming Style. Video: Self-Assembly Lab<h2 id="isPasted">Active textiles</h2>Students in the Self-Assembly Lab have been working with dynamic textiles for several years. The yarns they create can change shape, change property, change insulation, or become breathable. Previous applications to tailor garments include <a href="https://selfassemblylab.mit.edu/active-textile-tailoring" target="_blank">making sweaters</a> and <a href="https://news.mit.edu/2022/form-fitting-face-mask-lavender-tessmer-0718" target="_blank">face masks</a>. Tibbits says the 4D Knit Dress is a culmination of everything the students have learned from working with active textiles.McKinlay helped produce the active yarns, created the concept design, developed the knitting technique, and programmed the lab’s industrial knitting machine. Once the garment design is programmed into the machine, it can quickly produce multiple dresses. Where the active yarns are placed in the design allows for the dress to take on a variety of styles such as pintucks, pleats, an empire waist, or a cinched waist.“The styling is important,” McKinlay says. “Most people focus on the size, but I think styling is what sets clothes apart. We’re all evolving as people, and I think our style evolves as well. After fit, people focus on personal expression.”<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTM1NjY2MDgwLU1pbmlzdHJ5X0ZJTkFMX2RyZXNzZXMuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Designers explored this series of possible styles for the robotic heat activation of the 4D Knit Dress. Image courtesy of the Self-Assembly Lab.Danny Griffin MArch ’22, a current graduate student in architectural design, doesn’t have a background in garment making or the fashion industry. Tibbits asked Griffin to join the team due to his experience with robotics projects in construction. Griffin translated the heat activation process into a programmable robotic procedure that would precisely control its application.“When we apply heat, the fibers shorten, causing the textile to bunch up in a specific zone, effectively tightening the shape as if we’re tailoring the garment,” says Griffin. “There was a lot of trial and error to figure out how to orient the robot and the heat gun. The heat needs to be applied in precise locations to activate the fibers on each garment. Another challenge was setting the temperature and the timing for the heat to be applied.”It took a while to determine how the robot could&nbsp;reach all areas of the dress.“We couldn’t use a commercial heat gun — which is like a handheld hair dryer — because they’re too large,” says Griffin. “We needed a more compact design. Once we figured it out, it was a lot of fun to write the script for the robot to follow.”A dress can begin with one design — pintucks across the chest, for example — and be worn for months before having heat re-applied to alter its look. Subsequent applications of heat can tailor the dress further.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTM1NjgyOTQyLVJvYm90aWNfYXJtX2F0X3dvcmsuanBlZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib">Robotic heat activation can be seen during a demonstration at Ministry of Supply in Boston. Photo: Olivia Mintz<h2>Beyond fit and fashion</h2>Efficiently producing garments is a “big challenge” in the fashion industry, according to Gihan Amarasiriwardena ’11, the co-founder and president of Ministry of Supply.“A lot of times you'll be guessing what a season's style is,” he says. “Sometimes the style doesn't do well, or some sizes don’t sell out. They may get discounted very heavily or eventually they end up going to a landfill.”“Fast fashion” is a term that describes clothes that are inexpensive, trendy, and easily disposed of by the consumer. They are designed and produced quickly to keep pace with current trends. The 4D Knit Dress, says Tibbits, is the opposite of fast fashion. Unlike the traditional “cut-and-sew” process in the fashion industry, the 4D Knit Dress is made entirely in one piece, which virtually eliminates waste.“From a global standpoint, you don’t have tons of excess inventory because the dress is customized to your size,” says Tibbits.McKinlay says she hopes use of this new technology will reduce the amount of waste in inventory that retailers usually have at the end of each season.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzEwMTM1NzEwMDIxLU1pbmlzdHJ5X0ZJTkFMX0RyYWZ0MDUgY29weS5qcGVnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">A complete 4D Knit Dress comes out of a Stoll industrial knitting machine after being produced in one piece, without any cutting or sewing. Photo courtesy of the Self-Assembly Lab.“The dress could be tailored in order to adapt to these changes in styles and tastes,” she says. “It may also be able to absorb some of the size variations that retailers need to stock. Instead of extra-small, small, medium, large, and extra-large sizes, retailers may be able to have one dress for the smaller sizes and one for the larger sizes. Of course, these are the same sustainability points that would benefit the consumer.”The Self-Assembly Lab has collaborated with Ministry of Supply on projects with active textiles for several years. Late last year, the team debuted the <a href="https://selfassemblylab.mit.edu/4d-knit-dress" target="_blank">4D Knit Dress</a> at the company’s flagship store in Boston, complete with a robotic arm working its way around a dress as customers watched. For Amarasiriwardena, it was an opportunity to gauge interest and receive feedback from customers interested in trying the dress on.“If the demand is there, this is something we can create quickly” unlike the usual design and manufacturing process, which can take years, says Amarasiriwardena.Griffin and McKinlay were on hand for the demonstration and pleased with the results. For Griffin, with the “technical barriers” overcome, he sees many different avenues for the project.“This experience leaves me wanting to try more,” he says.McKinlay too would love to work on more styles.“I&nbsp;hope this research project helps people rethink or reevaluate their relationship with clothes,” says McKinlay. “Right now when people purchase a piece of clothing it has only one ‘look.’ But, how exciting would it be to purchase one garment and reinvent it to change and evolve as you change or as the seasons or styles change? I'm hoping that's the takeaway that people will have.”

Caption:In late 2023 the MIT Self Assembly Lab and the high-tech fashion company Ministry of Supply debuted their 4D Knit Dress at the latter's store Boston, complete with a robotic arm working its way around a dress as customers watched. Credits:Image courtesy of MIT Self Assembly Lab

Developed by the Self-Assembly Lab, the 4D Knit Dress uses several technologies to create a custom design and a custom fit, while addressing sustainability concerns.

Is this the future of fashion?

It’s been some time since we’ve had an update on&nbsp;<a href="https://www.realliferobotics.com/" target="_blank">Real Life Robotics</a>, an Ontario-based firm gaining traction with its BUBS last-mile delivery platform.A lot has happened over the past year, with all of it appearing to point toward a solid trajectory.“We started off 2024 with a bang – with a really exciting story that has to potential to significantly change the current trajectory of Canadian small and medium businesses from coast to coast,” says CEO and Founder Cameron Waite.The story? Real Life Robotics (RLR) was one of eight Canadian startups selected by the&nbsp;<a href="https://www.cfin-rcia.ca/media/news-releases/foodtechnext-jan" target="_blank">Canadian Food Innovation Network</a> to receive funding through its&nbsp;<a href="https://www.cfin-rcia.ca/funding/foodtech-next" target="_blank">FoodTech Next</a> program. FoodTech Next offers funding for early-stage Canadian technology firms who seek to be part of – or sell to – the wider food industry. Through this program, RLR will receive nearly $250,000 to test its solution in real-world environments and validate the return on investment for the food sector.&nbsp;In the current economic landscape, Canadian businesses grapple with increased customer demands for last-mile delivery and reduced profitability. Currently, most rely on third-party companies like Skip The Dishes, DoorDash and Uber Eats, which charge 20-35 per cent commissions on each order.Automation is poised to play a critical role in helping businesses efficiently and sustainably move products from Point A to B (and even C, D, E…).“The overarching goal of FoodTech Next is to accelerate the commercialization of Canadian innovation by generating first demonstration opportunities,” says its website.The announcement made the news, including <a href="https://www.cbc.ca/listen/live-radio/1-92/clip/16042550" target="_blank">this CBC interview</a> with Waite.Below: Founder/CEO Cameron Waite making a pitch for the FoodTech Next program…<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA5OTIzNzIzMDY0LTIwMjQwMjE0LUNGSU4tRm9vZFRlY2gtMjAyNC0xNTAtc2NhbGVkLndlYnAiLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 100%px;" class="fr-fic fr-dib"><h3 id="isPasted">THE PLATFORM</h3>When the RLR team carries out demonstrations across the country, it brings along BUBS – one of several solutions Real Life Robotics has available to customise and deploy. Out of the box, BUBS has a large cargo bay (50 kg) suitable for transporting everything from bottled water to medical supplies to prepared meals.BUBS can be remotely tele-operated over 5G networks with near-zero latency, or carry out deliveries autonomously. It can work indoors or out and has an IP protection that makes it impervious to inclement weather (with the exception of, say, a hurricane or tornado). It has excellent obstacle avoidance and a number of other features intended for safe operation near people. It’s also perceived as “friendly” – which is important as these devices are introduced in public spaces.BUBS can also be customised, pending client needs.“We’re a cargo and last-mile delivery robotics platform,” says Waite. “But clients inevitably and always have some sort of unique requirement to their business in order to fully adopt and scale automation. There’s no reason BUBS can’t be bigger or smaller, or a different shape or colour – or have its cargo bay modified to carry something unique or unusual that requires modification.”And the business model? Well, it’s not just about selling a single robot. It’s about that first robot proving its worth to the client in economic terms.“It’s nice to say: ‘I have a robot,'” says Waite. “But our goal is really to have a robot or automation solution that has a positive business impact so that you want to scale and buy more of them. Otherwise, you buy just one.”&nbsp;<h3>MORE OPTIONS EN ROUTE</h3>It’s not just BUBS. Real Life Robotics, says Waite, has another solution it’s about to unveil: A quadruped delivery robot. Having four legs instead of wheels means deliveries are not limited by stairs or rough terrain. And, in a world where businesses increasingly want their space or inventory scanned, this robot is capable of carrying out those tasks as it goes about its delivery work.While food delivery in public spaces is clearly the focus of Real Life Robotics (and is tied to the federal grant), Waite emphasises that BUBS can be put to use in far wider use-cases.“Right now our focus is the local delivery side of the food industry,” says Waite. “But beyond that, it could also be products – like hats at a hockey game or bottled water&nbsp;at a. convention centre. It all really comes down to increasing the margins for our clients while ensuring a high-quality memorable delivery experience for the customer.”Below: BUBS, making things easier…<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA5OTIzODc2NTk4LUN1c3RvbWVyLWxvYWRzLUJVQlMtanBnLndlYnAgY29weS5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 100%px;" class="fr-fic fr-dib"> <h3 id="isPasted">NEW TEAM AND FUNDING ROUND</h3>Though we’ve been focusing on the robots, you can’t build a business without a team. And there, Waite says Real Life Robotics has been fortunate in attracting some A-level talent who share his vision.The company has acquired <a href="https://uwaterloo.ca/scholar/bjdehart" target="_blank">Brandon J. DeHart</a> as Chief Technical Officer. DeHart is the head of the University of Waterloo’s <a href="https://uwaterloo.ca/robohub/" target="_blank">RoboHub</a>, the epicentre of all things robotic at the university. (Waterloo’s Engineering department, according to the RoboHub website, “has the largest and most active robotics and automation research group in Canada, supporting Canada’s largest robotics and automation cluster.”)So DeHart comes with impeccable credentials, and has the expertise to both modify products and engineer completely new solutions for RLR. He has both a PhD and a Masters degree.“In terms of a robotics pedigree, this guy is top of the tops,” says Waite. “So we’re really, really excited about having him on board as CTO and I’m really excited to see what we can build together.”You can read more about DeHart in this <a href="https://www.realliferobotics.com/news/supercharging-the-real-life-robotics-team" target="_blank">RLR blog post</a>. And you can look at him, in the photo below…<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1709924018119-Brandon-J-DeHart-RLR-jpg.webp" style="width: 100%px;" class="fr-fic fr-dib"><h3 id="isPasted">NEW CFO, HEAD OF GROWTH</h3>Real Life Robotics has also attracted a new Chief Financial Officer, as well as a Head of Growth.The CFO is Ian Watson. Based in the UK, Watson spent 25 years with <a href="https://www.pwc.com/ca/en/" target="_blank">Price Waterhouse Cooper</a> before venturing into the startup space. He has owned and managed several startups, and is a Canadian Chartered Accountant. Watson holds a Master’s degree in Business (McMaster University) and a BA in Economics (Wilfrid Laurier University).“He’s deeply experienced in the financial and accounting worlds, plus he knows startups and how to help businesses grow strategically,” says Waite.Sharif Virani is the new Head of Growth – and appears to be a great fit. Before joining RLR, Virani held a similar position with&nbsp;<a href="https://tinymile.ai/" target="_blank">Tiny Mile</a>, which deploys small pink robots for food delivery. The company is currently operating in Miami – and had previously been running its operation in Toronto. If you ever saw one of those little robots on the news or social media, odds are Virani was behind that.“He’s a serial entrepreneur in the restaurant industry space – so he understands that market really well,” says Waite.And those are just three of the recent additions to the RLR team. A total of 10 people are now part of the company, with several on the sales and operations side. Together, they bring a total of 53 years of direct experience in the robotics industry.&nbsp;<h3>FUNDING ROUND</h3>As Real Life Robotics prepares for its next phase of growth, the company is currently in a Series A raise round.“The traction we’ve received – from the partnerships we’ve been developing, the grants we’ve been winning, and the client revenue we’re now generating – tells a really strong story to the investment community,” says Waite.Below: a 360° video tour of the University of Waterloo’s RoboHub. Be sure to scroll around to see the big picture…<iframe width="640" height="360" src="https://www.youtube.com/embed/O_7KSGdVLoc??si=GRuboC_a2bKF_SND&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&amp;lt;span class="fr-mk" style="display: none;"&amp;gt;&amp;amp;nbsp;&amp;lt;/span&amp;gt;</iframe><h3 id="isPasted">WAIT A MINUTE</h3>Cameron Waite talks a good game. But how do we safely introduce robots onto public roadways? Though Toronto now has a pilot project underway to evaluate such delivery robots, it’s not like they’re going to be embraced tomorrow.So how can Waite be so optimistic, when public acceptance (and even permission from municipalities) is not guaranteed?The answer, he says, has been in ground work and relationship building. RLR is also part of multiple stakeholder organisations that have been actively engaging on precisely this issue. The company is part of the following groups:<ul><li><a href="https://www.urbanroboticsfoundation.org/" target="_blank">Urban Robotics Foundation</a></li><li><a href="https://www.roboticscouncil.ca/" target="_blank">Canadian Robotics Council</a></li><li>Founding member of the&nbsp;<a href="https://uwaterloo.ca/robohub/professional-partnership-program" target="_blank">RoboHub Professional Partnership Program</a></li><li>Founding member the Toronto Autonomous Mobility Working Group</li></ul>That last one? Its members are <a href="https://gatik.ai/" target="_blank">Gatik</a>,&nbsp;<a href="https://www.tesla.com/" target="_blank">Tesla</a>,&nbsp;<a href="https://www.uber.com/ca/en/" target="_blank">Uber</a> and&nbsp;<a href="https://www.realliferobotics.com/" target="_blank">Real Life Robotics</a>.Lobbying groups are one thing. But getting the automated rubber to meet the road is another. Here, Waite reveals that RLR is ahead of the game: It has permission from five municipalities across the country to operate and test its vehicles in public spaces.“That’s really what this government grant is targeted toward: Exploring the validity of robots in public environments,” says Waite.&nbsp;<h3>MAJOR PARTNERSHIPS</h3>Waite also says RLR has some significant partners onboard, including “an incredibly large restaurant space company.”“This partner not only gives us some amazing insight and data that we can utilise to ensure that this technology truly has ROI and business value to that industry. They also give us some scale and scope as we grow.”But why not name names?“The reason is simply that we’re moving a little bit faster than their marketing team can handle.”Waite promises some significant announcements on this front soon, and deployment of RLR robots in the streets in the near future. Again, Waite won’t reveal details but pledges that the use-case is “really cool” and will grab headlines.“By the summer, for sure, Real Life Robotics robots will be in the field – and there will be a huge story around it.”He adds that RLR has Indro Robotics as an engineering partner, and access to&nbsp;<a href="https://indrorobotics.ca/indro-forge-prepped-for-next-phase-expansion/" target="_blank">InDro Forge</a>, a rapid fabrication and prototyping facility based in Ottawa. These two partnerships, he says, speed custom fabrication for clients, in addition to builds of entirely new robots.Below: BUBS on the street…doing good work<iframe width="640" height="360" src="https://www.youtube.com/embed/kCwf5IxBOQE??si=K4hr3BrPVpKTftsV&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&amp;lt;span class="fr-mk" style="display: none;"&amp;gt;&amp;amp;nbsp;&amp;lt;/span&amp;gt;</iframe><h3 id="isPasted">INDRO’S TAKE</h3>We’ve been watching Real Life Robotics with interest over the past year and we’re pleased to see the terrific progress that’s been made.“Robotics and automation can make things much easier for many businesses, but municipal permissions for more than a one-off demo have traditionally been tricky in this space,” says InDro Robotics CEO Philip Reece.“That’s starting to shift, but you can’t have public adoption and acceptance until these devices are actually in the field. And they can’t be put in the field without the vision and cooperation of municipalities. We’re pleased to see that Real Life Robotics has made gains in this area, and congratulate them on winning that important grant. We look forward to seeing RLR robots in the streets – somewhere – this summer.”For more information on RLR, including an investor deck, contact Cameron Waite&nbsp;<a href="Mailto:cameron@realliferobotics.com">here</a>.

New Team, Research Grant and Partners

Real Life Robotics Expands

Industry 5.0 is a new phase of industrialization that builds upon the fourth industrial revolution (Industry 4.0) by adding a people-centric approach. It is characterized by the extensive use of automation, data exchange, and smart manufacturing technologies in a manner that fosters the well-being of the workers. It bridges the gap of the unfulfilled promise of full automation from Industry 4.0 in processes where a human in the loop is still needed, &nbsp;increasing the competitiveness of the industry and helping attract the best talents.The ultimate goal is to create human-centric, efficient, flexible, and responsive production environments that can quickly adapt to changing market demands.To achieve this goal, this next generation of manufacturing environments leverages the latest available technologies to the entire production process. One of the key operational aspects of manufacturing is intralogistics -understood as the management, control, and optimization of internal material and information flows.&nbsp;Intralogistics 5.0 leverages automated material handling, Internet of Things (IoT), data analytics, and Artificial Intelligence (AI) to create smart, interconnected, data-driven production environments and empower human workers.&nbsp;This intralogistics evolution is not only adding efficiency to industrial processes but is also driving a shift in manufacturing, from large, rigid systems into modular, flexible, and robot-supported self-optimizing ones.<h2>Optimizing Material Handling with Visual AI-Enabled Robotic Vehicles</h2>Autonomous Mobile Robots (AMRs), equipped with Visual AI and orchestrated through a Fleet Management System (FMS) are at the forefront of this transformation. The shape and function of these AMRs range from autonomous forklifts, shuttle systems, tugger trains, and stackers to platform or mouse robots, goods-to-person, and pick-assist robots. Their material transport activities are ideally tracked directly by the Enterprise Resource Planning (ERP) system of the factory.AMRs are designed to navigate with agility and accuracy through complex factory environments using a combination of sensors, cameras, and real-time data processing. The integration of Visual AI enables them to perceive their surroundings, identify objects and obstacles, make informed decisions, and share information in real-time, adding a number of benefits at each step of the process:<ul><li id="isPasted">Enhanced Goods-In: Vehicles equipped with Visual AI contribute to this stage by autonomously transporting goods from receiving areas to designated storage locations reducing manual work and extending operation hours. Additionally, the visual input ensures accurate identification and categorization of incoming goods, feeding the ERP, and laying the foundation for precise inventory management.</li><li>Optimized Storage and Retrieval: Visual AI allows robotic vehicles to analyze available storage space and stack goods efficiently, optimizing storage capacity, ensuring timely retrieval of items, and providing real-time inventory updates.</li><li>Streamlined Production Supply: Visual AI makes autonomous intralogistics vehicles inherently flexible, thus they can optimize routes dynamically, ensuring a continuous and streamlined supply of materials to production lines.&nbsp;</li><li>Accurate Order Picking: Visual AI technology supports workers in order picking, significantly reducing error rates and ensuring accurate order fulfillment.‍</li><li>Efficient Dispatch and Goods-Out: Visual AI enables robotic logistics vehicles to perform order verification and optimize load onto transportation vehicles, adding efficiency to the preparation and organization of finished goods for delivery to customers or distribution centers.</li></ul><h2>Flexible Manufacturing</h2>Besides the optimization across the material handling process, and on account of their inherent reconfigurability, Visual AI AMRs can flexibly support diverse production scenarios, such as batch, mass, or customized production, and different manufacturing layouts, from linear or modular to cellular.&nbsp;Serving as flexible links between individual production stages, these robots are also fundamental in the transition from traditional rigid conveyor-belt-based manufacturing to flexible-cell manufacturing, where production units can be reconfigured and rearranged without downtime.&nbsp;This flexible movement and connection of production cells, create dynamic and modular production environments that can adapt to different product variants and volumes, to respond to changing customer demands and market conditions.<h2>Challenges on the Path Towards the Factories of the Future</h2>Visual AI allows operating this Factory of the Future today. While the technology is already here, its adaption and implementation are only starting to pick up speed. The transition to Intralogistics 5.0 and new levels of automation is mostly gradual and incremental as it requires interoperability, scalability, and human-robot collaboration.<h3>Interoperability</h3>Many manufacturing facilities and warehouses are currently operating with mixed fleets that consist of both manned and unmanned material-handling vehicles, and an initial and crucial challenge in the path toward Intralogistics 5.0 is to integrate both types of shop floor traffic into an all-encompassing FMS and ERP.At this stage, equipping manned vehicles -like forklifts, tuggers, or stackers- with Visual AI-enabled Real Time Location System (RTLS) to track their location and feed the system with the visual data they capture would enable an FMS to orchestrate floor traffic holistically.Adding observability to manned traffic and integrating it into an FMS cancels out typical shortcomings of mixed fleets such as human drivers colliding with AMRs, inefficient manned routing unobservable by the FMS, or inventory compromised by human errors.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAyOTAzNTU1NTQzLU1hbm5lZF9Vbm1hbm5lZF9UcmFmZmljX0ludGVncmF0aW9uX1NldmVuc2Vuc2VfUm9ib3RpY3MucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib">Visual AI-enabled RTLS feeding manned traffic data into an FMSThe Visual AI-enabled RTLS adds value in manufacturing and warehousing unlocking completely new opportunities in material handling applications, where some operations will continue to be performed using manned vehicles for the next 20+ years.To make the benefits of holistically managed mixed fleets broadly accessible to the market, Sevensense Robotics is developing a Visual AI-enabled RTLS, which is already available to early adopters.<h3>Scalability</h3>In many cases, as part of their automation journey, manufacturers opt for initially commissioning AMRs at a small scale in a dedicated sector of their facilities. However, expanding the AMRs’ operating space from a wing of a plant or to the entire factory has traditionally been time-consuming.Until now, it implied a complex and disruptive endeavor of stopping operations and dedicating specialized professionals to the map expansion. including running a vehicle in manual mode to scan the new areas of the facility where robots will operate, and then manually editing and merging the new maps.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1702909540635-Continous+map+updates+V2.gif" style="width: 302px;" class="fr-fic fr-dib">Lifelong Visual SLAM enables seamless map updatesTo solve this scalability blocker, Sevensense has developed a solution that makes the map expansion seamless. Combining continuous map updates -also known as Lifelong Visual SLAM- with swarm intelligence, robots equipped with this technology can automatically map the new sections of the environment and share the extended map with the rest of the fleet. All they need to start their exploration is an anchor point in the existing map and the expansion is computed on-the-fly.By automatically incorporating relevant changes in the environment, Sevensense’s Lifelong Visual SLAM also offers the key benefit of lifelong robust, high precision localization &lt;5mm (&lt;0.2in) without markers, reflectors, or beacons, allowing the robots to operate in dynamic, ever-changing environments.<h3>Human-Robot Collaboration</h3>An increasing number of companies are incorporating AMRs into their operations. However, the lack of seamless human-machine collaboration solutions poses the need for dedicated robotic operations zones or the introduction of robotic shifts, restricting their flexibility and efficiency while also limiting the ROI.Visual AI AMRs have the built-in capability of understanding the context of the environment, distinguishing between unobstructed paths, obstacles -and types of obstacles-, and adapting their behavior accordingly in real-time.When the robot encounters an obstacle, the system identifies the type of object, then estimates its velocity and predicts its trajectory, calculates the most efficient path, and automatically performs an obstacle avoidance maneuver, rerouting the robot.This navigation mode can boost efficiency, in particular in scenarios when robots share the shop floor with other robots, but it may not be the optimal solution when robots share the shop floor with people.&nbsp;On the one hand, as human behavior is less predictable, robots have less visibility of a person’s movement intent than they have on other mobile robots or RTLS-tracked manned vehicles. On the other hand, having a robot overtake people while walking across a facility may be perceived as unpredictable and unsafe, making human workers feel anxious.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAyOTAzNzkyNTUyLUh1bWFuX01hY2hpbmVfQ29sbGFib3JhdGlvbl9Sb2JvdF9OYXZpZ3Rpb25fU2V2ZW5zZW5zZV9Sb2JvdGljcy5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 300px;" class="fr-fic fr-dib">Visual AI is key to developing collaborative AMRsSolving the human-robot collaboration challenge is key to enabling Industry 5.0 and is motivating Sevensense’s work to solve this issue by combining scene understanding and a people-centric approach, to turn AMRs into Co-AMRs. The solution involves Visual AI perceiving the obstacle as a person and then commanding the robot to perform a people-friendly behavior such as stopping and waiting for the person to continue their movement or complete their task.To learn more about Sevensense Robotics and its Visual AI technology, visit <a href="https://www.sevensense.ai/" target="_blank" rel="noopener noreferrer">sevensense.ai</a>

Visual AI enables Autonomous Mobile Robots to fulfil Industry 5.0 requirements

Visual AI is applied to overcome the obstacles in the path of the Factories of the Future

Autonomous Mobile Robots Powering Industry 5.0

Engineers at Princeton University and Google have come up with a new way to teach robots to know when they don’t know. The technique involves quantifying the fuzziness of human language and using that measurement to tell robots when to ask for further directions. Telling a robot to pick up a bowl from a table with only one bowl is fairly clear. But telling a robot to pick up a bowl when there are five bowls on the table generates a much higher degree of uncertainty — and triggers the robot to ask for clarification.Because tasks are typically more complex than a simple “pick up a bowl” command, the engineers use large language models (LLMs) — the technology behind tools such as ChatGPT — to gauge uncertainty in complex environments. LLMs are bringing robots powerful capabilities to follow human language, but LLM outputs are still frequently unreliable, said <a href="https://engineering.princeton.edu/faculty/anirudha-majumdar" target="_blank">Anirudha Majumdar</a>, an assistant professor of <a href="https://mae.princeton.edu/" target="_blank">mechanical and aerospace engineering</a> at Princeton and the senior author of a <a href="https://openreview.net/forum?id=4ZK8ODNyFXx" target="_blank">study</a> outlining the new method.“Blindly following plans generated by an LLM could cause robots to act in an unsafe or untrustworthy manner, and so we need our LLM-based robots to know when they don’t know,” said Majumdar.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1701898003603-knowno-ambiguities_WEB-2048x871.jpg" style="width: 766px;" class="fr-fic fr-dib">The researchers tested their method on a simulated robotic arm and on two types of robot hardware. The most complex experiments (left) involved a robotic arm mounted on a wheeled platform and placed in an office kitchen with a microwave and a set of recycling, compost and trash bins. Another set of experiments used a tabletop robotic arm (right) tasked with sorting a set of toy food items into two different categories; a setup with a left and right arm (center) added an additional layer of ambiguity. Images by the researchersThe system also allows a robot’s user to set a target degree of success, which is tied to a particular uncertainty threshold that will lead a robot to ask for help. For example, a user would set a surgical robot to have a much lower error tolerance than a robot that’s cleaning up a living room.“We want the robot to ask for enough help such that we reach the level of success that the user wants. But meanwhile, we want to minimize the overall amount of help that the robot needs,” said&nbsp;<a href="https://allenzren.github.io/" target="_blank">Allen Ren</a>, a graduate student in mechanical and aerospace engineering at Princeton and the study’s lead author. Ren received a&nbsp;<a href="https://www.corl2023.org/awards" target="_blank">best student paper award</a> for his Nov. 8 presentation at the Conference on Robot Learning in Atlanta. The new method produces high accuracy while reducing the amount of help required by a robot compared to other methods of tackling this issue.The researchers tested their method on a simulated robotic arm and on two types of robots at Google facilities in New York City and Mountain View, California, where Ren was working as a student research intern. One set of hardware experiments used a tabletop robotic arm tasked with sorting a set of toy food items into two different categories; a setup with a left and right arm added an additional layer of ambiguity.The most complex experiments involved a robotic arm mounted on a wheeled platform and placed in an office kitchen with a microwave and a set of recycling, compost and trash bins. In one example, a human asks the robot to “place the bowl in the microwave,” but there are two bowls on the counter — a metal one and a plastic one.The robot’s LLM-based planner generates four possible actions to carry out based on this instruction, like multiple-choice answers, and each option is assigned a probability. Using a statistical approach called conformal prediction and a user-specified guaranteed success rate, the researchers designed their algorithm to trigger a request for human help when the options meet a certain probability threshold. In this case, the top two options — place the plastic bowl in the microwave or place the metal bowl in the microwave — meet this threshold, and the robot asks the human which bowl to place in the microwave.In another example, a person tells the robot, “There is an apple and a dirty sponge … It is rotten. Can you dispose of it?” This does not trigger a question from the robot, since the action “put the apple in the compost” has a sufficiently higher probability of being correct than any other option.“Using the technique of conformal prediction, which quantifies the language model’s uncertainty in a more rigorous way than prior methods, allows us to get to a higher level of success” while minimizing the frequency of triggering help, said the study’s senior author&nbsp;<a href="https://engineering.princeton.edu/faculty/anirudha-majumdar" target="_blank">Anirudha Majumdar</a>, an assistant professor of mechanical and aerospace engineering at Princeton.Robots’ physical limitations often give designers insights not readily available from abstract systems. Large language models “might talk their way out of a conversation, but they can’t skip gravity,” said coauthor&nbsp;<a href="https://andyzeng.github.io/" target="_blank">Andy Zeng</a>, a research scientist at Google DeepMind. “I’m always keen on seeing what we can do on robots first, because it often sheds light on the core challenges behind building generally intelligent machines.”Ren and Majumdar began collaborating with Zeng after he gave a talk as part of the&nbsp;<a href="https://robo.princeton.edu/seminar" target="_blank">Princeton Robotics Seminar</a> series, said Majumdar. Zeng, who earned a computer science Ph.D. from Princeton in 2019, outlined Google’s efforts in using LLMs for robotics, and brought up some open challenges. Ren’s enthusiasm for the problem of calibrating the level of help a robot should ask for led to his internship and the creation of the new method.“We enjoyed being able to leverage the scale that Google has” in terms of access to large language models and different hardware platforms, said Majumdar.Ren is now extending this work to problems of active perception for robots: For instance, a robot may need to use predictions to determine the location of a television, table or chair within a house, when the robot itself is in a different part of the house. This requires a planner based on a model that combines vision and language information, bringing up a new set of challenges in estimating uncertainty and determining when to trigger help, said Ren.The paper, “<a href="https://openreview.net/forum?id=4ZK8ODNyFXx" target="_blank">Robots That Ask for Help: Uncertainty Alignment for Large Language Model Planners</a>,” was presented Nov. 8 at the Conference on Robot Learning. In addition to Ren, Zeng and Majumdar, coauthors include Anushri Dixit and Alexandra Bodrova of Princeton; and Sumeet Singh, Stephen Tu, Noah Brown, Peng Xu, Leila Takayama, Fei Xia, Jake Varley, Zhenjia Xu and Dorsa Sadigh of Google DeepMind. The research was supported in part by the U.S. National Science Foundation and the Office of Naval Research.

Engineers at Princeton University and Google have come up with a new way to teach robots to know when they don’t know and ask for clarification from a human. Photo by the researchers

Modern robots know how to sense their environment and respond to language, but what they don’t know is often more important than what they do know. Teaching robots to ask for help is key to making them safer and more efficient.

How do you make a robot smarter? Program it to know what it doesn't know.

So: You’ve got a great idea for a new technology product or process.That’s the first step: A concept that you’ve put some thought into. Of course, there’s a long road ahead before that brilliant idea becomes an actual commercial product. But how do you gauge that progress as you move along the development path? How would you describe where you’re at in a way that others might quickly grasp?Luckily, there’s a tool for that. It’s called the Technology Readiness Levels scale, or TRL.“It’s a&nbsp;standard measuring stick for everyone to communicate where they are with development,” explains InDro Robotics Engineering Lead Arron Griffiths.The TRL tool was first developed by NASA researcher Stan Sadin back in 1974 with seven basic levels. It would take another 15 years before the levels were formally defined, during which time two additional levels were added. There are now nine steps up the ladder, where TRL 9 is the equivalent of a working product that could be mass-produced or commercialized.Which means, of course, that Level 1 is at the very beginning of the technology development process.“Level 1 is universally seen as a napkin idea – where you’ve jotted down a concept,” says Griffiths.That’s a perfect analogy for TRL 1.For greater clarity, each level on the scale offers a short definition, a description, and examples of activities. The short definition for Level 1 is “Basic Principles Observed and Reported.” The description is “Lowest level of technology readiness. Scientific research begins to be translated into applied research and development (R&amp;D).”In terms of examples, Level 1 “Activities might include theoretical studies of a technology’s basic properties.” And yes, that could include a napkin sketch.Below: Aerospace is one of many industries to use TRLs. The noise-reducing chevron nozzles seen on the cowling below would have gone through each of the nine levels. Photo via Wikimedia Commons by John Crowley.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAxNzg5OTkyNjc5LUdlbmVyYWxfRWxlY3RyaWNfR0VueC0xQl8xNDIzMzQ5Nzc3Nl9jcm9wcGVkLWpwZWcud2VicCIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"> <h3 id="isPasted">Moving Up The TRL Scale</h3>Great! You’ve got that napkin sketch done.Obviously there’s a lot to do between that initial idea and a finished product suitable for commercialization. To get to TRL 2, you simply need to put more thought into it. You’re not actually building or programming yet, just putting greater clarity and focus on what you hope to accomplish.TRL 2 is defined as “Technology concept and/or application formulated.” Here’s its <a href="https://www.canada.ca/en/department-national-defence/programs/defence-ideas/technology-readiness-level.html" target="_blank" rel="noopener noreferrer">description</a>:“Invention begins. Once basic principles are observed, practical applications can be invented. Applications are speculative, and there may be no proof or detailed analysis to support the assumptions.”You could think of this stage as refining the idea, with activities limited to research and/or analytical studies.TRL 3 means you’re actually beginning the R&amp;D process. This might include some lab or analytical studies. At this stage you’re trying to validate predictions you’ve made about separate elements or components of the technology. The components you’re working with aren’t yet integrated – nor is it expected that the components you’re working with are at their final version. <h3>Two TRL Scales</h3>Before we move along, it’s worth noting there are actually two different TRL scales in use. The first (and the one we’re using here) is the NASA scale. But the European Union has its own TRL scale.&nbsp;“So there is some cloudiness,” explains Griffiths. “Typically the top and bottom of the scales are the same, but the middle moves around a bit. You have to be sure people are reading from the same scale. Typically when I talk to a client, I will show them the scale I am using.”Griffiths also emphasizes that during R&amp;D, the phase of development doesn’t always slot neatly into one of the TRL stages.&nbsp;“It’s typical to say: ‘We’re roughly about TRL 6’ – it’s not an exact science.”Below: The&nbsp;<a href="https://indrorobotics.ca/commander/" target="_blank" rel="noopener noreferrer">InDro Commander</a>&nbsp;module, with LiDAR sensor. This popular commercial product, which allows for rapid integration of ROS-based robots and sensors (and more), is TRL 9.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAxNzkwMTI5MzIxLUluRHJvLUNvbW1hbmRlci0xLjYtY29weS5qcGcud2VicCIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib" alt="InDro Commander Platform Agnostic Brain Box"> <h3 id="isPasted">Climbing The Ladder&nbsp;</h3>American inventor Thomas Edison once said: “Genius is one per cent inspiration and ninety-nine per cent perspiration.” The same could be said of the process of inventing a product for commercialization. Once that napkin sketch is done (the one per cent), there’s still a lot of methodical slogging ahead. (Trust us, we know.)TRL 4 is the stage where you’re putting things together. Basic components are integrated and readied for testing in a simulated environment. The short definition, via Canada’s <a href="https://www.canada.ca/en/department-national-defence/programs/defence-ideas/technology-readiness-level.html" target="_blank">Department of National Defence</a>, is “Component(s)/subsystem(s) and/or process validation in a laboratory environment.”The logical progression continues with the next step.“TRL 5 means it’s ready for testing in a lab environment,” explains InDro Lead Engineer Griffiths. He also adds that this middle stage – TRL 4 through 7 – “is always the difficult part.”Once TRL 5 is passed, it’s time to start seeing if the integrated components will work together in a simulated or lab environment. At this stage, TRL 6, the product is considered to be getting pretty close to its desired configuration. Yes, there will be further tweaking to come, but you’re getting there.Below: InDro’s Street Smart Robot (the large white unit). The product has been built but not yet deployed in winter conditions. This would be at TRL 7. Every other robot in this image would have made it to TRL 9.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1701791421275-DSCF4031-jpg.webp" style="width: 731px;" class="fr-fic fr-dib"> <h3 id="isPasted">Nearly There!</h3>All that hard work has been paying off. Your product is assembled and has been tested in simulation or other lab environment. Now it’s time to get it out into the real world to see how it performs. Congratulations, you’ve reached TRL 7, where “Prototype system [is] ready (form, fit, and function) for demonstration in an appropriate operational environment.”“TRL 7 is more like a long-term&nbsp;deployment. Once you can show it to be working in a real-world environment – outside of the lab – then you get to Levels 8 and 9,” says Griffiths.These final two levels are usually pretty exciting. Once the product/solution has been proven to work in its final form – and in the environment where it’s expected to be deployed as a product – you’ve reached TRL 8. Just one more to go.&nbsp;<h3>The Final Level</h3>Remember that Street Smart Robot you just saw a picture of? Well, it’s ready to go. And once the wintry conditions take hold in Ottawa, we’ll be operating that machine in ice and snow on Ottawa streets. Specifically, on bike lanes in Ottawa, where it will detect hazardous conditions (including potholes) that might pose challenges for safe cycling. City of Ottawa maintenance crews will then be notified of the problem (and its location) so they can address the issue. (You can read more about the SSR <a href="https://indrorobotics.ca/streetsmart-inspectionrobot/" target="_blank">here</a>.)And once the SSR is operating smoothly in those intended conditions? We will have achieved TRL 9, meaning “Actual solution proven through successful deployment in an operational setting.” <h3>Not Always A Smooth Path</h3>It’s easy enough to describe these levels. And in doing so, it can appear to be a straightforward, linear path where engineers move seamlessly from one level to the next. Reality is not quite so simple. Depending on the project, progress in the early stages can be made very rapidly.“Most people get up to Level 5 fairly quickly,” says Griffiths. “You can even get to Level 5 in a day if you’re doing software development – you can literally go from an idea all the way up to a basic rudimentary prototype.”But – as flagged earlier – things get a little trickier once you hit those middle levels.“You can think of it as walking up a hill to Level 5,” he says. “Then there’s this valley. A lot of stuff dies in Level 6 and 7. There’s not a lot of success there because once you push the technology into actual environments the success rate is very low. So a lot of time is spent in Levels 5 and 6 trying to make a system that can make it to Level 7 successfully, and then on to Level 8 – where you’re essentially across the valley.”Below: A graphic outlines the short definitions of Technology Readiness Levels<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1701791491699-TRL+Scale.png" style="width: 766px;" class="fr-fic fr-dib"> <h3 id="isPasted">InDro's Take</h3>The TRL scale is extremely useful in the R&amp;D world, in that it concisely conveys where a product is along the path to commercial development. And while it’s great for engineers, it’s also useful to help clients understand where one of our products is along that journey.We’ve scaled this ladder many times over the years. Sometimes it’s a relatively easy climb. But, like all Research and Development companies, we’ve also had a few products that never made it beyond the valley Arron Griffiths described. That’s R&amp;D.“The Technology Readiness Level scale is a really useful tool, and part of our daily language at InDro Robotics,” says CEO Philip Reece. “Each level represents unique challenges – and that valley Arron described can sometimes be a disappointing bit of landscape. But we learn something even with the occasional failure.“Thankfully, we have a creative and tenacious engineering team that seems to thrive on difficult challenges – and InDro now has a growing stable of products that have achieved TRL 9 and gone on to commercial success.”If you’re working on your own project and would like to know where it is on the TRL scale, you can use this <a href="https://ised-isde.canada.ca/site/clean-growth-hub/en/technology-readiness-level-trl-assessment-tool" target="_blank">assessment tool</a> from Industry, Science and Economic Development Canada.

A Guide to Understanding Technology Readiness Levels

Technology Readiness Levels Explained

There’s nothing like synergy. And a new high-precision solution for location and heading – a collaboration between <a href="https://indrorobotics.ca" target="_blank" rel="noopener noreferrer">Indro Robotics</a> and <a href="https://www.tallysman.com" target="_blank" rel="noopener noreferrer">Tallysman Wireless</a> – is the result.As you likely know, while GPS is great – and good enough for us driving around using WAZE – its accuracy can leave something to be desired. Traditional Global Navigation Satellite System (GNSS) solutions generally are accurate to around 2.5 metres Circular Error Probability (CEP). That means the reported location has a 50 per cent chance of being within 2.5 metres of where it actually is. What’s more, that error rate exists under ideal conditions – with the detection system stationary and with an unobstructed view of satellites.That’s good enough for a car with a driver, or a cargo ship. But many robotic applications require far greater precision. If you’re running a remote inspection robot using GPS waypoints, 2.5 metres isn’t good enough.Think about it. In the example of a remote inspection robot, the device is generally operating at the location of a high-value asset. You might want a repeatable routine where the robot can get up close to look at gauges, valves, or anything else requiring inspection. You might want it to pass through a doorway, or get very close to – without touching – a highly energised electrical component. So accuracy matters, whether in this application or many other use-cases.Now, InDro and Tallysman Wireless, a Calian company, are pleased to announce a solution.Below: An InDro Sentinel inspection robot<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk5NDY1MzQ4MzgwLTIwMjIwNDI3XzE2NDU0NDAwOF9pT1MgY29weS5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 300px;" class="fr-fic fr-dib"><h3>Location, Location, Location</h3>That real estate phrase certainly applies when it comes to high-level robotics. But how do you get from a potential error of 2.5 metres down to, say, 2.5 centimetres – two orders of magnitude?In this case, the solution came by partnering with Tallysman Wireless.The company is known for its leading-edge GNSS and Iridium antennas. Tallysman also has an enviable reputation for customising those antennas for global clients seeking specific GNSS solutions. Ships, aircraft, trains and even drones carry out critical missions daily while relying on Tallysman solutions. InDro, meanwhile, is known for its R&amp;D work, robots and custom innovations in the aerial and ground robotics world. So the potential was there for collaboration.Because – and we know this well – it’s not just as simple as plugging antennas and receivers together and hoping for the best.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk5NDY1Njg1Njk5LVNjcmVlbnNob3QtMjAyMy0wOS0yNi1hdC0xLjUzLjE4LVBNLnBuZy53ZWJwIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"><h3 id="isPasted">The Issue(s)</h3>Antennas – even really good ones – are finicky pieces of equipment. Depending on what you’re mounting them on, they can be subject to interference that diminishes their performance. The type of connector attaching them to a receiver, even the length of the cable used in that connection, can also detract from optimal signal acquisition and accuracy. That’s why you want someone like Tallysman Wireless on board.“We are experts in Global Navigation Satellite System (GNSS) solutions, specifically the antennae side of &nbsp;things,” explains Gord Echlin, Tallysman’s Director of Business Development.“A lot of people assume, unless you use the term GPS, that it’s a fairly easy thing to implement and get accurate results. Nothing could be farther from the truth.”As Tallysman Wireless explains in a brochure:“The problem is that keeping the antenna to system interface in the analog domain requires a lot of RF expertise to manage, expertise that is not widely available, and these issues amplify with long signal transmission over cables.&nbsp;Digital systems with built-in LTE communication links, common components of autonomous systems, are direct threats to the integrity of the GNSS signal.&nbsp;“Tallysman Wireless has solved this problem by integrating their sensitive, high performance, GNSS antennas in the same package as advanced GNSS receivers, in what is commonly called a ‘Smart’ Antenna. The GNSS processing solution is in compact, carefully engineered to mitigate the potential impairments between the antenna and receiver, and the Position/Navigation/Timing (PNT) information is now communicated to application system over in the digital domain, over a serial interface (UART, USB, CANbus, or Automotive Ethernet).”Or, as Echlin puts it: “We take the receiver, and we take the antenna and put it in the same package to mitigate the outside interference such that you get less than two centimetres of error. That, along with very precise heading information – with accuracy to 0.3 degree.” <h3>The InDro Connection</h3>With the Tallysman Wireless integrated solution, there was just one more piece of the puzzle remaining. How to integrate this into a robot? That’s where InDro’s engineering team came along.The package required a software interface where none had existed before. InDro engineers created a ROS2 coding solution and integrated the Tallysman smart antenna onto our InDro Backpack – which we use with Unitree quadrupeds.InDro Backpack is our system for remote teleoperations over 5G (and 4G), which also allows for rapid sensor integration and other customization using ROS1 and ROS2 software libraries (which, along with an EDGE computer and high-speed modem, are on-board).The complete solution – hardware and software – enable consistent, high-accuracy positioning. InDro Plans to offer this complete solution to clients in need of precision positioning.Below: The Tallysman Smart Antenna solution, integrated with new ROS2 coding into the InDro Backpack<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk5NDY1ODE5MjkyLTIwMjMwOTA2XzEzNDcxOS1qcGVnLndlYnAiLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib">InDro was pleased to partner with Tallysman Wireless on this integration project. With robots increasingly used for remote inspection of high-value assets, accurate positioning and heading data has become essential.“Being able to tap into the expertise of Tallysman Wireless – and combine their solution with software from InDro engineers – has resulted in a powerful solution,” says InDro Robotics CEO Philip Reece.“We’ve already begun integrating this onto our own robots, and look forward to offering this to clients in need of the most accurate and reliable positioning possible.”Looking for more information? <a href="https://indrorobotics.ca/connectwithanexpert/" target="_blank" rel="noopener noreferrer">Connect with us HERE</a>.&nbsp;

GNSS Solution for Ground Robots

InDro Robotics and Tallysman Partner on a New Precision GNSS Solution for Ground Robots

The Robot Operating System (ROS) has been a game-changer in the world of robotics, enabling developers to create and manage complex robot systems with ease. However, as technology evolves, so does the need for more advanced tools and capabilities. This has led to the development of ROS 2, the successor to ROS 1, and it's gaining traction rapidly among developers. Let's explore the key differences between ROS 1 and ROS 2 and why many developers are making the switch:<h3>ROS 1: The Foundation</h3>ROS 1, often referred to simply as ROS, was introduced in 2007 and quickly became the go-to framework for robot development. It provided a flexible and modular architecture for building robotic applications, and its extensive library of packages and tools made it an attractive choice for developers. ROS 1 was built on a message-passing middleware called ROS Master, which uses the DDS (Data Distribution Service) communication standard for inter-process communication.<h3>ROS 2: The Evolution</h3>ROS 2 was introduced as the successor to ROS 1 and addresses several limitations that developers encountered with the original system. Some of the key differences and improvements <a href="http://design.ros2.org/articles/changes.html" target="_blank" rel="noopener noreferrer">outlined by the ROS organization</a> in ROS 2 include:<ol><li>Real-time Support: ROS 2 offers enhanced real-time capabilities, making it suitable for safety-critical and time-sensitive applications, which were challenging to achieve with ROS 1.</li><li>Middleware Agnostic: Unlike ROS 1, which relies on the ROS Master, ROS 2 is middleware agnostic. This means it can support multiple middleware systems, such as DDS, Fast RTPS, and more. This flexibility allows for better compatibility with various hardware and network configurations.</li><li>Improved Security: ROS 2 incorporates improved security features, ensuring that robotic systems can operate securely in environments where data integrity and confidentiality are paramount.</li><li>Enhanced Cross-Platform Compatibility: ROS 2 has been designed with cross-platform compatibility in mind, making it easier to run on various operating systems, including Windows.</li><li>Simplified Dependency Management: ROS 2 streamlines package management, reducing dependencies and making it easier to manage the libraries and modules required for a project.</li></ol>Here's a chart outlining some of the key technical differences between ROS and ROS2:<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk4OTQ1ODI4MDE5LVJPUyB2cyBST1MyIENoYXJ0LnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"><h3>Why More Developers Are Making the Switch:</h3>Improved Real-time Capabilities: ROS 2's support for real-time systems is a significant attraction for developers working on applications where timing and synchronization are crucial, such as autonomous vehicles and industrial automation.Middleware Flexibility:&nbsp;ROS 2's middleware agnosticism allows developers to choose the best communication middleware for their specific use case, ensuring better integration with different hardware and network configurations.Enhanced Security: With an increased focus on security, ROS 2 provides a safer platform for robots operating in critical environments, including healthcare, defense, and manufacturing.Cross-Platform Compatibility: ROS 2's compatibility with various operating systems, including Windows, opens up new possibilities for developers and allows for a broader range of deployment options.Long-Term Support: ROS 2 is well-supported and continually updated, providing developers with a future-proof platform for their projects. ROS 1 is no longer under active development, which means that it may not receive the same level of support and enhancements.Overall, ROS 2 is designed to address some of the limitations and challenges of ROS 1, such as scalability, performance, security, and cross-platform compatibility. While both ROS 1 and ROS 2 have the same core functionality, many differences exist between the two, and the decision to use one over the other depends on specific use cases and requirements. To see a more in-depth analysis please <a href="https://roboticsbackend.com/ros1-vs-ros2-practical-overview/" target="_blank" rel="noopener noreferrer">visit “roboticsbackend”</a>.Here's what InDro's Engineering Manager, Arron Griffith, had to say: "Now is the time to make the switch to ROS 2 (or start using it). ROS 2 has matured over the 5 years to equal or better than ROS 1 after its first 5 years. Plus ROS 1 will be going <a href="http://wiki.ros.org/Distributions" target="_blank" rel="noopener noreferrer">End of Life over the next 2 years</a>, so there is no point in starting with ROS 1 anymore, the future is ROS 2".As the robotics industry continues to advance, ROS 2 is expected to play a pivotal role in shaping the future of robot development. If you're a developer, it's time to consider making the switch to ROS 2 to harness its full potential. &nbsp;Questions about ROS or ROS2? &nbsp;<a href="https://indrorobotics.ca/connectwithanexpert/" target="_blank" rel="noopener noreferrer">Connect with an expert HERE.</a>

Why Developers Are Making the Switch

ROS 1 vs. ROS 2

Building robots is hard.Even if you start with a manufactured platform for locomotion, the work ahead can be challenging and time-consuming. How many sensors will require a power supply and data routing? What EDGE processing is needed? How will a remote operator interface with the machine? What coding will allow everything to work in unison and ensure the best data and performance possible? How will data be transmitted or stored?That’s the hard stuff, which inevitably requires a fair bit of time and effort. &nbsp;Typical robotics development is lengthy, it can take anywhere from 3 to 12 months from idea to a functional robot rolling around. The more complex the robotic solution, the more time it takes. <a href="https://indrorobotics.ca/commander/" target="_blank" rel="noopener noreferrer">InDro Commander</a> can reduce this to 1 to 3 months, depending on the complexity, plus InDro Robotics provides clients with software tutorials and one-on-one support.It’s that hurdle – one faced by pretty much everyone in the robotics R&amp;D world – that led to the creation of InDro Commander.<h2><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1Njc2MjEwMDg5LUNvbW1hbmRlciBvbiBCdW5rZXIuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"></h2><h2>What Does InDro Commander Do?</h2><a href="https://indrorobotics.ca/commander/" target="_blank" rel="noopener noreferrer">InDro Commander</a> is a platform-agnostic module that can bolt on to pretty much any means of locomotion. In the photo above, it’s the box mounted on top of the AgileX bunker (just above the InDro logo). &nbsp;Commander is a single box with critical software and hardware designed to simplify payload integration and enable turn-key tele-operations. &nbsp;Whether you’re adding LiDAR, thermal sensors, RTK, Pan-Tilt-Zoom cameras – or pretty much any other kind of sensor – Commander takes the pain out of integration. &nbsp;With its modular system, reduced development time, software tutorials and one-on-one support, clients can get their robot solution to market faster and with less hassle.The module offers multiple USB inputs for sensors, allowing developers to decide on a mounting location and then simply plug them in. A powerful Jetson EDGE computer handles onboard compute functions. The complete Robot Operating System software libraries (ROS1 and ROS2) are bundled in, allowing developers to quickly access the code needed for various sensors and functions.“Our engineering team came up with the concept of the InDro Commander after integrating and customizing our own robots,” says Philip Reece, CEO of InDro Robotics. “We realized there were hurdles common to all of them – so we designed and produced a solution. Commander vastly simplifies turning a platform into a fully functioning robot.”Account Executive, Luke Corbeth takes it further:“The Commander serves as a “brain-box” for any UGV,” he says. “It safely houses the compute, connectivity, cameras, sensors and other hardware in an IP54 enclosure.”It also comes in several options, depending on the client’s requirements.“There are three ‘standard versions’ which are bundles to either be Compute Ready, Teleoperations Ready or Autonomy Ready,” adds Corbeth.“I’ve realized over time that the value of Commander is our ability to customize it to include, or more importantly, not include specific components depending on the needs of the project and what the client already has available. In reality, most Commanders I sell include some, but not usually all, of what’s in the Commander Navigate. We’re also able to customize to specific needs or payloads.”Below: Commander comes in multiple configurations<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1Njc0MDk1MDA2LVNjcmVlbnNob3QtMjAyMy0wOS0xOS1hdC0yLjMzLjQ2LVBNLnBuZy53ZWJwIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"><h2>Commander Does The Work</h2>With InDro Commander, developers can spend more time on their actual project or research – and far less time on the build.“For end-users wanting a fully customized robot, Commander saves a huge amount of time and hassle,” says InDro Engineering Lead, Arron Griffiths. “Customers using this module see immediate benefits for sensor integration, and the web-based console for remote operations provides streaming, real-time data. Commander also supports wireless charging, which is a huge bonus for remote operations.”Commander serves as the brains for several InDro ground robots, including Sentinel. This machine was recently put through its paces over 5G in a <a href="https://indrorobotics.ca/putting-sentinel-through-its-paces-at-epri/" target="_blank">test for EPRI</a>, the Electric Power Research Institute.Below: Commander is mounted on Sentinel, a site based autonomous robot, capable of complete continuous monitoring of infrastructure, with the ability to carry out autonomous inspection rounds with thermal, RGB and zoom sensors, for recognition of change detection.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1NjczODM5MTAwLVNlbnRpbmVsIEVQUkkuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii"><h2>5G Operations</h2>Depending on the model, Commander can also serve as a plug &amp; play device for operations over 4G or 5G networks. In fact, InDro was invited by US carrier T-Mobile to a 2022 event in Washington State to demonstrate&nbsp;the live, remote tele-operation of a Sentinel inspection robot.Using a simple Xbox controller plugged into a laptop at T-Mobile HQ in Bellevue WA, we operated a Sentinel in Ottawa – more than 4,000 kilometres away. There was no perceptible lag, and even untrained operators were able to easily control remote operations and cycle between the Pan Tilt Zoom camera, a thermal sensor, and a wide-angle camera used for situational awareness by the operator. Data from all sensors was displayed on the dashboard, with the ability for the operator to easily cycle between them.Below: T-Mobile’s John Saw, Executive Vice President, Advanced &amp; Emerging Technologies, talks about InDro Commander-enabled robots teleoperating over 5G networks&nbsp;<iframe width="640" height="360" src="https://www.youtube.com/embed/-C88iEnsh7E?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&amp;lt;span class="fr-mk" style="display: none;"&amp;gt;&amp;amp;nbsp;&amp;lt;/span&amp;gt;&amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;gt;&amp;amp;amp;nbsp;&amp;amp;lt;/span&amp;amp;gt;&amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;gt;&amp;amp;amp;amp;nbsp;&amp;amp;amp;lt;/span&amp;amp;amp;gt;&amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;span class="fr-mk" style="display: none;"&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/span&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;</iframe><h2 id="isPasted">Future-Proof</h2>Platforms change. Needs evolve. New sensors hit the market.With Commander on board, developers don’t need to start from scratch. The modular design enables end-users to seamlessly upgrade platforms down the road by simply unbolting Commander and affixing it to the new set of wheels (or treads).Any sensor, including LiDAR, can be quickly integrated with InDro Commander.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1Njc1MDA4NjA2LVNjcmVlbnNob3QgMjAyMy0wOS0yNSBhdCA0LjQ5LjIzIFBNLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"> You likely know the saying: “Necessity is the mother of invention.”InDro developed this product because we could see its utility – both for our own R&amp;D, and for clients. We’ve put Commander to use on multiple custom InDro robots, with many more to come. (We have even created a version of this for Enterprise drones.)“On the commercial side, our clients have really benefited from the inherent modularity that the Commander provides,” says Luke Corbeth.“Since the ‘brains’ are separate from the ‘body,’ this simplifies their ability to make the inevitable repairs or upgrades they’ll require. These clients generally care about having a high functioning robot reliably completing a repetitive task, and Commander allows us to operate and program our robots to do this.”It can also save developers money.“On the R&amp;D side, the customizable nature of the Commander means they only purchase what they don’t already have,” adds Corbeth.“For instance, many clients are fortunate enough to have some hardware already available to them whether it’s a special camera, LiDAR or a Jetson so we can support the integration of their existing systems remotely or they can send this hardware directly to us. This cuts down lead times and helps us work within our clients’ budgets as we build towards the dream robot for their project.”Still have questions or want to learn more about Commander?&nbsp;<a href="https://indrorobotics.ca/commander/" target="_blank" rel="noopener noreferrer">Click HERE.</a>

A platform-agnostic module that can bolt on to pretty much any means of locomotion

InDro Commander Streamlines Robotics Research and Development

Delineating cobots and industrial robots, this analysis drives deep into their respective roles and divergent characteristics that make each a vital cog in the machinery of Industry 4.0.

Cobots vs Robots: Understanding the Key Differences and Applications

<h2 id="isPasted">How Forward AM and OECHSLER Enable Robots and Humans to Collaborate Safely at Profitable Speed</h2>In today&rsquo;s modern factories around the globe, many production steps are automated and carried out by robots.<div data-parent="true" data-section="2"><div data-imgready="true"><div data-imgready="true"><hr>Humans sharing a workspace and collaborating with robots has become a reality that companies and their smart factories just can&rsquo;t do without, as it allows flexible manufacturing in variable batch sizes with maximum efficiency. In short, successful human-machine interaction is key for future-proof manufacturing.</div>With Additive Manufacturing (AM), it is now possible to create new functionalities for robots and to unlock novel possibilities. The AM technology is perfectly suited for the production of small, customized batches for robotic parts like grippers &ndash; and it is ideally capable to integrate internal ducts, as air pressure and vacuums play an important role in this industry.</div></div><div data-parent="true" data-section="3"><div data-imgready="true"><h2>The challenge &ndash; safe human-robot collaboration at profitable speed</h2>Collaborative robots (short: cobots) become increasingly present in manufacturing. Designed to work alongside humans in shared areas, they work together &lsquo;hand in hand&rsquo; &nbsp;&ndash; which makes it crucial to ensure safety by avoiding collisions of cobot and human co-worker.This is prevalently achieved by inherent optical sensors which trigger an immediate stop of the cobot in case of unexpected contact: whenever a human co-worker enters the defined warning zone, the system lowers its speed to a minimum and if the person keeps approaching, the system stops &ndash; only after the individuum departs, the system accelerates back to full speed. It&rsquo;s obvious: this results in highly limited processing speeds of the cobot and thus higher cost and lower productivity for the manufacturing company. These interruptions in the workflow may lead to unstable cycle times as well, and foremost &ndash; it is absolutely contrary to the intention of cobots being deployed flexibly and easy to integrate as a plug-and-play system: To achieve an appropriate reaction to an approaching human co-worker, cobots have to be programmed accordingly; always depending on the cobot&rsquo;s task, its exact form of cooperation with the human worker, and its physical position in the factory. Whenever the cobot is deployed at another workstation on the assembly line, or performs different tasks and movements, its programming has to be adapted. This limited flexibility only allows pre-defined reactions of the cobot.</div></div><div data-parent="true" data-section="4"><div data-imgready="true"><h2>The solution &ndash; a protective lattice skin for cobots made of Forward AM&rsquo;s Ultrasint&reg; TPU01</h2><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjg2MTI0MTYzMjMxLWZvcndhcmQtYW0tdXNlLWNhc2UtY29ib3RpY3Mtcm9ib3NraW4tMy0xLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"><div id="isPasted"><div>The cobot Kuka iiwa with mounted RoboSkin made from lattice structures printed with Ultrasint&reg; TPU01. (Source: OECHSLER).&nbsp;</div></div> A new approach by Forward AM and OECHSLER, a leading German polymer processing company, enables humans and cobots to share a workspace without any safety risks and manufacturing companies to keep productivity constantly high.How? By adding a new layer to the current solution &ndash; literally. A thin, high cushioning second &lsquo;skin layer&rsquo; is wrapped around the cobot&rsquo;s joints. Using Forward AM&rsquo;s <a href="https://forward-am.com/find-material/powder-bed-fusion/ultrasint-tpu-line/tpu01/" target="_blank">Ultrasint&reg; TPU01</a> to 3D print the RoboSkin enables a flexible and individualized lattice structure. <a href="https://forward-am.com/find-material/powder-bed-fusion/ultrasint-tpu-line/tpu01/" target="_blank">Ultrasint&reg; TPU01</a> is a thermoplastic polyurethane powder specifically designed for HP 5200 series Multi Jet Fusion printers. This flexible material is ideal for producing parts requiring high shock absorption at excellent flexibility depending on the functional requirements of the application, making it the perfect match for the cobot&rsquo;s protective skin and its cushioning function.The benefits of the lattice RoboSkin are manifold. Putting safety first, it reduces the risk of injuries to human workers interacting with the cobot. At the same time, production speed can be increased strikingly: Since the collision forces and pressures are highly damped by the RoboSkin, the cobot&rsquo;s speed can accordingly be higher up to 150 percent&ndash; thus enabling increased productivity for the manufacturer.The overall handling of the skin is easy: Because the RoboSkin works as a mechanical collision buffer, it requires no additional sensors, just the TPU layer that takes up only minimal installation space and is mounted with an easy system. Moreover, the lattice design of the skin is easily, rapidly and cost-effectively adaptable to every cobot type, thanks to the advantages of 3D printing. In production halls, cobots are often deployed at different workstations. The RoboSkin eliminates the need for dismantling, re-assembly and re-calibration, thus saving time and cost.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjg2MTI0MTAzOTE3LWZvcndhcmQtYW0tdXNlLWNhc2UtY29ib3RpY3Mtcm9ib3NraW4tMS0xLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"><div id="isPasted"><div>Thanks to Additive Manufacturing and its design freedom, the RoboSkin is easily adaptable to different shapes and functionalities of each cobot. This image shows a RoboSkin for the axes 2 and 3 of the cobot Kuka iiwa created with a lattice structure printed with Ultrasint&reg; TPU01. (Source: OECHSLER).&nbsp;</div></div> </div></div><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjg2MTI0MTE4OTI5LWZvcndhcmQtYW0tdXNlLWNhc2UtY29ib3RpY3Mtcm9ib3NraW4tMi0xLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib">Different axis, different RoboSkin &ndash; this image shows a cover for the axis 4 of the cobot Kuka iiwa (Source: OECHSLER).&nbsp;<blockquote><div data-imgready="true" id="isPasted">&ldquo;The RoboSkin solves a complex problem with a seemingly simple solution, enabling the end user to optimize the productivity of the human-robot-collaboration application. With AM, we can offer a configurable soft skin according to the safety needs at reasonable pricing &ndash; and which is reliable, easy to handle, lightweight, space-saving and permeable to ensure profitable performance.&rdquo;Meike Wischgoll, Program Manager, OECHSLER</div></blockquote><div data-parent="true" data-section="4"><div data-imgready="true"><div data-parent="true" data-section="6"><div data-imgready="true">Together, OECHSLER and Forward AM are enabling a solution that delivers a significant increase in safety and productivity. Harnessing the advantages of AM, human workers and cobots can work together at minimum risk of injury while maximizing productivity.</div></div></div></div>

Humans sharing a workspace and collaborating with robots has become a reality that companies and their smart factories just can’t do without, as it allows flexible manufacturing in variable batch sizes with maximum efficiency. In short, successful human-machine interaction is key for future-proof manufacturing.

Protective Lattice Layer for Cobots

In a warehouse or production facility, packing refers to the process of preparing goods and products for shipment or storage by placing them into appropriate containers or packaging materials. Packing presents many challenges that can significantly impact operational efficiency and overall productivity. One primary concern is the traditional toll it takes on the human-labor force. The labor-intensive nature of packing tasks can lead to workforce fatigue and decreased morale, potentially affecting safety and productivity.This article explores the need and benefits of automated packing solutions to streamline warehouses and production facilities, reduce time to delivery and increase safety. It highlights the features and applications of BRIXX&reg;, a new automated packaging solution with modular components and click-and-play-based software.<h1>Challenges in Packaging</h1>To understand the challenges in packing, it&rsquo;s crucial to understand the stages of packaging and packing along the &lsquo;product to pallet&rsquo; line. A product packaged in its for-consumption form is known as its primary packaging. Secondary packaging is used to group a certain number of products to create a stock-keeping unit, commonly referred to as a SKU. This helps the handling of smaller products and also adds a layer of protection for them during transport. Tertiary, bulk, or transit packaging is used to group larger quantities of SKUs to transport them from point A to point B (e.g. from the production facility to the point of sale). An example of tertiary packaging is a stretch-wrapped pallet containing a number of cardboard boxes (secondary packaging) to enable efficient product shipping.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjgzMTgxOTgyNjU5LTEgZmxleC5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 300px;" class="fr-fic fr-dib">A warehouse with a manual packing process.The challenges in automating packing lie at the secondary and tertiary stages because the conventional method of manual packing is costly and time-consuming due to the need for a large amount of labor. Complex packing requirements such as multiple product types and fragile items increase this labor need. This can then be further increased by seasonal demand.&nbsp;<h1 id="isPasted">BRIXX&reg;: An Innovative Packing Solution</h1>An example of an innovative solution for packing automation is BRIXX&reg;, a solution from <a href="https://www.flexlink.com/en" target="_blank">FlexLink</a>, a Coesia company. BRIXX&reg; is a modular, click-and-play software-based solution that reduces manual operations and provides an easy way to customize the process in co-packing lines. The solution was launched at <a href="https://www.interpack.com/vis/v1/en/exhprofiles/rOVtwM2eQ46OgVnf1sGOVw?oid=55128&lang=2&_query=flexlink" rel="noopener noreferrer" target="_blank">Interpack 2023</a> and can be seen live until 10 May.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjgzMTgyMDM0MTM1LTIzMDMwMl9CUklYWF9wcm9kdWN0aW9saW5lX0xpZ2h0R3JleV9CYWNrZ3JvdW5kLTMwMDB4MjEyMS01ODliZDMxLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib">Mixing of products with BRIXX&reg; modules Image credit: FlexLink.With BRIXX&reg;, companies can automate operations for various products, including packages, cartons, and trays. The flexible system provided by Flexlink is scalable to meet varying production needs while remaining affordable and user-friendly. This is possible through advanced mobile conveyor modules and the use of robots to automate repetitive manual packing and co-packing processes.<h3>Modular approach to packing</h3>The BRIXX&reg; system comprises conveyor and robot modules that work with an intuitive software overlay. The modules are easy to move, connect, and power and can be configured in various ways to suit the packing needs of thier location. They are also equipped with visual indicators for operational status, a built-in vision system, and automatic calibration. The modules use the same power connection, simplifying their setup and maintenance.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjgzMTgyMDc5MjU3LWZsZXgyLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib">The&nbsp;BRIXX&reg; units can be configured in various ways to handle diverse packing tasks.&nbsp;&nbsp;Packing facilities can leverage the modularity and ease of set-up of BRIXX&reg; to become a hyper-agile packing line. A facility may set up one configuration of BRIXX&reg; for one packing task, such as palletizing, and then quickly reconfigure to enable them to complete a different type of task, such as labeling. This modular &lsquo;super power&rsquo; means packing facilities can offer more services to their customers and manage unexpected requests rapidly.The robotic arm module has a moveable, connectable base with a multi-degree robotic arm with a single or multi-pick vacuum gripper. The conveyor belt line is a simple unit with a speed-adjustable conveyor belt that can link to other units to form continuous packing lines.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjgzMTgyMTkyNjY5LUZsZXhMaW5rLTIzMDIyMi0xNS0yMDQ4eDEzNjUtMjNmMTY2My5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 300px;" class="fr-fic fr-dib">The modules click and connect using the same modular system. Image credit: FlexLink.The flexible combination of BRIXX&reg; modules enables various operations with the same hardware and software. Production companies or co-packers can automate packing actions such as pick-and-place, mixing, labeling, re-labeling, palletizing, or de-palletizing for increased productivity and efficiency. Product transformations, such as case forming, tray forming, and carton closing, are optionally available. <h3>BRIXX&reg; Software&nbsp;</h3>The BRIXX&reg; software is designed to be user-friendly and easy to operate. It has drag-and-drop functionality that enables the rapid setup and adjustment of the system. A functioning automated packing line can be set up with the assistance of step-by-step visual instructions. Additionally, the software provides real-time production monitoring through overall equipment effectiveness (OEE) indicators and alarms. Its human-machine interface also allows you to plan for ordinary and extraordinary maintenance.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjgzMTgyMjQ1MTY4LUZsZXhMaW5rLTIzMDIyMi0yOC0yMDQ4eDEzNjUtMjNmMTY2My5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 300px;" class="fr-fic fr-dib">The BRIXX&reg; software enables users to design efficient packing lines, check for maintenance, and monitor processes. Image credit: FlexLink.Hence, the user can rearrange the robotic modules and change instructions and configurations in the code according to the hardware setup. The system supports up to 5 different conveyor layouts.The BRIXX&reg; software also features a built-in SKU management system with a selector guide, allowing the user to manage inventory. It also features MES-ERP integration tools thanks and an optional unified name-space MQTT open interface to support inventory management for packaging and labeling units.<iframe id="644a3752133e690008b02766" width="250" class="specs-iframe" height="420" src="https://wevolver.com/iframe/specs/brixx-packaging-automation-system?iframe=true" frameborder="0" scrolling="true" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> The system also allows up to 4 user levels to help set up various permissions and restrictions on controls. It has real-time monitoring features that include alarms and OEE indicators. Moreover, remote assistance packages and an integrated HMI system are helpful for preventative maintenance and planning.The software features PackML standard support backup and restores features in IPC for additional security. Each unit has a dedicated software license and an additional Android application to enhance functionality for packaging line operators.The BRIXX&reg; solution enables companies to quickly adapt to the increasing demand for automation to increase efficiency and lower costs. The system&rsquo;s unique modularity ensures companies can lower thier risk while being prepared for seasonal and consumer changes.&nbsp;<h3>Applications</h3>The BRIXX&reg; system is suitable for many standard packing applications required by warehouses and other packing facilities. Common applications include adding boxes to pallets, known as palletizing, removing boxes from pallets, adding SKUs to other tertiary packaging, and labeling and relabelling.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjgzMTgyMzM5OTI2LWFwcGxpZmxleC5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 300px;" class="fr-fic fr-dib"><h1 id="isPasted">Conclusion</h1>Automated packing solutions can increase efficiency and reduce costs and material waste by contributing to reduced packaging time and a company&#39;s sustainable footprint. FlexLink&#39;s BRIXX&reg; solution combines robot modules with intuitive software to automate secondary and tertiary packing applications.&nbsp;<h3>Learn more about BRIXX&reg;</h3>Flexlink is launching the BRIXX&reg;&nbsp; solution during <a href="https://www.interpack.com/vis/v1/en/exhprofiles/rOVtwM2eQ46OgVnf1sGOVw?oid=55128&lang=2&_query=flexlink" rel="noopener noreferrer" target="_blank">Interpak 2023</a>. Visit them at their stand in Hall 6/D31.&nbsp;

An automated packing system leveraging modular components and intuitive software to address labor-intensive challenges, optimize operational efficiency, and streamline product handling processes. 

Modular Automated Packing System Offers New Flexibility and Agility

This is the seventh article in a 7-part series featuring articles on&nbsp;<a href="https://www.wevolver.com/article/embracing-the-future-of-manufacturing-with-industry-40/" rel="noopener noreferrer" target="_blank">Transforming Industrial Manufacturing with Industry 4.0</a>. The series looks at technological developments and emerging trends in the manufacturing industry that drive growth and innovation. This series is sponsored by Mouser Electronics. Through their sponsorship, Mouser Electronics shares its passion and support for engineering advancements that enable a smarter, cleaner, safer manufacturing future. &nbsp;Customer needs and expectations are the driving force behind product development and manufacturing. Customers want product options and personalization. Customers want customized products manufactured and delivered quickly, and increasingly, customers expect manufacturers to align with their values.&nbsp;Although the traditional manufacturing goals of efficiency, accuracy, and safety remain relevant, manufacturing environments are trending toward new characteristics, such as being agile, accessible, data-driven, collaborative, resilient, and sustainable. The final article in the Transforming Industrial Manufacturing with Industry 4.0 series examines these characteristics and how they help meet customers&rsquo; rapidly evolving needs and expectations.<h1 dir="ltr">Agility to Meet Customer Needs</h1>Agile systems are rooted in batch production approaches, where the base product is mass-produced, but customization is carried out in batches &mdash;say, producing one batch with red paint, another with blue, and another with pink. Agility relates to market changes and what customers want; it changes the concept of producing one or two variations to instead offering those variations as options, taking manufacturing from customizing products to personalizing them. Whereas customization leads to customer satisfaction, personalization has an aspect of customer delight attached to it.The most advanced systems produce each product as a separate order along the production line, using customer data to drive personalization. Imagine ordering a product during the week of your birthday, for example. The manufacturer might add a birthday note in the box or print &ldquo;Happy Birthday!&rdquo; on the packaging to personalize the product. Or, say you have been researching meal delivery services online: A manufacturer might put a coupon in the box for a popular food delivery service. With batch production processes combined with customer data, manufacturers can do a lot to personalize products and not just satisfy customers but delight them.<h1 dir="ltr">Enhancing Accessiblity with Digital Technologies</h1>In industrial automation, accessibility refers to two different aspects. First, accessibility refers to connecting a distributed workforce through integrated, secure systems. Such systems have been evolving for decades, but only recently have the technologies necessary converged to enable seamless and secure collaboration. In earlier decades, we saw various components and pieces of technology make collaboration possible, but only now do we have what we need to fully integrate distributed workforces, resources, and services across all aspects of a business.Second, accessibility refers to integrating human factors into system design in terms of ease of use for installers, operators, technicians, floor workers, and others. Designing with humans in mind used to be an afterthought or a nicety. Now, companies realize that the installers, operators, and all the rest are the consumers in these cases. Therefore, considering human factors and applying related guidelines are important parts of design success.In both cases, cloud infrastructure, with system integrators such as infrastructure as a service, platform as a service, software as a service, and similar concepts, is the most significant enabler of accessibility. Teams working in real-time with minimum lag time provide considerable extensibility for the types of collaboration possible. Augmented reality (AR) is a good example. Rather than engineers, technicians, manufacturers, and other stakeholders flying in to install, operate, troubleshoot, or repair a mechanical system, AR enables stakeholders to access data analytics, see the system in real-time, and use visual overlays to make repairs or alterations. The efficiencies related to cost, time, and product life cycle are already significant, and we can expect them to increase the number of AR technologies improved over time.<h1 dir="ltr">Data-Driven Approach</h1>In today&rsquo;s industrial automation, data drives many insights. For instance, data can evaluate how a manufacturer is doing in terms of what is most important to the company. Here, value matrices are used to identify the five or six aspects most important in measuring the company&rsquo;s success, such as speed, accuracy, conformance to standards, conformance to regulations, and customer satisfaction. Using real-time data and data trends over time, stakeholders can see how the company performs overall, in terms of its values, and compared with industry averages.Data insights have moved humans from simply responding to manufacturing issues to instead proactively preventing and addressing them. Fluctuations in data can be used to identify when something is about to go wrong and then trigger email messages to responsible technicians, support tickets filed with the help desk, or text messages to supervisors. In some cases, fluctuations can be benign; nonetheless, real-time data and trends can help put humans in a proactive rather than reactive role.Finally, data can be used to evaluate the industrial automation characteristics discussed here. For instance, data can enable greater manufacturing agility by providing insights about when a manufacturer should start offering a sofa in additional colors or different fabrics rather than manufacturing those instances as product variations. Data can also drive process resilience by minimizing downtime for product variations and ensuring that humans are in the right places at the right times.<h1 dir="ltr">Boosting Efficiency through Collaborative Technologies</h1>The nature of collaboration is also evolving with humans collaborating with other humans and robots. The goal of using machines and robotics in industrial environments has historically been to shift heavy, repetitive, and dangerous tasks away from humans to mechanical and automated systems. Collaborative robotics (cobots) expands these use cases, however, to include:Skills that require years of training for humans to become proficient. Welding is one such skill where more than 100 hours of classroom time and three to four years as an apprentice are required. Even then, human welders typically cannot match the quality and consistency of welds that robots can make. By way of example, even highly skilled welders can weld only a 60cm seam in one continuous motion, and starts and stops can affect the overall quality of the weld. In contrast, robots can weld roughly a 121 cm seam in one continuous motion, producing a higher-quality weld. A collaborative approach for welding might have the robot completing steps that require skills and might affect quality. The human would do the tasks that are more intuitive to humans, such as setting up the process and handling exceptions. The idea here is to use the best of both worlds to achieve maximum efficiency.Tasks where robots can do part of the work. Imagine receiving components that are fragile or sensitive to handling or that require a clean room. In these instances, using a cobot to open boxes of various sizes and shapes would pose several design challenges and be less efficient or effective than having humans perform such tasks because the tasks are intuitive rather than calculated. In contrast, a cobot could easily meet the sensitive component handling requirements after the box has been opened and perhaps do so faster and more consistently than humans.<h1 dir="ltr">Finding the Balance between Resilience and System Complexity</h1>Resilience is about enabling systems to adapt quickly when variations in product manufacturing are needed. For example, imagine a system that is designed to produce product A. At the start of the production run, someone sets up the system to manufacture that product. However, what happens when variations of the product are needed &mdash;a different color, size, fabric pattern, module, or packaging?&nbsp;In less resilient systems, someone would need to manually change the setup to accommodate these variations, which means production downtime and higher labor cost. Resilient systems can withstand such unforeseen adversities and recover quickly. Resilient systems aim to account for possible variations that the system might encounter to adapt with as little downtime and human intervention as possible.From a design engineering standpoint, it&rsquo;s easy to get trapped in the idea of developing super-complex systems that can do many things and account for even rare scenarios. The more complex the system, however, the more opportunities for failures. A simpler system that handles 80% of production scenarios might be better than a more complex system that handles 90% of scenarios. Designing for resilience is about finding a balance between simplicity that requires more human time in the loop, and complexity that has more failure points and potentially affects other production areas.<h1 dir="ltr">Conclusion</h1>Companies that are agile, accessible, data-driven, collaborative with robots, and resilient are better positioned to meet the needs of their customers and stay ahead of the competition. As we move into the future, companies must continue to prioritize customer insights and use them to inform their automation strategies.&nbsp;This means understanding not only what customers want today but also anticipating their future needs and preferences. By doing so, companies can create a sustainable competitive advantage that will enable them to thrive in a rapidly evolving marketplace. With the right approach to industrial automation, companies can meet customer demands and create a more connected, efficient, and sustainable manufacturing ecosystem.This article is based on: <a href="https://resources.mouser.com/automation/customers-driving-industrial-automation-innovation" id="isPasted" target="_blank">Customers Driving Industrial Automation Innovation</a>, a blog by Mouser Electronics. It has been substantially edited by the Wevolver team and Electrical Engineer <a href="https://www.wevolver.com/profile/ravi.rao" target="_blank">Ravi Y Rao</a>. It&#39;s the final article from the <a href="https://www.wevolver.com/article/embracing-the-future-of-manufacturing-with-industry-40" target="_blank">Transforming Industrial Manufacturing with Industry 4.0</a> Series.<hr id="isPasted">The&nbsp;<a href="https://www.wevolver.com/article/embracing-the-future-of-manufacturing-with-industry-40/" rel="noopener noreferrer" target="_blank">introductory article</a>&nbsp;presented the different topics covered in the&nbsp;Transforming Industrial Manufacturing with Industry 4.0 Series.The&nbsp;<a href="https://www.wevolver.com/article/sensor-fusion-plcs-and-low-power-components-enable-innovations-in-manufacturing-40/" rel="noopener noreferrer" target="_blank">first article</a>&nbsp;discusses&nbsp;Sensor Fusion, PLCs, Low-Power Components, and Vision Systems and their impact on the progression of Manufacturing 4.0.The&nbsp;<a href="https://www.wevolver.com/article/the-impact-of-industry-40-on-industrial-engineering-branches" rel="noopener noreferrer" target="_blank">second article</a>&nbsp;examines the expanding and evolving roles of&nbsp;systems, process, and design engineers within the design chain of bringing new industrial automation products to fruition.The&nbsp;<a href="https://www.wevolver.com/article/building-smart-factories-with-industrial-iot" rel="noopener noreferrer" target="_blank">third article</a>&nbsp;takes a look at the&nbsp;development of smart factories, their characteristics, benefits, and challenges&nbsp;that need to be addressed for a successful digital transformation.The&nbsp;<a href="https://www.wevolver.com/article/overcoming-challenges-in-industrial-robotics/" rel="noopener noreferrer" target="_blank">fourth article</a>&nbsp;focuses on technologies like&nbsp;Robot Operating Systems, edge computing, and new software solutions that are improving robotics in industrial and commercial environments.The&nbsp;<a href="https://www.wevolver.com/article/ai-driven-ar-in-manufacturing-from-data-to-actionable-insights/" rel="noopener noreferrer" target="_blank">fifth article</a>&nbsp;explores some challenges in&nbsp;accessing information in the manufacturing sector and how AI-driven AR has the potential to overcome them.The&nbsp;<a href="https://www.wevolver.com/article/digital-twins-bridge-gap-between-product-design-and-manufacturing/" rel="noopener noreferrer" target="_blank">sixth article</a>&nbsp;explains how digital twins are helping bridge the gap between design and manufacturing.The&nbsp;<a href="https://www.wevolver.com/article/customers-driving-innovation-in-industrial-automation/" rel="noopener noreferrer" target="_blank">seventh article</a>&nbsp;how&nbsp;manufacturing environments are adapting to the evolving customer needs and expectations.<hr><h1 dir="ltr">About the sponsor: Mouser Electronics</h1>Mouser Electronics is a worldwide leading authorized distributor of semiconductors and electronic components for over 1,200 manufacturer brands. They specialize in the rapid introduction of new products and technologies for design engineers and buyers. Their extensive product offering includes semiconductors, interconnects, passives, and electromechanical components.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjgzMTM2NjA0ODUxLTE2ODMxMzY2MDQ4NTEucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" width="720" height="91" class="fr-fic fr-dii">

Article #7 of Transforming Industrial Manufacturing with Industry 4.0 Series: Customer needs are driving innovation in industrial automation, with manufacturing environments trending towards new characteristics such as being agile, accessible, data-driven, collaborative, and resilient.


Customers Driving Innovation in Industrial Automation

Robotic joints, which are sometimes known as axes, are the moveable parts of a robot that cause relative motion between adjacent links. These links refer to the rigid components that connect the joints to ensure their proper and straightforward operation. 

Robot Joints: An In-Depth Guide to Anatomy, Physics and Challenges in Design

University of Michigan-Fri Jun 30 2023 23:59:59 GMT+0200 (Central European Summer Time)

University of Michigan-Mon Jul 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

University of Michigan-Thu Aug 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

University of Michigan-Thu Aug 31 2023 23:59:59 GMT+0200 (Central European Summer Time)

University of Michigan-Sat Sep 30 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

Unitree Robotics

READY Robotics-Fri Jun 30 2023 23:59:59 GMT+0200 (Central European Summer Time)

READY Robotics-Mon Jul 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

READY Robotics-Thu Aug 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

READY Robotics-Thu Aug 31 2023 23:59:59 GMT+0200 (Central European Summer Time)

READY Robotics-Sat Sep 30 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

READY Robotics

DEEP Robotics

THINC Lab-Fri Jun 30 2023 23:59:59 GMT+0200 (Central European Summer Time)

THINC Lab-Mon Jul 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

THINC Lab-Thu Aug 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

THINC Lab-Thu Aug 31 2023 23:59:59 GMT+0200 (Central European Summer Time)

THINC Lab-Sat Sep 30 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

Rozum Robotics-Fri Jun 30 2023 23:59:59 GMT+0200 (Central European Summer Time)

Rozum Robotics-Mon Jul 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

Rozum Robotics-Thu Aug 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

Rozum Robotics-Thu Aug 31 2023 23:59:59 GMT+0200 (Central European Summer Time)

Rozum Robotics-Sat Sep 30 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

Rozum Robotics

Adapta Robotics-Fri Jun 30 2023 23:59:59 GMT+0200 (Central European Summer Time)

Adapta Robotics-Mon Jul 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

Adapta Robotics-Thu Aug 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

Adapta Robotics-Thu Aug 31 2023 23:59:59 GMT+0200 (Central European Summer Time)

Adapta Robotics-Sat Sep 30 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

Accerion-Fri Jun 30 2023 23:59:59 GMT+0200 (Central European Summer Time)

Accerion-Mon Jul 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

Accerion-Thu Aug 31 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

Accerion-Thu Aug 31 2023 23:59:59 GMT+0200 (Central European Summer Time)

Accerion-Sat Sep 30 2023 23:59:59 GMT+0300 (Eastern European Summer Time)

collaborative robots

collaborative robots

Profiles