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#431343 How Technology Is Driving Us Toward Peak ...

At some point in the future—and in some ways we are already seeing this—the amount of physical stuff moving around the world will peak and begin to decline. By “stuff,” I am referring to liquid fuels, coal, containers on ships, food, raw materials, products, etc.
New technologies are moving us toward “production-at-the-point-of-consumption” of energy, food, and products with reduced reliance on a global supply chain.
The trade of physical stuff has been central to globalization as we’ve known it. So, this declining movement of stuff may signal we are approaching “peak globalization.”
To be clear, even as the movement of stuff may slow, if not decline, the movement of people, information, data, and ideas around the world is growing exponentially and is likely to continue doing so for the foreseeable future.
Peak globalization may provide a pathway to preserving the best of globalization and global interconnectedness, enhancing economic and environmental sustainability, and empowering individuals and communities to strengthen democracy.
At the same time, some of the most troublesome aspects of globalization may be eased, including massive financial transfers to energy producers and loss of jobs to manufacturing platforms like China. This shift could bring relief to the “losers” of globalization and ease populist, nationalist political pressures that are roiling the developed countries.
That is quite a claim, I realize. But let me explain the vision.
New Technologies and Businesses: Digital, Democratized, Decentralized
The key factors moving us toward peak globalization and making it economically viable are new technologies and innovative businesses and business models allowing for “production-at-the-point-of-consumption” of energy, food, and products.
Exponential technologies are enabling these trends by sharply reducing the “cost of entry” for creating businesses. Driven by Moore’s Law, powerful technologies have become available to almost anyone, anywhere.
Beginning with the microchip, which has had a 100-billion-fold improvement in 40 years—10,000 times faster and 10 million times cheaper—the marginal cost of producing almost everything that can be digitized has fallen toward zero.
A hard copy of a book, for example, will always entail the cost of materials, printing, shipping, etc., even if the marginal cost falls as more copies are produced. But the marginal cost of a second digital copy, such as an e-book, streaming video, or song, is nearly zero as it is simply a digital file sent over the Internet, the world’s largest copy machine.* Books are one product, but there are literally hundreds of thousands of dollars in once-physical, separate products jammed into our devices at little to no cost.
A smartphone alone provides half the human population access to artificial intelligence—from SIRI, search, and translation to cloud computing—geolocation, free global video calls, digital photography and free uploads to social network sites, free access to global knowledge, a million apps for a huge variety of purposes, and many other capabilities that were unavailable to most people only a few years ago.
As powerful as dematerialization and demonetization are for private individuals, they’re having a stronger effect on businesses. A small team can access expensive, advanced tools that before were only available to the biggest organizations. Foundational digital platforms, such as the internet and GPS, and the platforms built on top of them by the likes of Google, Apple, Amazon, and others provide the connectivity and services democratizing business tools and driving the next generation of new startups.

“As these trends gain steam in coming decades, they’ll bleed into and fundamentally transform global supply chains.”

An AI startup, for example, doesn’t need its own server farm to train its software and provide service to customers. The team can rent computing power from Amazon Web Services. This platform model enables small teams to do big things on the cheap. And it isn’t just in software. Similar trends are happening in hardware too. Makers can 3D print or mill industrial grade prototypes of physical stuff in a garage or local maker space and send or sell designs to anyone with a laptop and 3D printer via online platforms.
These are early examples of trends that are likely to gain steam in coming decades, and as they do, they’ll bleed into and fundamentally transform global supply chains.
The old model is a series of large, connected bits of centralized infrastructure. It makes sense to mine, farm, or manufacture in bulk when the conditions, resources, machines, and expertise to do so exist in particular places and are specialized and expensive. The new model, however, enables smaller-scale production that is local and decentralized.
To see this more clearly, let’s take a look at the technological trends at work in the three biggest contributors to the global trade of physical stuff—products, energy, and food.
Products
3D printing (additive manufacturing) allows for distributed manufacturing near the point of consumption, eliminating or reducing supply chains and factory production lines.
This is possible because product designs are no longer made manifest in assembly line parts like molds or specialized mechanical tools. Rather, designs are digital and can be called up at will to guide printers. Every time a 3D printer prints, it can print a different item, so no assembly line needs to be set up for every different product. 3D printers can also print an entire finished product in one piece or reduce the number of parts of larger products, such as engines. This further lessens the need for assembly.
Because each item can be customized and printed on demand, there is no cost benefit from scaling production. No inventories. No shipping items across oceans. No carbon emissions transporting not only the final product but also all the parts in that product shipped from suppliers to manufacturer. Moreover, 3D printing builds items layer by layer with almost no waste, unlike “subtractive manufacturing” in which an item is carved out of a piece of metal, and much or even most of the material can be waste.
Finally, 3D printing is also highly scalable, from inexpensive 3D printers (several hundred dollars) for home and school use to increasingly capable and expensive printers for industrial production. There are also 3D printers being developed for printing buildings, including houses and office buildings, and other infrastructure.
The technology for finished products is only now getting underway, and there are still challenges to overcome, such as speed, quality, and range of materials. But as methods and materials advance, it will likely creep into more manufactured goods.
Ultimately, 3D printing will be a general purpose technology that involves many different types of printers and materials—such as plastics, metals, and even human cells—to produce a huge range of items, from human tissue and potentially human organs to household items and a range of industrial items for planes, trains, and automobiles.
Energy
Renewable energy production is located at or relatively near the source of consumption.
Although electricity generated by solar, wind, geothermal, and other renewable sources can of course be transmitted over longer distances, it is mostly generated and consumed locally or regionally. It is not transported around the world in tankers, ships, and pipelines like petroleum, coal, and natural gas.
Moreover, the fuel itself is free—forever. There is no global price on sun or wind. The people relying on solar and wind power need not worry about price volatility and potential disruption of fuel supplies as a result of political, market, or natural causes.
Renewables have their problems, of course, including intermittency and storage, and currently they work best if complementary to other sources, especially natural gas power plants that, unlike coal plants, can be turned on or off and modulated like a gas stove, and are half the carbon emissions of coal.
Within the next decades or so, it is likely the intermittency and storage problems will be solved or greatly mitigated. In addition, unlike coal and natural gas power plants, solar is scalable, from solar panels on individual homes or even cars and other devices, to large-scale solar farms. Solar can be connected with microgrids and even allow for autonomous electricity generation by homes, commercial buildings, and communities.
It may be several decades before fossil fuel power plants can be phased out, but the development cost of renewables has been falling exponentially and, in places, is beginning to compete with coal and gas. Solar especially is expected to continue to increase in efficiency and decline in cost.
Given these trends in cost and efficiency, renewables should become obviously cheaper over time—if the fuel is free for solar and has to be continually purchased for coal and gas, at some point the former is cheaper than the latter. Renewables are already cheaper if externalities such as carbon emissions and environmental degradation involved in obtaining and transporting the fuel are included.
Food
Food can be increasingly produced near the point of consumption with vertical farms and eventually with printed food and even printed or cultured meat.
These sources bring production of food very near the consumer, so transportation costs, which can be a significant portion of the cost of food to consumers, are greatly reduced. The use of land and water are reduced by 95% or more, and energy use is cut by nearly 50%. In addition, fertilizers and pesticides are not required and crops can be grown 365 days a year whatever the weather and in more climates and latitudes than is possible today.
While it may not be practical to grow grains, corn, and other such crops in vertical farms, many vegetables and fruits can flourish in such facilities. In addition, cultured or printed meat is being developed—the big challenge is scaling up and reducing cost—that is based on cells from real animals without slaughtering the animals themselves.
There are currently some 70 billion animals being raised for food around the world [PDF] and livestock alone counts for about 15% of global emissions. Moreover, livestock places huge demands on land, water, and energy. Like vertical farms, cultured or printed meat could be produced with no more land use than a brewery and with far less water and energy.
A More Democratic Economy Goes Bottom Up
This is a very brief introduction to the technologies that can bring “production-at-the-point-of-consumption” of products, energy, and food to cities and regions.
What does this future look like? Here’s a simplified example.
Imagine a universal manufacturing facility with hundreds of 3D printers printing tens of thousands of different products on demand for the local community—rather than assembly lines in China making tens of thousands of the same product that have to be shipped all over the world since no local market can absorb all of the same product.
Nearby, a vertical farm and cultured meat facility produce much of tomorrow night’s dinner. These facilities would be powered by local or regional wind and solar. Depending on need and quality, some infrastructure and machinery, like solar panels and 3D printers, would live in these facilities and some in homes and businesses.
The facilities could be owned by a large global corporation—but still locally produce goods—or they could be franchised or even owned and operated independently by the local population. Upkeep and management at each would provide jobs for communities nearby. Eventually, not only would global trade of parts and products diminish, but even required supplies of raw materials and feed stock would decline since there would be less waste in production, and many materials would be recycled once acquired.

“Peak globalization could be a viable pathway to an economic foundation that puts people first while building a more economically and environmentally sustainable future.”

This model suggests a shift toward a “bottom up” economy that is more democratic, locally controlled, and likely to generate more local jobs.
The global trends in democratization of technology make the vision technologically plausible. Much of this technology already exists and is improving and scaling while exponentially decreasing in cost to become available to almost anyone, anywhere.
This includes not only access to key technologies, but also to education through digital platforms available globally. Online courses are available for free, ranging from advanced physics, math, and engineering to skills training in 3D printing, solar installations, and building vertical farms. Social media platforms can enable local and global collaboration and sharing of knowledge and best practices.
These new communities of producers can be the foundation for new forms of democratic governance as they recognize and “capitalize” on the reality that control of the means of production can translate to political power. More jobs and local control could weaken populist, anti-globalization political forces as people recognize they could benefit from the positive aspects of globalization and international cooperation and connectedness while diminishing the impact of globalization’s downsides.
There are powerful vested interests that stand to lose in such a global structural shift. But this vision builds on trends that are already underway and are gaining momentum. Peak globalization could be a viable pathway to an economic foundation that puts people first while building a more economically and environmentally sustainable future.
This article was originally posted on Open Democracy (CC BY-NC 4.0). The version above was edited with the author for length and includes additions. Read the original article on Open Democracy.
* See Jeremy Rifkin, The Zero Marginal Cost Society, (New York: Palgrave Macmillan, 2014), Part II, pp. 69-154.
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#431155 What It Will Take for Quantum Computers ...

Quantum computers could give the machine learning algorithms at the heart of modern artificial intelligence a dramatic speed up, but how far off are we? An international group of researchers has outlined the barriers that still need to be overcome.
This year has seen a surge of interest in quantum computing, driven in part by Google’s announcement that it will demonstrate “quantum supremacy” by the end of 2017. That means solving a problem beyond the capabilities of normal computers, which the company predicts will take 49 qubits—the quantum computing equivalent of bits.
As impressive as such a feat would be, the demonstration is likely to be on an esoteric problem that stacks the odds heavily in the quantum processor’s favor, and getting quantum computers to carry out practically useful calculations will take a lot more work.
But these devices hold great promise for solving problems in fields as diverse as cryptography or weather forecasting. One application people are particularly excited about is whether they could be used to supercharge the machine learning algorithms already transforming the modern world.
The potential is summarized in a recent review paper in the journal Nature written by a group of experts from the emerging field of quantum machine learning.
“Classical machine learning methods such as deep neural networks frequently have the feature that they can both recognize statistical patterns in data and produce data that possess the same statistical patterns: they recognize the patterns that they produce,” they write.
“This observation suggests the following hope. If small quantum information processors can produce statistical patterns that are computationally difficult for a classical computer to produce, then perhaps they can also recognize patterns that are equally difficult to recognize classically.”
Because of the way quantum computers work—taking advantage of strange quantum mechanical effects like entanglement and superposition—algorithms running on them should in principle be able to solve problems much faster than the best known classical algorithms, a phenomenon known as quantum speedup.
Designing these algorithms is tricky work, but the authors of the review note that there has been significant progress in recent years. They highlight multiple quantum algorithms exhibiting quantum speedup that could act as subroutines, or building blocks, for quantum machine learning programs.
We still don’t have the hardware to implement these algorithms, but according to the researchers the challenge is a technical one and clear paths to overcoming them exist. More challenging, they say, are four fundamental conceptual problems that could limit the applicability of quantum machine learning.
The first two are the input and output problems. Quantum computers, unsurprisingly, deal with quantum data, but the majority of the problems humans want to solve relate to the classical world. Translating significant amounts of classical data into the quantum systems can take so much time it can cancel out the benefits of the faster processing speeds, and the same is true of reading out the solution at the end.
The input problem could be mitigated to some extent by the development of quantum random access memory (qRAM)—the equivalent to RAM in a conventional computer used to provide the machine with quick access to its working memory. A qRAM can be configured to store classical data but allow the quantum computers to access all that information simultaneously as a superposition, which is required for a variety of quantum algorithms. But the authors note this is still a considerable engineering challenge and may not be sustainable for big data problems.
Closely related to the input/output problem is the costing problem. At present, the authors say very little is known about how many gates—or operations—a quantum machine learning algorithm will require to solve a given problem when operated on real-world devices. It’s expected that on highly complex problems they will offer considerable improvements over classical computers, but it’s not clear how big problems have to be before this becomes apparent.
Finally, whether or when these advantages kick in may be hard to prove, something the authors call the benchmarking problem. Claiming that a quantum algorithm can outperform any classical machine learning approach requires extensive testing against these other techniques that may not be feasible.
They suggest that this could be sidestepped by lowering the standards quantum machine learning algorithms are currently held to. This makes sense, as it doesn’t really matter whether an algorithm is intrinsically faster than all possible classical ones, as long as it’s faster than all the existing ones.
Another way of avoiding some of these problems is to apply these techniques directly to quantum data, the actual states generated by quantum systems and processes. The authors say this is probably the most promising near-term application for quantum machine learning and has the added benefit that any insights can be fed back into the design of better hardware.
“This would enable a virtuous cycle of innovation similar to that which occurred in classical computing, wherein each generation of processors is then leveraged to design the next-generation processors,” they conclude.
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#430649 Robotherapy for children with autism

New Robotherapy for children with autism could reduce patient supervision by therapists.
05.07.2017
Autism treatments and therapies routinely make headlines. With robot enhanced therapies on the rise, often overlooked though, is the mental stress and physical toll the procedures take on therapists. As autism treatments can be taxing on both patient and therapists, few realize the stress and workload of those working with autistic patients.
It is against this backdrop, that researchers from the Vrije Universiteit Brussel are pioneering a new technology to aid behavioural therapy, and one with a very deliberate aspect: they are using robots to boost the basic social learning skills of children with ASD and while doing so, they hope to make the therapists’ job substantially easier.
A study, just published in PALADYN – Journal of Behavioural Robotics examines the use of social robots as tools in clinical situations by addressing the challenge of increasing robot autonomy.
The growing deployment of robot-assisted therapies in recent decades means children with Autism Spectrum Disorder (ASD) can develop and nurture social behaviour and cognitive skills. Learning skills that hold out in real life is the first and foremost goal of all autism therapies, including the Robot-Assisted Therapy (RAT), with effectiveness always considered a key concern. However, this time round the scientists have set off on the additional mission to take the load off the human therapists by letting parts of the intervention be taken over by the supervised yet autonomous robots.
The researchers developed a complete system of robot-enhanced therapy (RET) for children with ASD. The therapy works by teaching behaviours during repeated sessions of interactive games. Since the individuals with ASD tend to be more responsive to feedback coming from an interaction with technology, robots are often used for this therapy. In this approach, the social robot acts as a mediator and typically remains remote-controlled by a human operator. The technique, called Wizard of Oz, requires the robot to be operated by an additional person and the robot is not recording the performance during the therapy. In order to reduce operator workload, authors introduced a system with a supervised autonomous robot – which is able to understand the psychological disposition of the child and use it to select actions appropriate to the current state of the interaction.
Admittedly, robots with supervised autonomy can substantially benefit behavioural therapy for children with ASD – diminishing the therapist workload on the one hand, and achieving more objective measurements of therapy outcomes on the other. Yet, complex as it is, this therapy requires a multidisciplinary approach, as RET provides mixed effectiveness for primary tasks: the turn-taking, joint attention and imitation task comparing to Standard Human Treatment (SHT).
Results are likely to prompt a further development of the robot assisted therapy with increasing robot’s autonomy. With many outstanding conceptual and technical issues yet to tackle –it is definitely the ethical questions that pose one of the major challenges as far as the potential and maximal degree of robot autonomy is concerned.
The article is fully available in open access to read, download and share on De Gruyter Online.
Research was conducted as a part of DREAM (Development of Robot-Enhanced therapy for children with Autism spectrum disorders) project.
DOI: 10.1515/pjbr-2017-0002
Image credit: P.G. Esteban
About the Journal: PALADYN – Journal of Behavioural Robotics is a fully peer-reviewed, electronic-only journal that publishes original, high-quality research on topics broadly related to neuronally and psychologically inspired robots and other behaving autonomous systems.
About De Gruyter Open: De Gruyter Open is a leading publisher of Open Access academic content. Publishing in all major disciplines, De Gruyter Open is home to more than 500 scholarly journals and over 100 books. The company is part of the De Gruyter Group (www.degruyter.com) and a member of the Association of Learned and Professional Society Publishers (ALPSP). De Gruyter Open’s book and journal programs have been endorsed by the international research community and some of the world’s top scientists, including Nobel laureates. The company’s mission is to make the very best in academic content freely available to scholars and lay readers alike.
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#428367 Fusion for Energy signs multi-million ...

Fusion for Energy signs multi-million deal with Airbus Safran Launchers, Nuvia Limited and Cegelec CEM to develop robotics equipment for ITER
The contract for a value of nearly 100 million EUR is considered to be the single biggest robotics deal to date in the field of fusion energy. The state of the art equipment will form part of ITER, the world’s largest experimental fusion facility and the first in history to produce 500 MW. The prestigious project brings together seven parties (China, Europe, Japan, India, the Republic of Korea, the Russian Federation and the USA) which represent 50% of the world’s population and 80% of the global GDP.
The collaboration between Fusion for Energy (F4E), the EU organisation managing Europe’s contribution to ITER, with a consortium of companies consisting of Airbus Safran Launchers (France-Germany), Nuvia Limited (UK) and Cegelec CEM (France), companies of the VINCI Group, will run for a period of seven years. The UK Atomic Energy Authority (UK), Instituto Superior Tecnico (Portugal), AVT Europe NV (Belgium) and Millennium (France) will also be part of this deal which will deliver remotely operated systems for the transportation and confinement of components located in the ITER vacuum vessel.
The contract carries also a symbolic importance marking the signature all procurement packages managed by Europe in the field of remote handling. Carlo Damiani, F4E’s Project Manager for ITER Remote Handling Systems, explained that “F4E’s stake in ITER offers an unparalleled opportunity to companies and laboratories to develop expertise and an industrial culture in fusion reactors’ maintenance.”
Cut-away image of the ITER machine showing the casks at the three levels of the ITER machine. ITER IO © (Remote1 web). Photo Credit: f4e.europa.euIllustration of lorry next to an ITER cask. F4E © (Remote 2 web). Photo Credit: f4e.europa.euAerial view of the ITER construction site, October 2016. F4E © (ITER site aerial Oct). Photo Credit: f4e.europa.eu

Why ITER requires Remote Handling?
Remote handling refers to the high-tech systems that will help us maintain and repair the ITER machine. The space where the bulky equipment will operate is limited and the exposure of some of the components to radioactivity, prohibit any manual intervention inside the vacuum vessel.

What will be delivered through this contract?
The transfer of components from the ITER vacuum vessel to the Hot Cell building, where they will be deposited for maintenance, will need to be carried out with the help of massive double-door containers known as casks. According to current estimates, 15 of these casks will need to be manufactured and in their largest configuration they will measure 8.5 m x 3.7 m x 2.6 m approaching 100 tonnes when transporting the heaviest components. These enormous “boxes”, resembling to a conventional lorry container, will be remotely operated as they move between the different levels and buildings of the machine. Apart from the transportation and confinement of components, the ITER Cask and Plug Remote Handling System will also ensure the installation of the remote handling equipment entering into the vacuum vessel to pick up the components to be removed. The technologies underpinning this system will encompass a variety of high-tech skills and comply with nuclear safety requirements. A proven manufacturing experience in similar fields and the development of bespoke systems to perform mechanical transfers will be essential.

Background information
MEMO: Fusion for Energy signs multi-million deal with Airbus Safran Launchers, Nuvia Limited and Cegelec CEM to develop robotics equipment for ITER
Multimedia
To see how the ITER Remote Handling System will operate click on clip 1 and clip 2
To see the progress of the ITER construction site click here
To take a virtual tour on the ITER construction site click here

Image captions
Cut-away image of the ITER machine showing the casks at the three levels of the ITER machine. ITER IO © (Remote1 web)

Illustration of lorry next to an ITER cask. F4E © (Remote 2 web)

Aerial view of the ITER construction site, October 2016. F4E © (ITER site aerial Oct)

The consortium of companies
The consortium combines the space expertise of Airbus Safran Launchers, adapted to this extreme environment to ensure safe conditions for the ITER teams; with Nuvia comes a wealth of nuclear experience dating back to the beginnings of the UK Nuclear industry. Nuvia has delivered solutions to some of the world’s most complex nuclear challenges; and with Cegelec CEM as a specialist in mechanical projects for French nuclear sector, which contributes over 30 years in the nuclear arena, including turnkey projects for large scientific installations, as well as the realisation of complex mechanical systems.

Fusion for Energy
Fusion for Energy (F4E) is the European Union’s organisation for Europe’s contribution to ITER.
One of the main tasks of F4E is to work together with European industry, SMEs and research organisations to develop and provide a wide range of high technology components together with engineering, maintenance and support services for the ITER project.
F4E supports fusion R&D initiatives through the Broader Approach Agreement signed with Japan and prepares for the construction of demonstration fusion reactors (DEMO).
F4E was created by a decision of the Council of the European Union as an independent legal entity and was established in April 2007 for a period of 35 years.
Its offices are in Barcelona, Spain.
http://www.fusionforenergy.europa.eu
http://www.youtube.com/user/fusionforenergy
http://twitter.com/fusionforenergy
http://www.flickr.com/photos/fusionforenergy

ITER
ITER is a first-of-a-kind global collaboration. It will be the world’s largest experimental fusion facility and is designed to demonstrate the scientific and technological feasibility of fusion power. It is expected to produce a significant amount of fusion power (500 MW) for about seven minutes. Fusion is the process which powers the sun and the stars. When light atomic nuclei fuse together form heavier ones, a large amount of energy is released. Fusion research is aimed at developing a safe, limitless and environmentally responsible energy source.
Europe will contribute almost half of the costs of its construction, while the other six parties to this joint international venture (China, Japan, India, the Republic of Korea, the Russian Federation and the USA), will contribute equally to the rest.
The site of the ITER project is in Cadarache, in the South of France.
http://www.iter.org

For Fusion for Energy media enquiries contact:
Aris Apollonatos
E-mail: aris.apollonatos@f4e.europa.eu
Tel: + 34 93 3201833 + 34 649 179 42
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#428040 Servosila Robotic Arms launched

Servosila, a robotics technology company, announced a launch of a new line of robotic arm manipulators specifically targeted at mobile robotics market.
“Servosila Robotic Arms are the first manipulators specifically designed for mobile robots,” – said the company’s spokesperson, – “it is very easy to retrofit any existing robotic chassis or a torso with a Servosila Robotic Arm”.

Servosila Robotic Arms are attachable payload modules for mobile service robots or other robotic platforms. Servosila Robotic Arms shall typically be mounted on a chassis or a torso of a mobile robot and be powered by an on-board power supply system of the host robotic platform.
The robotic arms can be used both outdoors and indoors. The arms are water-tight, dust-proof and function properly in the rain and in the snow. The arms are designed to withstand impacts, collisions with obstacles and, in general, the harsh treatment so common to mobile robotics applications.
The servo drives and external electrical connectors of the robotic arms are water-tight and dust-proof (IP68 rating). The entire arm can be occasionally submersed in water without any adverse effects on its performance. The robotic arms may be operated in cold or hot weather.
Mobile robots tend to bump into things and hit obstacles while on the move. The harsh nature of outdoor mobile robotics applications caused a profound effect on the design of Servosila Robotic Arms, especially on the internal structure of servo drives and their harmonic reduction gears.
There are no exposed cables on the outside of the robotic arms that could be torn off when a mobile robot moves through bushes or forests.
Numerous protection measures built into electronic servo controllers and mechanical parts of Servosila Robotic Arms ensure reliable operation on-board of outdoor mobile service robots.

Servosila Robotic Arms are lightweight by design. For a given lifting capability, Servosila Robotic Arms have a significantly lower weight than their industrial counterparts. The lower weight of a Servosila Robotic Arm enables a mobile robot equipped with the arm to operate longer on a single battery charge, keep its center of gravity lower for better balance, climb stairs easier or have a superior mobility.

When not in an active use, Servosila Robotic Arms can folded into a very compact form that doesn’t occupy much space on the top of a robotic chassis or on the side of a torso. This feature protects the robotic arm of a mobile robot in case of an unexpected collision with an obstacle or whenever a rough terrain is encountered by the mobile robotic platform. The compact folded form also comes handy during transportation.

By folding its robotic arm into the compact form, the robot frees up its working area for other payloads to operate in. This is useful in case the robot is equipped with additional payloads other than the robotic arm.
www.servosila.com/en/robotic-arms
Photo Credits: Servosila Limited (Hong Kong)
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