Category Archives: Robotics

ISKANDAR PUTERI: Johor is set to become a major player in the drone and robotics sectors with the first specific zone in South-East Asia.

Mentri Besar Datuk Hasni Mohammad (pic) said the Drone and Robotic Zone (DRZ) Iskandar was a collaboration between Iskandar Investment Berhad (IIB), together with global logistics company DHL and Malaysian Global Innovation and Creativity Centre (MaGIC).

"Johor needs an integrated digital ecosystem to further boost our digital economy to the next level, especially in the South-East Asia region.

In line with the Johor Digital Masterplan to transform Johor into a smart state and accelerate its digital economy, the launch of DRZ Iskandar brings us one step closer in creating a digital hub in Iskandar Malaysia, as announced recently in the state Budget 2021, he added.

He stressed that the DRZ was projected to bring in over RM351mil of investments and generate 1,000 high-value jobs by 2025 in drone and robotics.

Hasni said this in his speech virtually during the official launch of DRZ Iskandar on Tuesday (Dec 8).

Also present at the event virtually was Science, Technology and Innovation Minister Khairy Jamaluddin.

Meanwhile, Khairy said that DRZ Iskandar was timely with Asia and North America the largest drone markets currently.

He added that according to the 2020 industry report produced by Drone Industry Insights, Asia was expected to experience growth from US$8.6bil (RM34.9bil) in 2020 to US$17.9bil (RM72.8bil) in 2025 in revenue.

As for robotics, Asia Pacific accounts for 54% of the global market, and is the leading market for robotics. This is set to double in five years with the increasing global demand for automation in various industries.

According to the Global Startup Ecosystem Report 2020 (GSER2020), Malaysia was ranked in the Top 10 of Emerging Ecosystems in Performance, and in the Top 20 for Emerging Ecosystems in Talent with an ecosystem valuation of US$15.3bil (RM63.5bil), he added.

He also said that Malaysia retains its 35th position out of 129 countries in the Global Innovation Index 2019 and remains among the middle-income economies that were bridging the innovation divide.

I am confident that with these indicators, coupled with our strategic location, ready infrastructure and a growing community of drone and robotics enthusiasts, Malaysia is set to become the drone and robotics hub of South-East Asia, he added.

Original post:

Johor set to be major player in drone, robotics sectors with new zone - The Star Online

Karakuri,the world leading food robotics company, is bringing the future of food to life as it lifts the lid to unveil the worlds first automated canteen to make meals, the DK-One.

Karakuris robotic system will revolutionise how and what we eat in restaurants, canteens, buffets, hotels and supermarkets as demand for personalised nutrition grows and the industrys looks for new ways to operate in a post-Covid world.

Today the company is showcasing a pre-production version of their DK-One robot, the next exciting stage in Karakuris journey to creating an entirely new category of made-to-order healthy convenience food. In order to accelerate the companys growth, Karakuri has also closed a 6.3million investment, led by firstminute capital and which includes funding from Hoxton Ventures, Taylor Brothers, Ocado Group and the Future Fund, which was developed by the UK government and is being delivered by the British Business Bank. This investment will be used to further accelerate the development of Karakuris technologies and create new products beyond the DK-One.

Todays announcement shows Karakuris first pre-production machine which uses the latest innovation in robotics, sensing and control technologies to offer freshly prepared, high quality hot and cold meals, which maximise nutritional benefits, restaurant performance and minimise food waste.

The pre-production version of the DK-One is being demonstrated and evaluated by customers in Karakuris facility in Hammersmith, London.

Post-COVID restrictions, further on-customer-site trials of the DK-One are expected to take place in the first half of 2021.

Key features of this version of the DK-One include:

Barney Wragg, CEO and co-founder of Karakuri, said,This is one of the most highly-anticipated stages of our business and a really important step. Weve spent time talking to our customers and industry specialists, and seen huge enthusiasm for DK-Ones potential. Now up and running, this will be the first time we can use a pre-production machine to demonstrate the DK-Ones commercial and nutritional benefits in the real world and thus demonstrate our vision for the future of food. I am proud of our amazing team for the work theyve done to get this far this quickly, despite the challenges of the pandemic. We are all really excited to begin fulfilling our customers expectations.

Professor David Lane, CBE, Director of the Edinburgh Centre for Robotics and Co-Chair of the UK Government Robotics Growth Partnership, added,Even before the pandemic, it was clear there were many opportunities to increase sustainability, resilience and productivity in the catering industry, and to better address changing consumer tastes and lifestyles while reducing the huge amount of wastage. The pandemic has thrown up further challenges of distancing and remote working that can now readily be addressed through robotic innovation. This is why there has been a huge interest in the developments Barney and his team are innovating at Karakuri and its a pleasure to be supporting them in the next stage of the business

The DK-One is the worlds first robotic solution for high throughput, fast turnaround, completely personalised, portion-controlled, volume catering. Customers are able to customise and place their order from their phone or an in-store tablet. The robot will individually prepare each meal, selecting from 18 hot or cold ingredients with precise accuracy. The DK-One prepares multiple orders at the same time, ensuring it meets the demand of the busiest restaurants.

Karakuri is a UK robotics startup established in February 2018. It emerged from the Founders Factory venture studio with the goal of utilising groundbreaking intelligent robotics, to transform and improve ready to eat catering and, at the same time, reduce the associated food wastage. Karakuri was founded by Barney Wragg, Simon Watt and Brent Hoberman and has closed 13.5m funding including investments from Ocado, Hoxton Ventures, firstminute capital, Taylor Brothers and the Future Fund.

More:

Karakuri unveils its first robotic canteen set to change the global food and hospitality industry - Robotics Tomorrow

08/12/2020 Panasonic System Solutions Europe

Panasonic announces its R&D strategy for its next generation of robots. Based on its broad expertise in sensor as well as drives technology, and derived from its leading technologies in industrial robots, Panasonic will tackle the needs of aging societies from healthcare add-ons to labour shortages in retail and logistics.

The companys approach is on pragmatic solutions that work with people, and this can be defined within three core pillars: augmented solutions, stand-alone solutions, and complete robotics automation solutions. The company introduced six robot models aligned with its new Robotics strategy during a virtual press conference.

Utilizing the Advantage in Industrial Robots & Sensory

Panasonic is a tier-one producer of industry robots due to its development of cutting-edge sensors and drives. The company predicts that the general market trends in the components sector such as the focus on miniaturization, the combination of multiple intelligent sensors in one device, and the reduction of mass, enable new applications to be explored.

Johannes Spatz, President of Panasonic Industry in Europe comments, We believe the knowledge and technology in these areas along with our know-how in industrial robots prepare a reliable and tested pathway for successful applications of robotics in other areas.

One of the examples highlighting the transference of industrial applications to the healthcare industry is the usage of lidar sensors within delivery robots that had originally been developed for automated guided vehicles in production sites. This semi-automated robotics application is enabling the outsourcing of standard tasks to meet the needs of staff shortage within busy hospitals.

Increasing Value Depth & Adaption Speed for Robotics

Panasonic has pointed out that two key trends are on the rise: customers expect turnkey solutions from one supplier, and the adaption time decreases significantly. During the press conference, the company highlighted the engineering solution for the Continental factory in Regensburg as an example for the demand for holistic solutions. Delivered this year, the solution included process analysis, re-designing the layout of the loading area, physical process optimization, and the technical hardware. Alongside this was the installation of a Visual Sort Assist solution with direct integration into the SAP warehouse management system. As an example for the reduction in adaptation time, Panasonic presented a project of equipping a 3,000sm retail store in the UK within one working day with Electronic Shelf Labels including the connection to the warehouse system.

Academic Partnerships & Open Source Solutions

Central to the new strategy is a strategic change. Panasonic now has cooperation and joint offices with eight universities two in Europe and six in Japan. Among the partnerships in Europe are those with the Technical University in Munich, Germany, and the ETH in Zurich, Switzerland. Takeshi Ando, head of the Global Robotics R&D activities at Panasonic summarizes: Panasonic has evolved from pushing proprietary systems to an open technology platform. The new platform combines elemental technologies such as sensing, system integration, planning and computing, locomotion, object handling, communication and power source and battery.

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Panasonic's Robotics Solutions: The Importance of Functional over Fun - Process & Control Today

Deep learning is great, but no, it won't be able to do everything. The only way to make progress in AI is to put together building blocks that are there already, but no current AI system combines. Adding knowledge to the mix, getting over prejudice against "good old AI", and scaling it up, are all necessary steps in the long and winding road to reboot AI.

This is a summary of the thesis taken by scientist, best-selling author, and entrepreneur Gary Marcus towards rebooting AI. Marcus, a cognitive scientist by training, has been doing interdisciplinary work on the nature of intelligence -- artificial or otherwise -- more or less since his childhood.

Marcus, known in AI circles among other things for his critique on deep learning, recently published a 60-page long paper titled "The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence." In this work, Marcus goes beyond critique, putting forward concrete proposals to move AI forward.

As a precursor to Marcus' recent keynote on the future of AI in Knowledge Connexions, ZDNet engaged with him on a wide array of topics. We set the stage by providing background on where Marcus is coming from, and elaborated on the fusion of deep learning and knowledge graphs as an example of his approach.

Today we wrap up with a discussion on how to best use structured and unstructured data, techniques for semantics at scale, and future-looking technologies.

Marcus acknowledges that there are real problems to be solved to pursue his approach, and a great deal of effort must go into constraining symbolic search well enough to work in real-time for complex problems. But he sees Google's knowledge graph as at least a partial counter-example to this objection.

Knowledge graphs are a rebranding of the semantic web approach and technology stack, introduced by Sir Tim Berners Lee 20 years ago. Marcus emphasized there is a lot of knowledge which is not picked up by AI on the web, and adding more semantics and metadata using standards like RDF would help.

A prime example is Wikipedia. People can read it it, and advance their knowledge by doing so. Wikipedia has been targeted by knowledge and data engineers too, in order to achieve what Marcus described. One of the first knowledge graphs, established before the term was even coined, and still one of the biggest ones today, is DBpedia.

DBpedia is one of the biggest and oldest knowledge graphs around. It is populated by extracting data from Wikipedia

What the people behind DBpedia have done is they have created sophisticated mechanisms to extract structured knowledge from Wikipedia. Imagine having all the knowledge in Wikipedia, but being able to query it like you would query a database. Marcus noted the content in Wikipedia boxes is what is most accessible to current techniques:

They're already somewhat useful for things like disambiguation and what a particular use of a word is going to be. There's a lot of knowledge in Wikipedia that's in the form of unstructured text that doesn't go in those boxes and we're not nearly as good as leveraging that. So if you have a historical description of what somebody did during some particular war, the system's probably not going to be able to understand that at this moment.

But it will be able to like look up that this person's title was captain. They were alive during these years. They were they died in this year. The names of their children were this and that. So the latter is data that's more structured, and is more easily leveraged by the current techniques. And there's a whole lot of other data that we're not using.

I'm glad to see that we're starting to use at least some of it. I don't think we're using it as well as one could in principle, because if you don't understand the conceptual relations between all these entities, it's hard to maximize the use that you get out of it.

The people in DBpedia get that apparently. This is why they have created the DBpedia Ontology: a shallow, cross-domain ontology, which has been manually created based on the most commonly used infoboxes within Wikipedia. Ontologies, in the context of knowledge graphs, can be thought of as the schema used to populate the knowledge graph with facts.

In addition, we also have Wikidata. Wikidata is in a way the reverse of DBpedia: where DBpedia creates a structured version of unstructured knowledge in Wikipedia, Wikidata acts as central storage for the structured data of its Wikimedia sister projects, including Wikipedia. It's a free and open knowledge base that can be read and edited by both humans and machines.

Another way to leverage semantics and knowledge in machine learning which is gaining in popularity is embeddings. This is a way of representing complex structure in simpler ways, in order to speed up calculations. As graphs are increasingly being recognized as a rich structure to represent knowledge, graph embeddings are gaining in popularity too.

Graph embeddings are the transformation of graphs to a vector or a set of vectors. Embedding should capture the graph topology, edge-to-edge relationships, and other relevant information about graphs, subgraphs, and edges. There are specific techniques developed for knowledge graphs, too.

When asked about embeddings, Marcus replied with a quote from computational linguist Ray Mooney: "You can't cram the meaning of a whole $&!#* sentence into a single $!#&* vector."

"Vectors, at least as we understand them right now, often take a lot of different things, make a similarity measure around that, but don't really represent things with precision. And so they're often a mixed bag. You get something out of them, but you don't know exactly what. And sometimes it works, but it's not really all that reliable. I've yet to see that kind of architecture be supremely reliable".

Embedding is a method for reducing data dimensionality. Sometimes it works, but its reliability is not great, according to Gary Marcus

In his paper, Marcus mentioned something else which piqued our interest. Being someone who has studied human cognition, Marcus does not believe that the way to artificial intelligence necessarily goes through trying to mimic the human brain. We wondered what is his take on neuromorphic chips, i.e. AI chips that claim to mimic the human brain:

We should not be imitating human brains -- we should be learning from them, or from human minds. The best AI systems will have some of the properties of human minds and some properties of machines. They will put them together in new ways that exceed either what we could do with current machines or with current human brains.

In the case of neuromorphic chips, the idea is to learn from how the brain works in order to make better chips. So far, I'm totally sympathetic in principle. The reality is we don't know enough about neuroscience yet to make that work all that well. And I worry about people like Jeff Hawkins who try to stick only to the things we already know about the brain. I think we just don't know enough about the brain to really do that effectively yet.

You know, maybe 20 years from now we will be able to do that. But right now, our understanding of brain operation is pretty limited. And as a consequence, I think that the neuromorphic chips field has been more promise than results. There's not a lot of concrete applications from it yet.

We may have some reasons to think that it might lead us, for example, to lower power alternatives to the technologies that we're using right now. So far, I haven't seen anything really that useful come out of that literature. It will, but maybe we need to know a little bit more about how the brain works before we can really leverage that.

Another forward-looking idea, this time from software, is so-called Software 2.0. The traditional approach to software has been to build algorithms that encode in a really detailed way what software does. The idea behind Software 2.0 is that for really complex processes, it's very hard or even impossible to do that.

Instead of specifying how software works, the Software 2.0 approach is to use data from existing processes and machine learning to figure out a pattern, and produce something that we can use. There are some issues with the approach: not all processes have enough data we can use, and the machine learning development lifecycle is work in progress. Marcus, however, questions the approach altogether:

Nobody tries to build a Web browser by taking supervised learning over a bunch of logs of what users typed and what they saw on their screens. That's what the machine learning approach would be -- rather than sit there and laboriously code, you would just induce it from the data. And that doesn't really work. Nobody's even trying to make that work.

It's nice that we have some new techniques available. But if people think we're not going to need anybody to code..well, certainly in the short term, that's just not true. I think that the real revolution might come, but it's going to be a long time from what Charles Simoni called intentional programming.

Instead of writing all the lines of code that you want, have the machine figure out what is the logic of what you want to do. Maybe you do that with some machine learning, and some classical logic-driven programming, but we're not anywhere close to being able to do that.

Robots are really interesting because they force us beyond approximation, towards systems that really can cope with the real world, says Gary Marcus

Some people may be trying to get the Software 2.0 approach to work. As for Marcus, his focus is on Robust.ai, the company he founded. Rather than just being operated and working the assembly lines, Robust AI wants to build robots that work in a wide range of environments -- homes, retail, elder care, construction and so forth.

When asked why focus on robotics, Marcus' answer was similar to Facebook's Yann LeCun, one of Deep Learning's most vocal proponents. Facebook is also doubling down on robotics, and LeCun believes we're missing something in terms of how humans can learn so fast. The best ideas so far, he went on to add, have come out of robotics.

Marcus said he sees things somewhat similarly, but not entirely similar. He thinks robots are really interesting because they force us beyond approximation, towards systems that really can cope with the real world:

If you're dealing with speech recognition, you can solve the problem by just gathering a lot of data because words don't change that much from one day to the next. But if you want to build a robot that can say, wander the streets and clean them up, it has to be able to deal with the fact that every street is going to be different every hour, every day.

Robots have to be as resourceful as people, if we're going to put them out in the real world. Right now, robots mostly work in very well controlled environments with either no humans or humans limited to a particular place. Robots are very restricted in what they can do right now. And that allows us to sidestep the question of how do you make robots that are really autonomous and able to deal with things on their own.

This is part of the definition of a robot. I think that's a fascinating intellectual problem, and one that will push the field of AI forward considerably as we move robots more and more into the real world as a function of the business. This will be a huge opportunity -- not that much of the world is automated with robots right now.

Marcus said that robotics right now is maybe a 50 billion dollar industry, but it could be much bigger. In order to get to that place, we need to make robots safe, reliable, trustworthy, and flexible. Robust AI just raised $15 million, so apparently progress is under way.

Read more:

Getting there: Structured data, semantics, robotics, and the future of AI - ZDNet

Adhering to the declaration would prohibit researchers from working on robots that conduct search-and-rescue operations, or in the new field of social robotics. One of Dr. Bethels research projects is developing technology that would use small, humanlike robots to interview children who have been abused, sexually assaulted, trafficked or otherwise traumatized. In one of her recent studies, 250 children and adolescents who were interviewed about bullying were often willing to confide information in a robot that they would not disclose to an adult.

Having an investigator drive a robot in another room thus could yield less painful, more informative interviews of child survivors, said Dr. Bethel, who is a trained forensic interviewer.

You have to understand the problem space before you can talk about robotics and police work, she said. Theyre making a lot of generalizations without a lot of information.

Dr. Crawford is among the signers of both No Justice, No Robots and the Black in Computing open letter. And you know, anytime something like this happens, or awareness is made, especially in the community that I function in, I try to make sure that I support it, he said.

Dr. Jenkins declined to sign the No Justice statement. I thought it was worth consideration, he said. But in the end, I thought the bigger issue is, really, representation in the room in the research lab, in the classroom, and the development team, the executive board. Ethics discussions should be rooted in that first fundamental civil-rights question, he said.

Dr. Howard has not signed either statement. She reiterated her point that biased algorithms are the result, in part, of the skewed demographic white, male, able-bodied that designs and tests the software.

If external people who have ethical values arent working with these law enforcement entities, then who is? she said. When you say no, others are going to say yes. Its not good if theres no one in the room to say, Um, I dont believe the robot should kill.

Originally posted here:

Can We Make Our Robots Less Biased Than We Are? - The New York Times

By nature, this robotic surgical company has an enormous competitive edge. Intuitive Surgical (NASDAQ:ISRG) is one of the largest holdings in a new ETF called ProShares MSCI Transformational Changes ETF (NYSEMKT:ANEW) that captures the revolutionary changes accelerated by the pandemic. Here's what investors need to know.

Corinne Cardina: Definitely. Genomics and telehealth. I want to start with Intuitive Surgical because this is a Fool favorite in the healthcare space. It's the company behind the da Vinci robotic surgical system. It helps surgeons perform minimally invasive procedures. It's got a nice installed base of systems and enjoys a lot of competitive benefits. How do you envision the future of Intuitive Surgical?

Scott Helfstein: You mentioned the importance of robots and while I'm not really a fan of not having a doctor in the room to operate on me, nonetheless, we have seen surgery, number of surgeries have come down during COVID. People are putting things off unless it is really a necessity. I think any ways we can deliver more efficient and safer healthcare outcomes is a pathway to the future and it's something that we should be excited about. When we think about something like surgical robots, there's a phenomenal barrier to entry there. You need to get people trained. They are expensive. It's not exactly the type of thing where a hospital is just going to hop off and go do something else. For a lot of reasons, we think that that's a growth opportunity. It speaks to remote, it speaks to artificial intelligence and automation, and so really encapsulates so much of what we're trying to talk about here.

Go here to see the original:

Has Intuitive Surgical Only Scratched The Surface of Robotics? - Motley Fool

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Welding and Assembly Robotics System Integration Market 2020 Research With Size, Growth, Manufacturers, Segments And 2025 Forecasts Research -...

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Global Collaborative Robotics Market Growth Powered With Latest Development Scenario and Influencing Trends and Forecast 2026 - Murphy's Hockey Law

Milking robots made by DeLaval replaced the human operated milking parlor at Hillcrest Farms in Dearing, Ga., a fourth-generation American family dairy farm owned and operated by Mark Rodgers and his family since 1941. Hillcrest Farms is Georgia's first robotic dairy, but others are being added as technology changes agriculture. (Hyosub Shin / Hyosub.Shin@ajc.com)

Credit: HYOSUB SHIN / AJC

Credit: HYOSUB SHIN / AJC

Agriculture is still Georgias largest industry with an estimated $75 billion impact on the states trillion-dollar economy. And though it still carries a dirt-under-the-fingernails stereotype, those fingers are becoming as used to swiping screens full of data as they are cleaning out a jammed cotton picker.

From autonomous tractors to field-pest analysis provided by drone and in-ground sensors providing moisture content, farming in Georgia is moving well into the 21st century. Technology is critical to keeping folks fed as fewer farmers provide more food and agriculture often a tough business to turn a profit in looks for efficiency. Lt. Gov. Geoff Duncan included high-tech farming as a key element of his economic plan to make Atlanta and Georgia the Silicon Valley of the East.

The Rodgers family knows that as well any. Georgia has lost 40% of its dairy farms in the last decade, according to the Georgia Milk Producers, which points to low milk prices, competition from other drinks and the challenge of finding workers who can milk cows two or three times a day, every day.

Rodgers and his brother, Andy, could have avoided the debt of adding robots to the farm, which is near Augusta, as they near their 60s, and eased into the life of raising beef rather than milking. But Marks daughter Caitlin, 30, and Andys son Joshua, 27, wanted to come home and take over the 850 acres.

Its still a family farm. Thats the beauty of the whole thing, Mark Rodgers said.

The robots, the family hopes, will help a fourth generation to hang on and, hopefully, thrive.

Their Holsteins let themselves into the milking stalls about twice a day. Cows love routines, Rodgers says. And dairy cows get an urge to be relieved of the liquid pressure when their udders are full. On top of that, the stainless steel robotic milkers throw in a treat sweet, high-starch feed when the cows enter the milking chute.

Its kind of like giving a kid candy. They love it, Rodgers said.

Each individual cow can be monitored daily for any changes using artificial intelligence and robotic technology at Hillcrest Farms in Dearing, Ga. Technology is quickly changing how Georgia farmers operate and helping them stay competitive. (Hyosub Shin / Hyosub.Shin@ajc.com)

Credit: HYOSUB SHIN / AJC

Credit: HYOSUB SHIN / AJC

It was a matter of training and repetition taking a cow of average intelligence and good temper about three days to figure out and a few months to perfect.

But it was a little nerve-wracking when the occasional jumpy trainee gave a startled kick while being touched by one of the five expensive robotic milkers.

The technology at Hillcrest is the first in Georgia. At least four other dairies in the state are making the move to robotics. Its more common in Europe, where the technology was perfected.

The local pioneer is attracting attention. Lots of people come for tours, including other farmers. The bejeaned Rodgers says he also gets questions via internet from farmers as far away as New Zealand and Pakistan.

DeLaval of Sweden, the manufacturer of the robotic milkers, promises on its website to make farms more profitable.

Rodgers said DeLaval doesnt want him to say how much the robots cost. But its like buying Porsches and dropping them into a barn.

Luckily Hillcrest Farms can afford the investment. Agriculture Secretary Sonny Perdue, the former Georgia governor, has told farmers that small farms will have to bulk up if they want to survive.

Josh, Andy Rodgers son, got a degree in industrial maintenance and was the one who suggested the family take a look at adding robots to the 79-year-old operation. He maintains the machines and said the start was something of a trial by fire.

Mark Rodgers talked daughter Caitlin into trying something other than farming when she went to college.

Dad told me not to come back. That it was going to be a hard life, she said.

She started in nursing but soon gave it up and followed her heart to an agricultural degree. She manages the herd.

Labor costs is driving this, Mark Rodgers said of the robotics. He cant compete for workers with some of the local manufacturers hourly wages.

Rodgers has reduced staff from about 10 to six. Theres still plenty of work to do: feeding, cleaning, caring for the herd, birthing calves, growing corn and other fodder for feed. The robotics lets them focus on the cows rather than the daily churn of milkings.

The DeLaval robotic arm detaches from a cow's udder at Georgia's first robotic dairy, Hillcrest Farms in Dearing Georgia. The family farm invested in five robotic milkers to stay efficient in the hyper-competitive dairy business. (Hyosub Shin / Hyosub.Shin@ajc.com)

Credit: HYOSUB SHIN / AJC

Credit: HYOSUB SHIN / AJC

As Rodgers talked in front of one robotic milker, a steady stream of Holsteins let themselves into the chute. They can do that 24/7. After moveable gates backed the cows into perfect position, a low-slung silver arm holding the milking cups and a spray-and-wash unit for the udders carefully moved into place beneath the cow, guided by a camera and artificial intelligence that can recognize teats and seat the milking cups.

An iPad-sized screen lights up with information about the cow and, ounce by ounce, production in real time.

The machine already knows more about the cow than Rodgers could ever memorize, down to how much milk each teat has given in the last 10 months and how much the cow moved in the last 24 hours, thanks to a bovine equivalent of a Fitbit around its neck. He has more data stacked up on the farms cows than he knows what to do with, all accessible on a computer screen or iPhone.

The decision to make the investment was about making things more efficient, making a profit and making the cows happy, Rodgers said.

He thinks they like the process better than human-controlled milking.

Mark Rodgers shows how each of the farms hundreds of cows are individually monitored 24 hours a day. Artificial intelligence can tip the Rodgers family off to health, from sickness to when a cow is ready to breed. (Hyosub Shin / Hyosub.Shin@ajc.com)

Credit: HYOSUB SHIN / AJC

Credit: HYOSUB SHIN / AJC

You want to be leave them alone and let cows be cows. That is the beauty of the system, we are not forcing them to do anything, he said.

A relaxed cow is a good milker. An average Holstein gives about 11 gallons a day. His best girl gives about 24. Production is down a little this year as the cows continue to get used to the process.

Rodgers thinks that will go back up over time as the cows settle in and he culls those now carefully monitored Holsteins and keeps the ones that do well. Those that dont are still marketable as meat.

Hell be happy to ease into the life of a gentleman farmer and watch the robots and the children take more of the responsibility.

Ill never see the benefit of all this, he said of the investment. But they will.

Read more from the original source:

Tended by robots, milk cows mooove into life of luxury - Atlanta Journal Constitution

Warehouse features more than 60 GreyMatter-directed robots working alongside employees.

GreyOrange today announced that its GreyMatter operating system and Ranger MoveSmart robots have been implemented in Active Ants' new e-fulfillment center in Roosendaal, The Netherlands. The 20,000 square meter warehouse features the GreyMatter Smart Zone Transfer application, utilizing Ranger MoveSmart robots to autonomously move and sort inventory in flexible process flows not possible with fixed conveyors or sorters.

Active Ants provides warehousing services to various e-commerce companies in Belgium, The Netherlands and Germany with the goal of raising the efficiency and accuracy of e-fulfillment through innovation, automation and the deployment of robots. The Dutch e-fulfillment company stores, packs and distributes goods for more than 250 customers and more than 3 million orders annually.

At the Roosendaal e-fulfillment center, Smart Zone Transfer happens autonomously as GreyMatter software orchestrates the complete process flow as Ranger MoveSmart robots convey inventory to various workstations. The process begins as Ranger robots take empty boxes to employees who fill them with goods brought by other robots. Next, Ranger robots transport the filled boxes to packaging machines where they are sealed and weighed. Then, Ranger robots collect the packages and sort them to the correct zones for shipping directly to customers.

Process flows executed by Ranger robots can be altered as needed through simple changes in GreyMatter's intuitive Command Center interface. With traditional conveyor systems and most existing software platforms, this type of change would typically take months of customized solutioning and implementation.

"No matter what I need to do with zone transfer, I can alter the process flow in GreyMatter even though I'm not a programmer," said Dekker. "This level of flexibility allows us to meet our current needs while also having the ability to quickly make changes. We can easily modify the robot movements if needed as well as scale up the solution in line with our throughput growth to smartly manage capital investment."

"Fast-growing companies require automation that equips them to easily adapt their fulfillment processes as market dynamics change," said Akash Gupta, cofounder and chief technology officer for GreyOrange. "They don't want to be constricted by fixed infrastructure that locks them into process flows for 10 to15 years. The power to quickly adapt is what gives retailers an edge in today's world, and it's a foundational design principle of our GreyMatter Fulfillment Operating System and family of Ranger robots. We're pleased to deliver this unmatched innovation and versatility to Active Ants as part of their goal of delivering exceptional service to their customers," Gupta added.

Unlike fixed infrastructure that is difficult or impossible to reconfigure, Ranger MoveSmart autonomous mobile robots perform with complete flexibility. Through orchestrated integration with GreyMatter, Ranger MoveSmart can convey, move or sort anywhere in the DC and provide rapid response to changing processes and accelerated throughput.

The e-fulfillment partnership between Active Ants and GreyOrange will be highlighted in a webinar "Free from Fixed: Why Moving from Rigid to Flexible Systems is the Go-To Answer to Fulfilling Today's Immediate Commerce" to be held on Dec. 9, 2020 at 9:30 AM ET.

Attendees will hear from Jean Lahaye, Active Ants Managing Partner, and Nigel Lahiri, GreyOrange EMEA Sales Director, about how they applied innovative thinking, AI and robotics to solve current and future fulfillment challenges. To register, visit:

https://greyorange.zoom.us/webinar/register/9216061516484/WN_M2VGOjhcTTexBZpKldnf9Q

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GreyOrange Deploys Smart Zone Transfer Capabilities within Active Ants e-Fulfillment Warehouse in The Netherlands - Robotics Tomorrow