Robotics

6 River Systems
The fulfillment economy has exploded during the pandemic, as has competition among automation technology providers, whose robotic technology is becoming critical during widespread labor shortages and ballooning demand.That’s the good news. The bad news, if you’re a robotics firm with a great product and opportunity as far as the horizon is that scaling hardware distribution, whether via direct sales or as-a-service, is extremely complex, typically takes massive capital outlays, and is fraught with the perils of miscalculation. What’s an emerging robotics firm to do?One model that’s becoming increasingly important for savvy businesses is to partner with an existing brand with a broad reach and pre-existing infrastructure. Examples include Kinova teaming up with Northrop Grumman to help distribute a small manipulator to existing customers and Robotiq partnering with Universal Robots on off-the-shelf robotic tooling.In the latest example, 6 River Systems, LLC, a leading fulfillment solutions provider, just announced a new initiative to support warehouse efficiencies by teaming up with Ricoh USA. Under the arrangement, RICOH’s service solutions business unit will augment 6 River Systems’ existing service team for its collaborative robots – called “Chucks,” solving for a crucial weakness in any young enterprise technology company’s bid to scale: giving customers an ample support network.”The demand for our automated retail solution is significant, especially with retailers continually looking for ways to get their products into consumers’ hands faster via seamless experiences,” says Eran Frenkel, Vice President of Technical Operations, 6 River Systems. “By partnering with Ricoh, we’re able to focus on making our solutions more widely available, which ultimately helps our customers quickly and efficiently meet their fulfillment goals.”Like other fulfillment automation providers, 6RS is on a bit of a tear during the pandemic. The company has provided solutions for major fulfillers and brands like Crocs, which implemented 6RS’ wall-to-wall fulfillment solution, including its collaborative mobile robot Chuck. As I wrote last year, Crocs has seen a 182% pick rate improvement with the 6RS system, illustrating a key reason fulfillers are turning to automation in such numbers. This increase in throughput was especially critical during the holiday peak season.In general, robots have become essential to scaling, and the solutions can now be brought online with unprecedented speed and minimal downtime. Not surprisingly as according to Statista, the global warehouse automation market is predicted to increase from $15 billion in 2019 to $30 billion by 2026.

But the warehouse automation sector, while maturing rapidly in the Amazon Prime era, is still nascent, with many of the players less than a decade old. That’s a short time to build a massive global or even national distribution and support infrastructure. Collaborating seems like a key to efficiently do just that.”Our collaboration with 6 River Systems is a prime example of how our stable and trusted infrastructure – coupled with a team of more than 10,000 service delivery professionals supporting and maintaining more than one million devices across the U.S. – helps solve our customers’ problems,” says Jim Kirby, Vice President, Service Advantage, Ricoh USA, Inc. “Together, we are addressing some of the biggest challenges and opportunities in retail today including supply chain operational efficiency such as retail and warehouse automation. By expertly assisting with service and support for companies like 6 River Systems, we are helping them maintain focus on what matters most – innovation that solves supply chain hurdles and moves business forward.”It’s a great example of how smart robotics firms are taking advantage of the growth opportunities of 2022 and beyond through effective collaborations designed to scale at speed. More

Pixabay

Among the deluge of robotics predictions you’re bound to encounter this year, there’s one you should pay particular attention to: The way robots “see” is fundamentally changing, and that’s going to have a huge impact on the utility cost and proliferation of robotic systems.Of course, it’s a bit of a mischaracterization to talk about robots “seeing,” or at least a reductive shorthand for a complex interplay of software and hardware that’s allowing robots to do much more sophisticated sensing with much less costly equipment. Machine vision incorporates a variety of technologies and increasingly relies on software in the form of machine learning and AI to interpret and process data from 2D sensors that would have been unachievable even a short time ago.With this increasing reliance on software comes an interesting shift away from highly specialized sensors like LiDAR, long a staple for robots operating in semi-structured and unstructured environments. Robotics experts marrying the relationship between humans and AI software are coming to find that LiDAR isn’t actually necessary. Rather, machine vision is providing higher quality mappingat a more affordable cost, especially when it comes to indoor robotics and automation.See also: 2022: A major revolution in robotics.To learn more about the transformation underway, I connected with Rand Voorhies, CTO & co-founder at inVia Robotics, about machine vision, the future of automation, and whether LiDAR is still going to be a foundational sensor for robots in the years ahead.GN: Where have the advances come in machine vision, the sensors or the software?Rand Voorhies: While 2D imaging sensors have indeed seen constant continuous improvement, their resolution/noise/quality has rarely been a limiting factor to the widespread adoption of machine vision. While there have been several interesting sensor improvements in the past decade (such as polarization sensor arrays and plenoptic/light-field cameras), none have really gained traction, as the main strengths of machine vision sensors are their cost and ubiquity. The most groundbreaking advancement has really been along the software front through the advent of deep learning. Modern deep learning machine vision models seem like magic compared to the technology from ten years ago. Any teenager with a GPU can now download and run object recognition libraries that would have blown the top research labs out of the water ten years ago. The fact of the matter is that 2D imaging sensors capture significantly more data than a typical LiDAR sensor – you just have to know how to use it.

While cutting-edge machine vision has been improving in leaps and bounds, other factors have also contributed to the adoption of even simpler machine vision techniques. The continual evolution of battery and motor technology has driven component costs down to the point where robotic systems can be produced that provide a very strong ROI to the end-user. Given a good ROI, customers (in our case, warehouse operators) are happy to annotate their environment with “fiducial” stickers. These stickers are almost like a cheat-code to robotics, as very inexpensive machine vision solutions can detect the position and orientation of a fiducial sticker with ultra-precision. By sticking these fiducials all over a warehouse, robots can easily build a map that allows them to localize themselves.GN: Can you give a little context on LiDAR adoption? Why has it become such a standardized sensing tool in autonomous mobility applications? What were the early hurdles to machine vision that led developers to LiDAR?Rand Voorhies: Machine vision has been used to guide robots since before LiDAR existed. LiDAR started gaining significant popularity in the early 2000s due to some groundbreaking academic research from Sebastian Thrun, Daphne Koller, Michael Montemerlo, Ben Wegbreit, and others that made processing data from these sensors feasible. That research and experience led to the dominance of the LiDAR-based Stanley autonomous vehicle in the DARPA Grand Challenge (led by Thrun), as well as to the founding of Velodyne (by David Hall, another Grand Challenge participant), which produces what many now consider to be the de-facto autonomous car sensor. The Challenge showed that LiDAR was finally a viable technology for fast-moving robots to navigate through unknown, cluttered environments at high speeds. Since then, there has been a huge increase in academic interest in improving algorithms for processing LiDAR sensor data, and there have been hundreds of papers published and PhDs minted on the topic. As a result, graduates have been pouring into the commercial space with heaps of academic LiDAR experience under their belt, ready to put theory to practice.In many cases, LiDAR has proven to be very much the right tool for the job. A dense 3D point cloud has long been the dream of roboticists and can make obstacle avoidance and pathfinding significantly easier, particularly in unknown dynamic environments. However, in some contexts, LiDAR is simply not the right tool for the job and can add unneeded complexity and expense to an otherwise simple solution. Determining when LiDAR is right and when it’s not is key to building robotic solutions that don’t just work — they also provide positive ROI to the customer.At the same time, machine vision has advanced as well. One of the early hurdles in machine vision can be understood with a simple question: “Am I looking at a large object that’s far away or a tiny object that’s up-close”? With traditional 2D vision, there was simply no way to differentiate. Even our brains can be fooled, as seen in funhouse perspective illusions. Modern approaches to machine vision use a wide range of approaches to overcome this, including:Estimating the distance of an object by understanding the larger context of the scene, e.g., I know my camera is 2m off the ground, and I understand that car’s tires are 1000 pixels along the street, so it must be 25m away.Building a 3D understanding of the scene by using two or more overlapping cameras (i.e., stereo vision).Building a 3D understanding of the scene by “feeling” how the camera has moved, e.g., with an IMU (inertial measurement unit – sort of like a robot’s inner ear) and correlating those movements with the changing images from the camera.Our own brains use all three of these techniques in concert to give us a rich understanding of the world around us that goes beyond simply building a 3D model.GN: Why is there a better technological case for machine vision over LiDAR for many robotics applications?Rand Voorhies: LiDAR is well suited for outdoor applications where there are a lot of unknowns and inconsistencies in terrain. That’s why it’s the best technology for self-driving cars. In indoor environments, machine vision makes the better technological case. As light photons are bouncing off objects within a warehouse, robots can easily get confused under the direction of LiDAR. They have a difficult time differentiating, for example, a box of inventory from a rack of inventory — both are just objects to them. When the robots are deep in the aisles of large warehouses, they often get lost because they can’t differentiate their landmarks. Then they have to be re-mapped.By using machine vision combined with fiducial markers, our inVia Picker robots know exactly where they are at any point in time. They can “see” and differentiate their landmarks. Nearly all LiDAR-based warehouse/industrial robots require some fiducial markers to operate. Machine vision-based robots require more markers. The latter requires additional time and cost to deploy long rolls of stickers vs fewer individual stickers, but when you factor in the time and cost to perform regular LiDAR mapping, the balance swings far in the favor of pure vision. At the end of the day, 2D machine vision in warehouse settings is cheaper, easier, and more reliable than LiDAR.If your use of robots does not require very high precision and reliability, then LiDAR may be sufficient. However, for systems that cannot afford any loss in accuracy or uptime, machine vision systems can really show their strengths. Fiducial-based machine vision systems allow operators to put markers exactly where precision is required. With inVia’s system that is picking and placing totes off of racking, placing those markers on the totes and the racking provides millimeter level accuracy to ensure that every tote is placed exactly where it’s supposed to go without fail. Trying to achieve this with a pure LiDAR system would be cost and time prohibitive for commercial use.GN: Why is there a better business case?Rand Voorhies: On the business side, the case is simple as well. Machine vision saves money and time. While LiDAR technology has decreased in cost over the years, it’s still expensive. We’re committed to finding the most cost-effective technologies and components for our robots in order to make automation accessible to businesses of any size. At inVia we’re driven by an ethos of making complex technology simple. The difference in the time it takes to fulfill orders with machine vision versus with LiDAR and all of its re-mapping requirements is critical. It can mean the difference in getting an order to a customer on time or a day late. Every robot that gets lost due to LiDAR re-mapping reduces that system’s ROI. The hardware itself is also cheaper when using machine vision. Cameras are cheaper than LiDAR, and most LiDAR systems need cameras with fiducials anyway. With machine vision, there’s an additional one-time labor cost to apply fiducials. However, applying fiducials one time to totes/racking is extremely cheap labour-wise and results in a more robust system with less downtime and errors. GN: How will machine vision change the landscape with regards to robotics adoption in sectors such as logistics and fulfillment?Rand Voorhies: Machine vision is already making an impact in logistics and fulfillment centers by automating rote tasks to increase the productivity of labor. Warehouses that use robots to fulfill orders can supplement a scarce workforce and let their people manage the higher-order tasks that involve decision-making and problem-solving. Machine vision enables fleets of mobile robots to navigate the warehouse, performing key tasks like picking, replenishing, inventory moves, and inventory management. They do this without disruption and with machine-precision accuracy. Using robotics systems driven by machine vision is also removing barriers to adoption because of their affordability. Small and medium-sized businesses that used to be priced out of the market for traditional automation are able to reap the same benefits of automating repetitive tasks and, therefore, grow their businesses.GN: How should warehouses go about surveying the landscape of robotics technologies as they look to adopt new systems?Rand Voorhies: There are a lot of robotic solutions on the market now, and each of them uses very advanced technology to solve a specific problem warehouse operators are facing. So, the most important step is to identify your biggest challenge and find the solution that solves it. For example, at inVia we have created a solution that specifically tackles a problem that is unique to e-commerce fulfillment. Fulfilling e-commerce orders requires random access to a high number of different SKUs in individual counts. That’s very different from retail fulfillment, where you’re retrieving bulk quantities of SKUs and shipping them out in cases and/ or pallets. The two operations require very different storage and retrieval setups and plans. We’ve created proprietary algorithms that specifically create faster paths and processes to retrieve randomly accessed SKUs.E-commerce is also much more labor-dependent and time-consuming, and, therefore, costly. So, those warehouses want to adopt robotics technologies that can help them reduce the cost of their labor, as well as the time it takes to get orders out the door to customers. They have SLAs (service level agreements) that dictate when orders need to be picked, packed, and shipped. They need to ask vendors how their technology can help them eliminate blocks to meet those SLAs. More

Starship Robotics
Look, it was a weird year. We were supposed to be emerging from a socio-political cataclysm, supposed to be getting back on track, but in a lot of ways, the drudgery just kept on keeping on. This is why it makes a lot of sense that comfort food ranked high on the list of items folks ordered from shops and restaurants that were then delivered by an emergent class of autonomous delivery robots.

Innovation

If you live in a city or dense suburb and don’t have delivery robots in your area yet, brace yourself: They’re coming. Delivery bots are designed to reduce car traffic and increase efficiency for last-mile urban delivery. They’re also pretty amazing data collection devices, which advocates say will help streamline operations and reduce waste but will also lead to profound privacy worries in the near future. One of the leading providers in the field, Starship Technologies, recently released its 2021 Robot Wrap Up, “highlighting the most popular and quirky requests and orders” that its fleet of more than 1,000 robots worldwide have received in the past year.And yeah … comfort food. In the U.S., that meant things like boneless chicken wings, which ranked most popular in the western states, and curly fries, which topped orders in the midwest. Chicken fingers were popular in the east and the south. Interestingly, pizza didn’t make the cut on Starship’s most-ordered list, which almost certainly says more about the distribution of the technology than market trends. In fact, pizza is having its own automation makeover, and owing to the fact that pizza preparation and handling is distinct from that of many other fast foods, which are fried, autonomous pizza making and delivering technology seems endemic to the sector rather generalized (see: 2022 will be the year of the pizza-making robot).When you look internationally, the picture starts to change (and the U.S., perhaps not surprisingly, doesn’t come out looking very healthy). Among British consumers, the most popular items delivered by Starship’s fleet were breakfast and included bread, eggs, and bananas. Bananas!One of the primary markets for Starship’s robots has been college campuses. That’s because local regulations are still a patchwork of inconsistent or non-existent guidelines governing the use of robots on public streets. Colleges, however, are contained ecosystems often with their own governing authorities. It was, of course, a tough year for college kids, who once again saw much of campus life cancelled among quarantine orders. Perhaps that’s why any individual’s record for the most orders goes to an unidentified individual at Arizona State University, who placed 230 orders with Starship during 2021. Go Sun Devils…

Oregon State students claim the dubious record of having the most late-night orders. (Study sessions, maybe?) And parents of Northern Arizona University students will be proud to know that their students placed the most early morning orders.What does all this data tell us about robot delivery now and in the future? Not much, honestly. Though Starship has the most widely distributed delivery fleet, the footprint is still fairly small. But it is growing, and the volume is now becoming hard to ignore. Starship robots travelled, in aggregate, more than three million miles making deliveries in 2021, which the company proudly boasts is 13 trips to the Moon. That accounts for 100,000 road crossings every day and, over the lifetime of the company, which was founded in 2014, more than two million commercial deliveries globally.Now that 2022 is upon us, with a fresh wave of news about a new variant and unseen dimensions of unrest and chaos, it’s a safe bet we’ll see another important growth milestone for autonomous delivery. Comfort food anyone? More

Drone delivery is still in the starting gate, but with early testbeds showing positive results there’s good reason to suspect regulators will become more permissive in the mid term. But should delivery include controlled substances like pharmaceuticals?It’s not an idle question. Amazon and CVS have teased drone delivery for medications, though it doesn’t strain the imagination to spot glaring problems. Drone regulations will only allow drones to fly in particular areas, excluding certain populations based on geography and thus hobbling one of the primary arguments for delivering drugs via drone — namely that drones can help solve for pharmacy deserts. What’s more, packages delivered by drone might be tampered with or stolen, drones can be shot down, and identity authentication will be tricky.ALSO READ: Watch these autonomous drones zip through the woodsUnderlying this push is the fact that the pharma industry needs tech innovation, yet there are very few who have been able to disrupt this giant industry. I connected with Susan Lang, Founder & CEO of XIL Health, a complex drug pricing analytics company, about the prospects of delivering medicine via drones.GN: Who has trialed prescription delivery by drone, and what have been the results?Susan Lang: So far publicly companies have begun pilots. CVS and UPS started in May 2020 and are using Matternet’s M2 drones with authorization from the Federal Aviation Association to deliver prescription medication to residents in The Villages community in Florida. In Ireland, the healthcare system and Irish aviation systems have allowed Manna Aero to deliver medications via drone to the elderly in Moneygall, a small Irish village. In Uganda, Johnson and Johnson are piloting a program in the Lake Victoria Kalangala District. Access to the islands is difficult, making it hard to get needed medications. The drones could offer quicker and safer transport, being more effective than even boats. 

Walgreens partnered with Wing, a subsidiary of Alphabet, people will be able to have over-the-counter medicines and household items delivered to their backyards. There are so many different pilot programs going on, these are just a few of the public trials we know about. GN: Why is the Pharma industry in need of tech innovation?Susan Lang: When there’s a retail infrastructure like in the United States and Ireland, it’s the retail store that’s in charge. In the case of Uganda, Johnson and Johnson as a pharmaceutical company is directly involved in the pilot program because it’s direct access from them. Innovation is needed for the ease of access for consumers, it could also help avoid delays from weather or other issues. Like disaster recovery, drone technology could help reach people in an emergency situation we might otherwise not have access to. Drone deliveries also started during COVID, as more and more companies are trying to do touchless deliveries. In the US drones could be safer and quicker to use when compared to trucks with drivers, especially with the supply chain issues that have come up. Drones can also be more sustainable in the long term, reducing the need for other forms of transportation. GN: What are the biggest challenges ahead and where might drone delivery pilots excel while others miss the mark? Susan Lang: Most likely companies experimenting with drone deliveries will exclude controlled substances and avoid any class two drugs because of the sensitivities involved. One of the biggest challenges is that drone delivery won’t work for every type of product, so they need to test to see when it works. For the pilot programs, going to central zip codes, not residential, they’ll have to answer how to scale and deliver to individual homes in the future. What will it look like to have multiple drones going in and out of neighborhoods? They’ll have to take into consideration how consumers will react to drones in their neighborhoods. Pilot programs are still figuring it out, we just don’t have the answers yet. Healthcare companies will either run the pilot programs themselves or partner with a third-party program. Part of the issues they face is having the volume to scale the program, and since it’s such a new technology, they’ll need big anchor clients like CVS and Walgreens to come on board. They’ll have to work with the FAA to see if delivery affects any animals, people, will need to see how high they can fly the drones, where is the drone highway, etc. Drones themselves are a robust technology, but in healthcare, it’s still very new and there’s a lot of questions. GN: For what environments is drone delivery best suited? Susan Lang: One of my earlier examples, the pilot program in Uganda where it was difficult to reach and deliver, shows how drone delivery might be better suited for more rural and suburban markets right now. With urban markets, there are more risks. There is a difference in geography, of where this is going to be valuable in terms of getting packages to consumers quicker. There are only a couple of pilot programs in the pharmaceutical space, they’re all new, most of them are less than a year old. It’s still very new, we don’t have all the results yet. In the U.S there are two models that are emerging right now, models that are delivering to your home and then models that are delivering to a central location then driven last-mile to your home. Outside of the U.S., drones are also being used instead of boats and other transportation in areas that are difficult to deliver to. The other concern is battery life, limiting how far they can travel. Now, over time, the battery technology will improve but for right now it’s limiting the delivery reach. GN: Why will some pilots possibly not lead to adoption while others succeed? Susan Lang: What matters in adoption of technology is finding clients that are early adopters — that’s not dissimilar to any emerging technology. You’re looking for folks that want a solution and are willing to look at non-traditional answers. Looking for key clients early on that can test, which is what they’re doing with Walgreens and CVS, helps ensure more success early in the program. Otherwise, it will be a slow painful adoption process. Pilot programs are a chance to figure out all the ways the program can fail and fix them early on. Critical thinkers are trying to find the faults now to improve the technology sooner, giving them more potential for success. Drones are not necessarily inadequate, rather delivery services might need a multi-pronged approach. They need to have other things in place to ensure patients and consumers get timely access, drones are not the only approach. The issues that could arise are still unknown with drone technology. The FAA is still developing its own drone highway to ensure it doesn’t interfere with other flying devices. There are still a lot of questions on if they can be hacked and diverted.  More

Seoul Robotics
A 3D perception company specializing in novel solutions for robotics is reimagining autonomy. The trick? Take the sensing burden off individual units and place it in the surrounding infrastructure.Infrastructure to vehicle communication isn’t a new concept, though it’s development and deployment have been hamstrung from widespread adoption on public roads by the difficulties of coordinating the technology rollout and the underlying costs of such a scheme. Seoul Robotics is rolling out a practical testbed specifically targeting enterprise logistics. The company’s Level 5 Control Tower guides vehicles autonomously through a proprietary mesh network of computers without having to place any sensors on an individual vehicle. It could be the quickest route to Level 5 autonomy and a foundation for future autonomous public transit.”Level 5 mobility has been proven to be more challenging to achieve than expected – until now. Level 5 Control Tower has massive potential to fuel autonomous mobility, and we are thrilled to continue expanding upon the implementation of this technology with BMW and other partners,” says HanBin Lee, CEO of Seoul Robotics. “Ultimately, these systems will be deployed in additional public and business settings, powering aspects of our everyday lives, such as autonomously navigated parking and public transit. With the Level 5 Control Tower, this future is closer and more accessible than ever.” The barriers to L5 autonomy are substantial: It’s cost-prohibitive, has questionable safety, and lacks intelligence because vehicles currently cannot fully perceive and anticipate obstacles, nor can they communicate with one another. Seoul Robotics hopes to solve this challenge by creating a system of software, sensors, and processors that take in the environment, communicating with other sensors and the 4/5G systems that come standard on vehicles today to navigate them without requiring a human. The concept, autonomy through infrastructure, is made possible in Seoul Robotics’ new rollout by the Level 5 Control Tower, the brain of the system. This system makes the last-mile logistics process safer and more efficient because it can better capture the full environment and move hundreds of vehicles simultaneously, reducing costs and mitigating accidents. And beyond contained business settings, which is the first deployment, the vision is that these systems could be deployed in everyday applications, from autonomously navigated parking to public transit and beyond.The announcement of this new technology comes at the same time Seoul Robotics is entering a collaboration with BMW to automate fleet logistics at their manufacturing facility. The deployment uses hundreds of connected LiDAR sensors and leverages the Level 5 Control Tower system so that vehicles are autonomously guided from the factory floor to a parking facility, where they are housed before moving to dealerships. 

This is a good reminder that full autonomy will creep into the market, making inroads at the edges in easily automated use cases rather than bursting onto the scene in full public view.Seoul Robotics plans to showcase the Level 5 Control Tower at CES, provided the show moves ahead as scheduled and isn’t canceled due to heightened concerns about COVID-19.  More

Labrador Systems
A new personal robot takes a page from the massive proliferation of enterprise materials handling robots over the past few years. The Retriever from developer Labrador Systems is like a sleek version of the autonomous mobile robots (AMRs) that are now commonplace in logistics centers and manufacturing.After several years of, frankly, ridiculous personal robotic humanoids and mobile robot assistants that amount to very expensive Alexas on wheels, this kind of practical consumer unit is a welcome evolution of existing successful commercial platforms. To put a finer point on it, here’s a robot that some users might actually have a use for.”There’s a significant portion of our society that’s massively underserved,” says Labrador Systems CEO Mike Dooley. “When pain or other health issues start interfering with your ability to move yourself or other things, even short distances can have a major impact on your independence, quality of life and overall health. The Retriever is meant to help physically bridge some of that gap and empower individuals to be more active and do more on their own.”The system works via touch screen, voice, or through a mobile app. Like a personal assistant you can set the robot to to respond to certain programmed reminders, which it does by delivering prescribed objects at the right time. The system is self-driving and guides itself through homes using a proprietary navigation system that fuses algorithms from Augmented Reality with robotics to create 3D maps of the home.Robotics technology in general has plummeted in cost, in large part thanks to the leaps and bounds in machine vision and AI, which enable robots to operate at high levels using essentially consumer grade electronics and sensors. The company is also working with care providers such as senior living communities, occupational therapists and home health providers to explore ways the Retriever can support their mission.  The Company, which is backed by SOSV/HAX, Amazon Alexa Fund, iRobot and the National Science Foundation, has had it robots deployed and operating autonomously in pilot users’ homes since February 2021. “This is the first time we’ve seen this class of robot developed for the home; until now this level of functionality has been confined to warehouses and other commercial environments,” says Paul Willard, Partner at Grep VC. “We’re impressed with how the team is enabling robotics and navigation systems to run on low-cost consumer grade electronics to provide more independence for millions of individuals.”

Labrador recently announced that it has raised an additional $3.1M in Seed Funding. Amazon’s Alexa Fund and iRobot Ventures co-led the round, with SOSV returning and new investors, including Grep VC, joining in. More

BrainCorp
With crippling staff shortages across numerous industries, the role of robots and automation in our workplaces is becoming increasingly important. But are they taking jobs away from humans or filling essential labour gaps and keeping industry safely on the rails?A recent study by IBM showed that AI-driven intelligent automation in the retail sector alone will leap from 40 percent usage to more than 80 percent in the next three years. Experts have staked out a variety of positions on the intersection of adoption, employment, and job security. For the moment, aided by a tight labor market and automation trends coming out of the pandemic, the pendulum seems to have swung toward automation’s role as a driver of overall economic growth. But will that trend last?I recently virtually sat down with Michel Spruijt, Senior Vice President of International Business at Brain Corp, a robotics automation company that helps power the largest fleet of autonomous mobile cleaning robots in the world. It has seen 400% year on year growth in the use of robots in Europe alone. Michel, is an industry insider and works for an automation firm, so it makes sense that he’s bullish on automation for the foreseeable future. However he also has some remarkably keen insights on the robot/human worker dynamic and speaks regularly with leaders from across retail, logistics, transport, education, and healthcare about how they view the ideal balance between automation/robotics and human teams.GN: How have you seen perception of automation solutions change over the pandemic among the general public?Michel Spruijt: Among the general public, robots have always been a sign of innovation and “coolness” when seen in public. What has changed is that now people also recognize robots as necessary and useful – contributing real value to certain operations such as cleaning floors. This puts companies in a great position to leverage robots as they can capitalize on the added productivity and brand value. A common misconception that is lessening amongst the general public is the idea that robots take jobs away from humans. In today’s business landscape where companies face high levels of job shortages and overburdened teams are asked to get more done with less resources, robots can lend a helping hand to immediately fill in gaps. The negative effects of staff shortages are being felt by all of us and robots are recognized as an innovative solution. 

GN: How about among industry — what kind of adoption patterns are we seeing in retail, logistics, transport, education, and healthcare? What accounts for that?Michel Spruijt: The pandemic has taken automation solutions, and in particular robotics, from nice to haves to must haves. This has resulted in an increase in the deployment and usage of robots. While retail has been a key adopter of BrainOS-powered AMRs, it is not alone in its increased usage over the last year. In fact, we’ve seen usage surge in other verticals like airports, malls, offices, industrial environments, education facilities and hospitals.Increased coverage in square feet – October 1st, 2020, to October 1st, 2021:Retail +40%Airport +69%Mall +113%Offices +138%Industrial +313%Education +426%Hospital +2,500%While we understand robot usage has increased dramatically during the pandemic, we project this overall trend to continue to rise because of the value robots are adding to businesses – driving efficiency, improving safety and bringing cost-savings. We’re excited to see what the future holds.GN: This feels like a moment of transition: Automation is spreading in the industries above but we’re a long way from being fully automated. Where are the growing pains likely to crop up?Michel Spruijt: In many of the industries in which robots are being deployed, high turnover is very common. What this means is that businesses must quickly onboard new employees to continue operations. When onboarding, employees are forced to learn new processes, rules, technologies and more. Several different vendors are rolling out AMR solutions for companies. This gives businesses valuable options, but also creates problems: It’s difficult to be good at building both hardware and software that can operate autonomously, thereby reducing product quality. It introduces far greater operating complexity, including separate management systems, user interfaces, safety standards, data aggregation, and so on. In this siloed environment, companies and their staff would be forced to go through the pains of learning multiple systems.We have chosen a platform-based approach which leverages the same central, cloud-based AI software platform, but works with a diverse set of best-in-class OEMs (original equipment manufacturers): OEMs have years, if not decades, of experience in building very specialized machines to accomplish specific tasks. In our opinion, this approach leads to easier fleet management, better data capture and reporting, and lessens the learning process for current and new employees.This is why we believe developing a unifying platform across robotic solutions is a critical step for removing growing pains and helping companies plan a strategic, long term automation strategy. GN: What can industry do to conscientiously shepherd the transition while doing right by workers?Michel Spruijt: Deploying automation and doing right by workers are not two separate actions. In the majority of cases, deploying automation supports your workforce. Robots are a tool workers can use to get their job done more efficiently and effectively, taking monotonous repetitive tasks that can become overbearing or can be unsafe, off their plates to be more effective at the other valuable parts of their job. GN: What can workers do to prepare for and adapt to this transition?Michel Spruijt: In our view, robotics should be developed with humans in mind, so that using this helpful technology can be accessible to all. We have made the BrainOS user interface incredibly intuitive so that employees of all technical backgrounds can successfully utilize and benefit from the added help robots provide, allowing them to focus on other tasks that only humans are uniquely qualified to do. GN: What will surprise people about automation over the next five years?Michel Spruijt: I think what will surprise people is the amount of value robots can bring to organizations through the data they collect. What we have seen so far from robots is the ability to complete one specific task. Going forward though, robots will be able to complete a multitude of tasks, perhaps the most valuable being the collection of data. For example, what is a cleaning robot today, can become a machine that cleans and collects inventory data, tomorrow. This inventory data can, for example, help retailers understand their stock levels, pricing inaccuracies, and planogram compliance issues, potentially saving retailers a huge amount of money while also helping deliver a better shopping experience to customers.  This is what we are working on now and already have deployments and pilots starting. Over the next 5 years, new streams of sensory data will be collected, further transitioning robots from operationally focused machines, to true mobile IoT platforms.  More

ForwardX
A Beijing-based robotics firm specializing in warehouse and logistics automation recently upped its overall funding to $100 million. ForwardX Robotics, which makes autonomous mobile robots for materials handling, recently announced the completion of its Series C. The funding is part of a broader narrative playing out in China, where the domestic robotics sector has soared thanks to an onshoring push by the government and heavy investment in the country’s tech sector. Since 2016 the country has nearly tripled its output of robots by unit. Meanwhile, Chinese robotics developers have seen more than 40% year-on-year revenue growth.In general, the robotics market is hot right now thanks to heavy demand and labor disruptions partly brought on by COVID-19; however, the growth of the Chinese robotics sector marks a major shift over the past five years globally. China has long been a net importer of foreign industrial robots to support its manufacturing infrastructure, but the Made in China 2025 plan has made domestic automation development a top priority. The trend isn’t exactly new. Back in 2018, Jeremie Capron, Director of Research at ROBO Global, a benchmark index series tracking robotics and AI companies, told us about the brisk pace of growth in Chinese automation: “China is home to the largest and fastest-growing robotics market on earth. Chinese government contracts, such as the Made in China 2025 plan, are fueling R&D into AI technologies and its investments are now rivaling Silicon Valley startups. So far, Chinese activity in robotics and AI is on a rampage and there are no signs of a slowdown in innovation.”If there was any doubt that growth would continue, it can be laid to rest. By some estimates, China now exports more robots than the U.S. ForwardX is illustrative of the trend. Only 7 months after the close of its $63-million Series B round, the latest round of funding brings ForwardX to approximately $100 million in total investment since its founding in 2016.”Our latest round of funding contributes to the positive momentum we have been building over the past 24 months. With a growing market share across our key territories, we look forward to continuing to deliver transformational results to our current and future customers,” Founder and CEO Nicolas Chee says. “While previously we’ve been focused on the domestic Chinese market, 2021 has brought us more success outside of China. We’re really looking forward to making our solutions available to a wider audience and cementing our position as a dominant player in North and South America, Asia, and Europe.”

Not surprisingly, the company has ambitions to expand and plans to use the new capital in part to increase its deployment capabilities in key markets, such as the US market, and expand its sales reach into new markets. ForwardX is opening an office on the East Coast as well as in Tokyo, which might be read as a shot across the bow of two once-dominant robotics powerhouses.”It’s an exciting time for us and the industry as a whole. COVID-19 made it difficult to expand overseas during 2020, but this year has brought us a lot more success in that regard,” says ForwardX’s COO, Yaxin Guan. “E-commerce in the US has seen its 18-month spike become the new base level resulting in accelerated demand for automation, and, with this round of funding, we’re in a better position to deliver quality solutions to North American customers.”So far the company has deployed fleets of autonomous mobile robots (AMRs) to partners like JD Logistics, SF DHL Supply Chain China, TCL Electronics, ITOCHU Logistics China, and Dongfeng Motor Corporation. LinkedIn China dubbed ForwardX a Top 13 Startup. More