Monthly Archives: April 2020

Starsky robotic trucking has closed their doors

In March, Stefan Seltz-Axmacher, CEO and founder of Starsky Robotics, announced the end of their trucking company, which combined autonomous driving software and remote monitoring techniques to move big rigs. Back in 2015, I had advised Seltz-Axmacher on their plan, but had lost touch. Recently he published a detailed essay outlining the causes of the failure of the company which caused some stir, because one of its assertions that effectively, the problem is too hard, and others will fail as well. Others have rejected that claim and argue that Starsky failed because of failings of the company itself, not the industry.

Lets look at some of the arguments made in the essay:

Ill actually start with some elements of #2 that I dug into in a discussion last week with Seltz-Axmacher. Starsky picked trucking because its a horribly managed industry with lots of opportunities to do better. Theres a giant driver shortage. Drivers are also sometimes unreliable as one customer told him, a robot is unlikely to get into a fight with people at a warehouse, or decide to stop in Las Vegas and spend a few days in a strip club. This doesnt happen all the time in trucking, but it happens enough that having it never happen is a big plus. Starsky planned to run their trucks only on the easiest of highways, short to middle distance runs on clear, open uncongested highways. If a problem arose due to traffic or weather, the truck would just pull over because multi-hour stops are common with human drivers too.

This also meant that a combination of full self-driving with occasional remote assistance could work on these easy roads. Their trucks would never change lanes on their own. They would not mind going slow behind other trucks. They would not mind anything. They felt they picked the easiest driving problem to solve, other than, of course the issue of moving an 40 ton vehicle at high speed and the risks that entails.

Current fleet operators are not early adopters. It is indeed going to be hard to convince them to do something this radical, even with the problem in finding good drivers, or any drivers at all. Starskys original plan was all remote operation, sticking only to roads with good data. In 2015, I told them that finding such roads would be a challenge. Its more possible today, and the deployment of services like Starlink DTLK will probably make it much easier soon.

If existing operators are not early adopters, Starsky reports that investors are scared of having to become a freight carrier in order to be a robotic truck company. Theyre probably right VC investing habits are strange to the rest of the world. They expect to invest in a dozen interesting startups each with the potential of becoming a home run and expecting the other 11 to try like crazy for that but flame out. Traditional businesses dont usually fit that mold.

So here we have a case where Seltz-Axmacher is right that trucking can be a hard sell though it hasnt stopped many other trucking options from getting large investments.

Youll need to read the essay for the full details, but it touches on one of the big questions of 2020 how much harder is self-driving AI than people originally thought? In particular, there was a lot of enthusiasm, some of it definitely hype, about the powers of deep neural networks.

Pretty much every car team has done extensive work building training data for these machine learning approaches. That means gathering real world data (images and LIDAR clouds) and having humans label them to train the AI. This technique has delivered astonishing results, by the standards of just a few years ago. The question is, is it good enough to provide the quality level for self driving, and when will it be, and will it ever be?

Seltz-Axmacher correctly points out its pretty easy to get some early impressive results, and this guiles people into thinking full success is just around the corner. Several companies have even tried to build self-driving systems with full end to end neural networks, which are black boxes you stick camera pixels in and get driving commands out of (steering and pedals.)

Hes right that pure supervised machine learning is not enough right now, and may be some distance in the future. Tesla TSLA is betting it isnt, but most companies are trying to build hybrids that use other algorithms combined with asking machine learning to do what its best at. They still believe this strategy will succeed. Generally, they have looked with disdain on those hoping to use an end-to-end approach, for the very reasons that Seltz-Axmacher outlines. In 2019 and 2020, there has been a pull-back by several players, particularly those in no particular hurry to see the automotive industry disrupted. Those who exist to do that disruption always expected the problem to be hard, I believe, but do not think their efforts are wasted.

That includes the self-driving truck world. Many companies have been attracted to trucking because highway driving is simple, even if trucks are fast and heavy. I mean really simple compared to urban streets. And the commercial value is also very clear. If anything, the commercial value is too clear, and there could be backlash when accidents come (even if at a lower rate) that people are being hurt just to make shipping more efficient, rather than to change how transportation works in general.

This claim is also true, though not entirely. There are forward thinking VCs and strategic investors who could be sold on a somewhat more capital and infrastructure intensive business. Its true that, given the choice, they would rather invest in an Uber that writes only software and owns no cars. The returns are far greater. But even Uber can get investment selling a story of switching to owning large fleets of robotaxis, replacing their drivers.

It may simply be that as the slowdown and market jitters have come, it was Starskys plan and company that didnt pass muster, and not the concept behind it. Certainly several other companies have raised rounds and gotten good valuations, though perhaps not as stratospheric as the valuations from a couple of years ago. There is still a very big prize to be won.

Seltz-Axmacher touches on a real issue when he wonders how much people really care about safety. After all, every company in every presentation you see says, we are all about safety and safety is priority #1 for us. Now, you have to say that, and everybody is very interested in safety, because if you cant attain safety, you cant put your product on the market. So in that sense its a top priority. But in reality, in almost every business, Safety is definitely third after functionality and price. We can recount a hundred stories of products that could have been safer if they cost more money, or has less functionality. After all, self-driving cars that only went 10mph would be pretty easy to make safe quickly, but nobody would want them.

In fact, when car buyers are asked what factors they are considering in choosing their next car, they always list safety as the first choice. Studies of what factors actually govern their choices have suggested its really in more like seventh place. Otherwise, nobody would buy from anybody but the highly-safety focused brands like Volvo and Mercedes, which at various times in history have had the top reputations in that area. They dont.

But Seltz-Axmacher points out something stronger that the public, press and investors dont get excited about safety because it is inherently boring. And it is. The ideal demo ride in a self-driving car is dull as dishwater. Its hard to demo safety.

In the early days of the field, when advising a potential X Prize on self-driving to follow on the heels of the DARPA challenges, I suggested a man vs. machine safety contest. Vehicles would drive a tricky course, and fake obstacles, inflatable pedestrians and cars on small robot platforms, would create problems. Both the skilled race drivers and the robocars would compete on who could avoid hitting anything. It might have been popular not when perfect, but when things are hit but once the robots got perfect while the famous race car drivers were not, it would actually install confidence in the public. But nothing like this has ever been done, and no demo like this has been set up, both because nobody wants video of cars hitting even balloons, and it turns out that just driving was complex enough that handling fake situations never got high on the priority list. Teams now do this in simulator, or sometimes on test tracks, but its never the exciting demo. (Waymo shows a video of their car reacting to employees letting moving boxes fall onto the road.)

I wasnt in the VC meetings that turned down more funding for Starsky. Todays VC climate has cooled, and a lot of companies are being turned down. They may have had other flaws which they dont want to go into. I suspect a lot of companies will continue to get funding, though some will be hurt by having initially received high valuations that cant be sustained.

And it may be true that building a robocar or robotruck just isnt a game for a small startup. Its hard enough for the megafunded startups like Zoox, Cruise and Aurora. Theres a tremendous amount of hard slogging detail work to get from 99% to 99.9999%, which is where you need to be. Its not 1% harder, its 10,000 times harder, and not everybody realizes that. The closer you get to great safety, the harder and harder it is, because each issue becomes harder to find, and each change could cause a regression on something fixed long ago. This may remain something for the big boys, at least for a few years. (Things which took billions to do the first time eventually become doable in a dorm room, it often seems.)

Some companies were going to fail. There was no way they could all survive. Indeed, there is no way that most of the teams out there will survive. Thats to be expected in something as audacious as this. Big valuations demand big results, and only a few will deliver them.

Continued here:

Starsky Robotics Shuts Down And Worries Everybody Else Will Also Fail In Robotic Trucks - Forbes

As the coronavirus pandemic forces people to keep their distance, could this be robots time to shine? A group of scientists think so, and theyre calling for robots to do the dull, dirty, and dangerous jobs of infectious disease management.

Social distancing has emerged as one of the most effective strategies for slowing the spread of COVID-19, but its also bringing many jobs to a standstill and severely restricting our daily lives. And unfortunately, the one group that cant rely on its protective benefits are the medical and emergency services workers were relying on to save us.

Robots could be a solution, according to the editorial board of Science Robotics, by helping replace humans in a host of critical tasks, from disinfecting hospitals to collecting patient samples and automating lab tests.

According to the authors, the key areas where robots could help are clinical care, logistics, and reconnaissance, which refers to tasks like identifying the infected or making sure people comply with quarantines or social distancing requirements. Outside of the medical sphere, robots could also help keep the economy and infrastructure going by standing in for humans in factories or vital utilities like waste management or power plants.

When it comes to clinical care, robots can play important roles in disease prevention, diagnosis and screening, and patient care, the researchers say. Robots have already been widely deployed to disinfect hospitals and other public spaces either using UV light that kills bugs or by repurposing agricultural robots and drones to spray disinfectant, reducing the exposure of cleaning staff to potentially contaminated surfaces. They are also being used to carry out crucial deliveries of food and medication without exposing humans.

But they could also play an important role in tracking the disease, say the researchers. Thermal cameras combined with image recognition algorithms are already being used to detect potential cases at places like airports, but incorporating them into mobile robots or drones could greatly expand the coverage of screening programs.

A more complex challengebut one that could significantly reduce medical workers exposure to the viruswould be to design robots that could automate the collection of nasal swabs used to test for COVID-19. Similarly automated blood collection for tests could be of significant help, and researchers are already investigating using ultrasound to help robots locate veins to draw blood from.

Convincing people its safe to let a robot stick a swab up their nose or jab a needle in their arm might be a hard sell right now, but a potentially more realistic scenario would be to get robots to carry out laboratory tests on collected samples to reduce exposure to lab technicians. Commercial laboratory automation systems already exist, so this might be a more achievable near-term goal.

Not all solutions need to be automated, though. While autonomous systems will be helpful for reducing the workload of stretched health workers, remote systems can still provide useful distancing. Remote control robotics systems are already becoming increasingly common in the delicate business of surgery, so it would be entirely feasible to create remote systems to carry out more prosaic medical tasks.

Such systems would make it possible for experts to contribute remotely in many different places without having to travel. And robotic systems could combine medical tasks like patient monitoring with equally important social interaction for people who may have been shut off from human contact.

In a teleconference last week Guang-Zhong Yang, a medical roboticist from Carnegie Mellon University and founding editor of Science Robotics, highlighted the importance of including both doctors and patients in the design of these robots to ensure they are safe and effective, but also to make sure people trust them to observe social protocols and not invade their privacy.

But Yang also stressed the importance of putting the pieces in place to enable the rapid development and deployment of solutions. During the 2015 Ebola outbreak, the White House Office of Science and Technology Policy and the National Science Foundation organized workshops to identify where robotics could help deal with epidemics.

But once the threat receded, attention shifted elsewhere, and by the time the next pandemic came around little progress had been made on potential solutions. The result is that its unclear how much help robots will really be able to provide to the COVID-19 response.

That means its crucial to invest in a sustained research effort into this field, say the papers authors, with more funding and multidisciplinary research partnerships between government agencies and industry so that next time around we will be prepared.

These events are rare and then its just that people start to direct their efforts to other applications, said Yang. So I think this time we really need to nail it, because without a sustained approach to this history will repeat itself and robots wont be ready.

Image Credit: ABBs YuMi collaborative robot. Image courtesy of ABB

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Robots to the Rescue: How They Can Help During Coronavirus (and Future Pandemics) - Singularity Hub

OYSTER BAY, N.Y., April 2, 2020 /PRNewswire/ -- The Coronavirus outbreak has highlighted use cases for mobile robotics to successfully disinfect, monitor, surveille, and handle and deliver materials. These proven use cases will propel the overall mobile robotics market to US$23 billion by 2021, states global tech market advisory firm, ABI Research.

"Crises shift perceptions on what is possible regarding investment and transformative action on the part of both private and government actors. By the time the COVID-19 pandemic has passed, robots will be mainstreamed across a range of applications and markets," says Rian Whitton, Senior Analyst at ABI Research.

The virus has been a good opportunity for companies to display robots for public applications. One of the more popular has been deploying mobile unmanned platforms with Ultraviolet (UV) light to disinfect facilities. Danish company UVD Robots is reaping the benefits of this opportunity and is scaling up deployments of robots to disinfect hospitals. U.S.-based Germ Falcon is offering a similar UV disinfection solution for aircraft, while Chinese TMiRob is deploying disinfection robots in Wuhan. "Automating disinfection is a key part of maintaining health and safety and could be one of the major bright spots in the response to COVID-19," Whitton points out.

Drones have also been deployed to enforce curfews and surveil areas for security purposes. This represents a big opportunity for aerospace and drone companies to increase sales to government agencies. ABI Research expects the small drone delivery market to reach US$414 million by 2021 and US$10.4 billion by 2030.

In the short term, to enforce quarantine mandates, governments will need to increase their security apparatuses, as well as the productivity of their medical agencies. Robots will be key to achieving that through disinfection, monitoring, and surveillance. Furthermore, the shutting down of households and even ships represents a chance for robot delivery companies (for both land and air) to display their worth. The drone delivery market could take its experience with transporting supplies in the developing world and scale up their operations in the most affected countries.

Long-term, COVID-19 is leading to a significant reassessment of the global manufacturing supply chain. America's dependence on Chinese imports for basic equipment and medicines is becoming a contentious issue, and government representatives are already interpreting the crisis as a chance to revitalize the campaign to reshore more manufacturing capacity to the domestic market. If this translates into more significant measures by governments to diversify or reshore the manufacturing of key goods, this could bode very well for the robotics industry, as such changes would require big increases in CAPEX and productivity improvements within developed countries.

COVID-19 represents a disaster for robotics vendors building solutions for developed markets in manufacturing, industry, and the supply chain. But for vendors targeting markets closer to government, such as health, security, and defense, it represents a big opportunity. Whitton recommends that "industrial players develop customized solutions for non-manufacturing use cases or look to build comprehensive solutions for enabling a scale-up in medical supply manufacturing. For mobile robotics vendors and software companies targeting more nascent markets, this represents a big chance to highlight the importance of robotics for dealing with national emergencies, as well as mitigating the economic shock."

For a clearer picture of the current and future ramifications of COVID-19 across technologies and verticals, including Industrial, Collaborative and Commercial Robotics, download the whitepaper Taking Stock of COVID-19: The Short- and Long-Term Ramifications on Technology and End Markets.

About ABI ResearchABI Research provides strategic guidance to visionaries, delivering actionable intelligence on the transformative technologies that are dramatically reshaping industries, economies, and workforces across the world. ABI Research's global team of analysts publish groundbreaking studies often years ahead of other technology advisory firms, empowering our clients to stay ahead of their markets and their competitors.

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COVID-19 Pandemic Impact: A Surge in Proven Mobile Robotics Use Cases for Disinfection, Monitoring, Surveillance, and Delivery Will Propel the Market...

FIRST Robotics Team 1741 Red Alert Robotics based in Center Grove High School won the prestigious Chairmans Award at the Bloomington, Ind. district competition on Saturday, March 7. This award honors the team that best represents a model for other teams to emulate and best embodies the purpose and goals of FIRST.

Since Jan. 4, FIRST Team 1741 Red Alert Robotics has been working on a robot to compete in this years game, Infinite Recharge.SM. The team also did well in the robot competition by finishing the qualification matches as the seventh-ranked alliance captain out of 32 teams. Red Alert Robotics is in their 15th year of competition. This is their sixth chairmans award. By winning the most prestigious award given by FIRST, Red Alert has automatically qualified for the State Championship at Lafayette Jefferson High School, where they will compete against 31 other teams for a chance to qualify for the FIRST Championships in Detroit.

Combining the excitement of sport with the rigors of science and technology, the FIRST Robotics Competition is the ultimate sport for the mind. High-school student participants call it the hardest fun youll ever have. Students ages 14-18 get to work alongside professional engineers, build and compete with a robot of their own design, learn and use sophisticated hardware and software, develop design, project management, programming teamwork and strategic thinking skills, earn a place in the World Championships and qualify for more than $30 million in college scholarships.

Under strict rules, limited resources and an intense six-week time limit, teams consisting of 15-60 students, one to two coaches and three to 10 volunteer mentors are challenged to raise funds, design a team brand, hone teamwork skills and build and program industrial-size robots to play a difficult field game against like-minded competitors. Its as close to real-world engineering as a student can get. Volunteer professional mentors lend their time and talents to guide each team.

For more information, email Nathan Coulombe at ncoulombe@redalert1741.org.

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Center Grove-based robotics team wins at district competition - Southside Times

Dublin, April 02, 2020 (GLOBE NEWSWIRE) -- The "Collaborative Robots - Market Shares, Market Forecasts, Market Analysis, 2020-2026" report from Wintergreen Research, Inc has been added to ResearchAndMarkets.com's offering.

Collaborative Robot markets valued at $2.3 billion in 2019 promise to grow to $13.3 billion by 2026. With the opportunity to participate in the 5G next-generation semiconductor markets. Collaborative Robots will achieve broad economies of scale, making them far more affordable and more available for the entire new industrial revolution.

Worldwide Collaborative Robots markets are poised to achieve remarkable uptake in the market. Next-generation collaborative robots promise to bring the biggest change in human labour that has ever occurred. The market for the products is not a huge market, but the ability to replace much human labour in factories and service jobs is a big deal. Whereas robot ability to complete repetitive tasks with speed, strength, and precision has been hampered, collaborative robots change that situation. Until now, industrial robots have been designed to work autonomously with safety assured by isolation from human contact.

Once human contact becomes possible, robots become a lot more useful. With collaborative robots, safety relies on lightweight construction materials. Rounded edges and limits on speed or force are essential aspects of collaborative robots. Safety depends on sensors and software used to implement collaborative interaction. Human cooperation adds dexterity, flexibility, and problem-solving to an industrial robot. Collaborative service robots can function as information robots in public spaces; logistics robots that transport materials within a building, inspection robots equipped with cameras and visual processing technologies.

Key Topics Covered

1. Collaborative Robots: Market Description and Market Dynamics

2. Collaborative Robots Market Shares and Forecasts2.1 Collaborative Robots Market Driving Forces2.1.1 Digitalization of Labor Reduces Complexity of Manufacturing2.2 Collaborative Robot Market Shares2.3 Collaborative Robot Market Forecasts2.3.1 Collaborative Robot Market by Payload Capacity2.4 Collaborative Robot Market Segments2.4.1 Autonomous Mobile Robots Market Shares2.4.2 Collaborative Robot Market by Application: Automotive Repetitive, Fetching and Carrying, Machine Feeding, Final Assembly, Inspection, Logistics, Patrolling, and Public Information2.4.3 Collaborative Robot Industry: (Automotive, Electronics, Metals & Machining, Plastics & Polymers, Food & Beverages, Healthcare),2.4.4 Collaborative Robot Market by Payload Capacity2.4.5 Industrial Robot Installed Base Units2.4.6 E-Commerce2.4.7 Picking, Packing, And Palletizing2.4.8 Welding Done by Collaborative Robots2.4.9 Collaborative Robotic Handling Materials2.4.10 Collaborative Robot Applications2.5 Collaborative Robot Prices2.6 Collaborative Robot Regional Market Analysis

3. Empowering Robots and Humans To Work Side-By-Side

4. Collaborative Robots Research and Technology4.1 Safety Standards for Collaborative Robots4.2 Collaborative Robot End-Use Cases4.3 Robots and Robot Systems - Safety Requirements ANSI/RIA R15.06-2012, Industrial4.3.1 General Motors has 35,000 Robots in Production4.3.2 GE Hendersonville

5. Collaborative Robots Company Profiles5.1 ABB5.1.1 IBM and ABB Working Together with Cognitive Visual Inspection Tools5.2 Aceita5.2.1 Acieta Partnered with FANUC5.3 Acronis International GmbH Collaborative Robots5.4 AMP Robotics5.5 Asiga5.6 Balyo5.7 Cognex5.7.1 Cognex Cameras5.8 Datto5.9 Epson5.10 Fanuc5.10.1 Fanuc CRX Series Collaborative Robots5.10.2 Fanuc5.11 Festo5.11.1 Festo Family-Owned Company5.11.2 Festo Collaborative Robotics5.12 Hahn Group / Rethink Robots5.13 IBM5.13.1 IBM Watson5.13.2 IBM / Softbank5.13.3 IBM and ABB Working Together with Cognitive Visual Inspection Tools5.14 inVia Robotics5.15 Kuka5.16 Locus Robotics5.17 Motoman5.18 Omron5.19 OnRobot5.20 Clearpath Robotics / OTTO Motors5.21 Productive Robotics OB7 Cobots5.22 Robotiq5.23 RightHand Robotics5.23.1 RightHand Robotics Japanese Subsidiary5.24 RobotWorx5.25 Shangtang Technology / SenseTime5.26 Schmalz5.26.1 Schmalz Collaborative Robots for Motoman5.27 Schunk5.27.1 Schunk Collaborative Robots for Motoman5.28 Seegrid5.29 Softbank5.30 Soft Robotics5.30.1 Soft Robotics Collaborative Robots for Motoman5.31 Stanley Black & Decker5.31.1 Stanley Engineered Fastening5.31.2 Stanley Assembly Technologies.5.32 Starship5.33 Techman Robot5.34 Teradyne / Universal Robots5.34.1 Teradyne5.34.2 Teradyne Acquired Mobile Industrial Robots5.34.3 Teradyne Acquired Energid5.34.4 Teradyne Acquired AutoGuide5.34.5 Teradyne Acquired Universal Robots5.35 Vecna5.36 List of Selected Collaborative Robot Companies

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A-Z List of Companies Mentioned

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CONTACT: ResearchAndMarkets.comLaura Wood, Senior Press Managerpress@researchandmarkets.comFor E.S.T Office Hours Call 1-917-300-0470For U.S./CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900

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Global Collaborative Robots Industry Valued at $2.3 Billion in 2019, is Expected to Surpass $13 Billion by 2026 - Yahoo Finance

Tally inside a store.

Grocery stores are considered essential businesses during the coronavirus outbreak, and employees have been working overtime to keep shelves stocked. As retailers struggle to hire more workers to meet rising demand, the use of robots may grow. Brad Bogolea, co-founder and CEO of Simbe Robotics, shared more in an interview.

Simbe Robotics' autonomous shelf-scanning robot, Tally, has been used in Schnucks Markets and Giant Eagle stores. The no-maintenance robot has more than 40 sensors that allow it to avoid obstacles as it navigates the floor to scan shelves. Tally can check 15,000 to 30,000 products per hour as it audits inventory through the help of cameras, computer vision and machine learning. It is able to identify prices, product placement, availability and special promotions.

"Tally strategically, autonomously roams up and down store aisles, quietly scanning shelves and identifying out of stock, misplaced and mispriced items. The data Tally collects about shelf health helps store teams by automating the tedious, often dreaded task of inventory and freeing up human workers to service customers in store, improving the shopper experience," Bogolea said.

Tally the robot.

Stores can use the data Tally collects in real-time, so they can optimize products on the shelves. This also helps them make better informed ordering and product placement decisions while analyzing trends. The data can be shared with retailers consumer packaged goods (CPG) brand partners to make better business decisions.

"Amid the coronavirus outbreak, we are seeing unprecedented surges in demand for not only products in-store but for retail staff across the country. Our partners have responded by making their stores more accommodating by adjusting their operations to ensure the elderly and other at-risk communities have time to shop without crowds and giving store teams sufficient time to restock and sanitize. We know that some stores are modifying Tally's traversal times to best support their adjusted hours," Bogolea added.

Tally's data is also helping customers find things easier inside the store. Schnucks Markets integrated Tallys product location information into its customer-facing app, which helps both shoppers and newer employees who are not as familiar with the store layout find the exact product location in real-time, down to the aisle and shelf section.

"For shoppers, experiencing out-of-stocks can be frustrating. Statistically, we know that two out of five shoppers encounter empty shelves in place of the products they are looking for, simply due to retailers not optimizing their inventory. For customers, Tally helps retailers ensure the products they are looking for are in stock, priced correctly, and where they are expected to be on the sales floor, improving the overall shopping experience," Bogolea said.

Bogolea believes retailers can lean on robotics to empower their human team members without replacing the workers, which would lead to job loss. Allowing technology like Tally to take on the repetitive, time-consuming task of inventory frees up store associates to focus on higher priority work, like getting items back on shelves as quickly as possible. This reliance on technology to increase efficiency and minimize supply chain disruption in the stores will continue to grow.

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How Robots Are Helping Grocery Stores During The Coronavirus Outbreak - Forbes