Tag Archives: systems

#431315 Better Than Smart Speakers? Japan Is ...

While American internet giants are developing speakers, Japanese companies are working on robots and holograms. They all share a common goal: to create the future platform for the Internet of Things (IoT) and smart homes.
Names like Bocco, EMIEW3, Xperia Assistant, and Gatebox may not ring a bell to most outside of Japan, but Sony, Hitachi, Sharp, and Softbank most certainly do. The companies, along with Japanese start-ups, have developed robots, robot concepts, and even holograms like the ones hiding behind the short list of names.
While there are distinct differences between the various systems, they share the potential to act as a remote control for IoT devices and smart homes. It is a very different direction than that taken by companies like Google, Amazon, and Apple, who have so far focused on building IoT speaker systems.
Bocco robot. Image Credit: Yukai Engineering
“Technology companies are pursuing the platform—or smartphone if you will—for IoT. My impression is that Japanese companies—and Japanese consumers—prefer that such a platform should not just be an object, but a companion,” says Kosuke Tatsumi, designer at Yukai Engineering, a startup that has developed the Bocco robot system.
At Hitachi, a spokesperson said that the company’s human symbiotic service robot, EMIEW3, robot is currently in the field, doing proof-of-value tests at customer sites to investigate needs and potential solutions. This could include working as an interactive control system for the Internet of Things:
“EMIEW3 is able to communicate with humans, thus receive instructions, and as it is connected to a robotics IT platform, it is very much capable of interacting with IoT-based systems,” the spokesperson said.
The power of speech is getting feet
Gartner analysis predicts that there will be 8.4 billion internet-connected devices—collectively making up the Internet of Things—by the end of 2017. 5.2 billion of those devices are in the consumer category. By the end of 2020, the number of IoT devices will rise to 12.8 billion—and that is just in the consumer category.
As a child of the 80s, I can vividly remember how fun it was to have separate remote controls for TV, video, and stereo. I can imagine a situation where my internet-connected refrigerator and ditto thermostat, television, and toaster try to work out who I’m talking to and what I want them to do.
Consensus seems to be that speech will be the way to interact with many/most IoT devices. The same goes for a form of virtual assistant functioning as the IoT platform—or remote control. Almost everything else is still an open ballgame, despite an early surge for speaker-based systems, like those from Amazon, Google, and Apple.
Why robots could rule
Famous android creator and robot scientist Dr. Hiroshi Ishiguro sees the interaction between humans and the AI embedded in speakers or robots as central to both approaches. From there, the approaches differ greatly.
Image Credit: Hiroshi Ishiguro Laboratories
“It is about more than the difference of form. Speaking to an Amazon Echo is not a natural kind of interaction for humans. That is part of what we in Japan are creating in many human-like robot systems,” he says. “The human brain is constructed to recognize and interact with humans. This is part of why it makes sense to focus on developing the body for the AI mind as well as the AI mind itself. In a way, you can describe it as the difference between developing an assistant, which could be said to be what many American companies are currently doing, and a companion, which is more the focus here in Japan.”
Another advantage is that robots are more kawaii—a multifaceted Japanese word that can be translated as “cute”—than speakers are. This makes it easy for people to relate to them and forgive them.
“People are more willing to forgive children when they make mistakes, and the same is true with a robot like Bocco, which is designed to look kawaii and childlike,” Kosuke Tatsumi explains.
Japanese robots and holograms with IoT-control capabilities
So, what exactly do these robot and hologram companions look like, what can they do, and who’s making them? Here are seven examples of Japanese companies working to go a step beyond smart speakers with personable robots and holograms.
1. In 2016 Sony’s mobile division demonstrated the Xperia Agent concept robot that recognizes individual users, is voice controlled, and can do things like control your television and receive calls from services like Skype.

2. Sharp launched their Home Assistant at CES 2016. A robot-like, voice-controlled assistant that can to control, among other things, air conditioning units, and televisions. Sharp has also launched a robotic phone called RoBoHon.
3. Gatebox has created a holographic virtual assistant. Evil tongues will say that it is primarily the expression of an otaku (Japanese for nerd) dream of living with a manga heroine. Gatebox is, however, able to control things like lights, TVs, and other systems through API integration. It also provides its owner with weather-related advice like “remember your umbrella, it looks like it will rain later.” Gatebox can be controlled by voice, gesture, or via an app.
4. Hitachi’s EMIEW3 robot is designed to assist people in businesses and public spaces. It is connected to a robot IT-platform via the cloud that acts as a “remote brain.” Hitachi is currently investigating the business use cases for EMIEW3. This could include the role of controlling platform for IoT devices.

5. Softbank’s Pepper robot has been used as a platform to control use of medical IoT devices such as smart thermometers by Avatarion. The company has also developed various in-house systems that enable Pepper to control IoT-devices like a coffee machine. A user simply asks Pepper to brew a cup of coffee, and it starts the coffee machine for you.
6. Yukai Engineering’s Bocco registers when a person (e.g., young child) comes home and acts as a communication center between that person and other members of the household (e.g., parent still at work). The company is working on integrating voice recognition, voice control, and having Bocco control things like the lights and other connected IoT devices.
7. Last year Toyota launched the Kirobo Mini, a companion robot which aims to, among other things, help its owner by suggesting “places to visit, routes for travel, and music to listen to” during the drive.

Today, Japan. Tomorrow…?
One of the key questions is whether this emerging phenomenon is a purely Japanese thing. If the country’s love of robots makes it fundamentally different. Japan is, after all, a country where new units of Softbank’s Pepper robot routinely sell out in minutes and the RoBoHon robot-phone has its own cafe nights in Tokyo.
It is a country where TV introduces you to friendly, helpful robots like Doraemon and Astro Boy. I, on the other hand, first met robots in the shape of Arnold Schwarzenegger’s Terminator and struggled to work out why robots seemed intent on permanently borrowing things like clothes and motorcycles, not to mention why they hated people called Sarah.
However, research suggests that a big part of the reason why Japanese seem to like robots is a combination of exposure and positive experiences that leads to greater acceptance of them. As robots spread to more and more industries—and into our homes—our acceptance of them will grow.
The argument is also backed by a project by Avatarion, which used Softbank’s Nao-robot as a classroom representative for children who were in the hospital.
“What we found was that the other children quickly adapted to interacting with the robot and treating it as the physical representation of the child who was in hospital. They accepted it very quickly,” Thierry Perronnet, General Manager of Avatarion, explains.
His company has also developed solutions where Softbank’s Pepper robot is used as an in-home nurse and controls various medical IoT devices.
If robots end up becoming our preferred method for controlling IoT devices, it is by no means certain that said robots will be coming from Japan.
“I think that the goal for both Japanese and American companies—including the likes of Google, Amazon, Microsoft, and Apple—is to create human-like interaction. For this to happen, technology needs to evolve and adapt to us and how we are used to interacting with others, in other words, have a more human form. Humans’ speed of evolution cannot keep up with technology’s, so it must be the technology that changes,” Dr. Ishiguro says.
Image Credit: Sony Mobile Communications Continue reading

Posted in Human Robots

#431238 AI Is Easy to Fool—Why That Needs to ...

Con artistry is one of the world’s oldest and most innovative professions, and it may soon have a new target. Research suggests artificial intelligence may be uniquely susceptible to tricksters, and as its influence in the modern world grows, attacks against it are likely to become more common.
The root of the problem lies in the fact that artificial intelligence algorithms learn about the world in very different ways than people do, and so slight tweaks to the data fed into these algorithms can throw them off completely while remaining imperceptible to humans.
Much of the research into this area has been conducted on image recognition systems, in particular those relying on deep learning neural networks. These systems are trained by showing them thousands of examples of images of a particular object until they can extract common features that allow them to accurately spot the object in new images.
But the features they extract are not necessarily the same high-level features a human would be looking for, like the word STOP on a sign or a tail on a dog. These systems analyze images at the individual pixel level to detect patterns shared between examples. These patterns can be obscure combinations of pixel values, in small pockets or spread across the image, that would be impossible to discern for a human, but highly accurate at predicting a particular object.

“An attacker can trick the object recognition algorithm into seeing something that isn’t there, without these alterations being obvious to a human.”

What this means is that by identifying these patterns and overlaying them over a different image, an attacker can trick the object recognition algorithm into seeing something that isn’t there, without these alterations being obvious to a human. This kind of manipulation is known as an “adversarial attack.”
Early attempts to trick image recognition systems this way required access to the algorithm’s inner workings to decipher these patterns. But in 2016 researchers demonstrated a “black box” attack that enabled them to trick such a system without knowing its inner workings.
By feeding the system doctored images and seeing how it classified them, they were able to work out what it was focusing on and therefore generate images they knew would fool it. Importantly, the doctored images were not obviously different to human eyes.
These approaches were tested by feeding doctored image data directly into the algorithm, but more recently, similar approaches have been applied in the real world. Last year it was shown that printouts of doctored images that were then photographed on a smartphone successfully tricked an image classification system.
Another group showed that wearing specially designed, psychedelically-colored spectacles could trick a facial recognition system into thinking people were celebrities. In August scientists showed that adding stickers to stop signs in particular configurations could cause a neural net designed to spot them to misclassify the signs.
These last two examples highlight some of the potential nefarious applications for this technology. Getting a self-driving car to miss a stop sign could cause an accident, either for insurance fraud or to do someone harm. If facial recognition becomes increasingly popular for biometric security applications, being able to pose as someone else could be very useful to a con artist.
Unsurprisingly, there are already efforts to counteract the threat of adversarial attacks. In particular, it has been shown that deep neural networks can be trained to detect adversarial images. One study from the Bosch Center for AI demonstrated such a detector, an adversarial attack that fools the detector, and a training regime for the detector that nullifies the attack, hinting at the kind of arms race we are likely to see in the future.
While image recognition systems provide an easy-to-visualize demonstration, they’re not the only machine learning systems at risk. The techniques used to perturb pixel data can be applied to other kinds of data too.

“Bypassing cybersecurity defenses is one of the more worrying and probable near-term applications for this approach.”

Chinese researchers showed that adding specific words to a sentence or misspelling a word can completely throw off machine learning systems designed to analyze what a passage of text is about. Another group demonstrated that garbled sounds played over speakers could make a smartphone running the Google Now voice command system visit a particular web address, which could be used to download malware.
This last example points toward one of the more worrying and probable near-term applications for this approach: bypassing cybersecurity defenses. The industry is increasingly using machine learning and data analytics to identify malware and detect intrusions, but these systems are also highly susceptible to trickery.
At this summer’s DEF CON hacking convention, a security firm demonstrated they could bypass anti-malware AI using a similar approach to the earlier black box attack on the image classifier, but super-powered with an AI of their own.
Their system fed malicious code to the antivirus software and then noted the score it was given. It then used genetic algorithms to iteratively tweak the code until it was able to bypass the defenses while maintaining its function.
All the approaches noted so far are focused on tricking pre-trained machine learning systems, but another approach of major concern to the cybersecurity industry is that of “data poisoning.” This is the idea that introducing false data into a machine learning system’s training set will cause it to start misclassifying things.
This could be particularly challenging for things like anti-malware systems that are constantly being updated to take into account new viruses. A related approach bombards systems with data designed to generate false positives so the defenders recalibrate their systems in a way that then allows the attackers to sneak in.
How likely it is that these approaches will be used in the wild will depend on the potential reward and the sophistication of the attackers. Most of the techniques described above require high levels of domain expertise, but it’s becoming ever easier to access training materials and tools for machine learning.
Simpler versions of machine learning have been at the heart of email spam filters for years, and spammers have developed a host of innovative workarounds to circumvent them. As machine learning and AI increasingly embed themselves in our lives, the rewards for learning how to trick them will likely outweigh the costs.
Image Credit: Nejron Photo / Shutterstock.com Continue reading

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#431203 Could We Build a Blade Runner-Style ...

The new Blade Runner sequel will return us to a world where sophisticated androids made with organic body parts can match the strength and emotions of their human creators. As someone who builds biologically inspired robots, I’m interested in whether our own technology will ever come close to matching the “replicants” of Blade Runner 2049.
The reality is that we’re a very long way from building robots with human-like abilities. But advances in so-called soft robotics show a promising way forward for technology that could be a new basis for the androids of the future.
From a scientific point of view, the real challenge is replicating the complexity of the human body. Each one of us is made up of millions and millions of cells, and we have no clue how we can build such a complex machine that is indistinguishable from us humans. The most complex machines today, for example the world’s largest airliner, the Airbus A380, are composed of millions of parts. But in order to match the complexity level of humans, we would need to scale this complexity up about a million times.
There are currently three different ways that engineering is making the border between humans and robots more ambiguous. Unfortunately, these approaches are only starting points and are not yet even close to the world of Blade Runner.
There are human-like robots built from scratch by assembling artificial sensors, motors, and computers to resemble the human body and motion. However, extending the current human-like robot would not bring Blade Runner-style androids closer to humans, because every artificial component, such as sensors and motors, are still hopelessly primitive compared to their biological counterparts.
There is also cyborg technology, where the human body is enhanced with machines such as robotic limbs and wearable and implantable devices. This technology is similarly very far away from matching our own body parts.
Finally, there is the technology of genetic manipulation, where an organism’s genetic code is altered to modify that organism’s body. Although we have been able to identify and manipulate individual genes, we still have a limited understanding of how an entire human emerges from genetic code. As such, we don’t know the degree to which we can actually program code to design everything we wish.
Soft robotics: a way forward?
But we might be able to move robotics closer to the world of Blade Runner by pursuing other technologies and, in particular, by turning to nature for inspiration. The field of soft robotics is a good example. In the last decade or so, robotics researchers have been making considerable efforts to make robots soft, deformable, squishable, and flexible.
This technology is inspired by the fact that 90% of the human body is made from soft substances such as skin, hair, and tissues. This is because most of the fundamental functions in our body rely on soft parts that can change shape, from the heart and lungs pumping fluid around our body to the eye lenses generating signals from their movement. Cells even change shape to trigger division, self-healing and, ultimately, the evolution of the body.
The softness of our bodies is the origin of all their functionality needed to stay alive. So being able to build soft machines would at least bring us a step closer to the robotic world of Blade Runner. Some of the recent technological advances include artificial hearts made out of soft functional materials that are pumping fluid through deformation. Similarly, soft, wearable gloves can help make hand grasping stronger. And “epidermal electronics” has enabled us to tattoo electronic circuits onto our biological skins.
Softness is the keyword that brings humans and technologies closer together. Sensors, motors, and computers are all of a sudden integrated into human bodies once they became soft, and the border between us and external devices becomes ambiguous, just like soft contact lenses became part of our eyes.
Nevertheless, the hardest challenge is how to make individual parts of a soft robot body physically adaptable by self-healing, growing, and differentiating. After all, every part of a living organism is also alive in biological systems in order to make our bodies totally adaptable and evolvable, the function of which could make machines totally indistinguishable from ourselves.
It is impossible to predict when the robotic world of Blade Runner might arrive, and if it does, it will probably be very far in the future. But as long as the desire to build machines indistinguishable from humans is there, the current trends of robotic revolution could make it possible to achieve that dream.
This article was originally published on The Conversation. Read the original article.
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#431178 Soft Robotics Releases Development Kit ...

Cambridge, MA – Soft Robotics Inc, which has built a fundamentally new class of robotic grippers, announced the release of its expanded and upgraded Soft Robotics Development Kit; SRDK 2.0.

The Soft Robotics Development Kit 2.0 comes complete with:

Robot tool flange mounting plate
4, 5 and 6 position hub plates
Tool Center Point
Soft Robotics Control Unit G2
6 rail mounted, 4 accordion actuator modules
Custom pneumatic manifold
Mounting hardware and accessories

Where the SRDK 1.0 included 5 four accordion actuator modules and the opportunity to create a gripper containing two to five actuators, The SRDK 2.0 contains 6 four accordion actuator modules plus the addition of a six position hub allowing users the ability to configure six actuator test tools. This expands use of the Development Kit to larger product applications, such as: large bagged and pouched items, IV bags, bags of nuts, bread and other food items.

SRDK 2.0 also contains an upgraded Soft Robotics Control Unit (SRCU G2) – the proprietary system that controls all software and hardware with one turnkey pneumatic operation. The upgraded SRCU features new software with a cleaner, user friendly interface and an IP65 rating. Highly intuitive, the software is able to store up to eight grip profiles and allows for very precise adjustments to actuation and vacuum.

Also new with the release of SRDK 2.0, is the introduction of several accessory kits that will allow for an expanded number of configurations and product applications available for testing.

Accessory Kit 1 – For SRDK 1.0 users only – includes the six position hub and 4 accordion actuators now included in SRDK 2.0
Accessory Kit 2 – For SRDK 1.0 or 2.0 users – includes 2 accordion actuators
Accessory Kit 3 – For SRDK 1.0 or 2.0 users – includes 3 accordion actuators

The shorter 2 and 3 accordion actuators provide increased stability for high-speed applications, increased placement precision, higher grip force capabilities and are optimized for gripping small, shallow objects.

Designed to plug and play with any existing robot currently in the market, the Soft Robotics Development Kit 2.0 allows end-users and OEM Integrators the ability to customize, test and validate their ideal Soft Robotics solution, with their own equipment, in their own environment.

Once an ideal solution has been found, the Soft Robotics team will take those exact specifications and build a production-grade tool for implementation into the manufacturing line. And, it doesn’t end there. Created to be fully reusable, the process – configure, test, validate, build, production – can start over again as many times as needed.

See the new SRDK 2.0 on display for the first time at PACK EXPO Las Vegas, September 25 – 27, 2017 in Soft Robotics booth S-5925.

Learn more about the Soft Robotics Development Kit at www.softroboticsinc.com/srdk.
Photo Credit: Soft Robotics – www.softroboticsinc.com
###
About Soft Robotics
Soft Robotics designs and builds soft robotic gripping systems and automation solutions
that can grasp and manipulate items of varying size, shape and weight. Spun out of the
Whitesides Group at Harvard University, Soft Robotics is the only company to be
commercializing this groundbreaking and proprietary technology platform. Today, the
company is a global enterprise solving previously off-limits automation challenges for
customers in food & beverage, advanced manufacturing and ecommerce. Soft Robotics’
engineers are building an ecosystem of robots, control systems, data and machine
learning to enable the workplace of the future. For more information, please visit
www.softroboticsinc.com.

Media contact:
Jennie Kondracki
The Kondracki Group, LLC
262-501-4507
jennie@kondrackigroup.com
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#431175 Servosila introduces Mobile Robots ...

Servosila introduces a new member of the family of Servosila “Engineer” robots, a UGV called “Radio Engineer”. This new variant of the well-known backpack-transportable robot features a Software Defined Radio (SDR) payload module integrated into the robotic vehicle.

“Several of our key customers had asked us to enable an Electronic Warfare (EW) or Cognitive Radio applications in our robots”, – says a spokesman for the company, “By integrating a Software Defined Radio (SDR) module into our robotic platforms we cater to both requirements. Radio spectrum analysis, radio signal detection, jamming, and radio relay are important features for EOD robots such as ours. Servosila continues to serve the customers by pushing the boundaries of what their Servosila robots can do. Our partners in the research world and academia shall also greatly benefit from the new functionality that gives them more means of achieving their research goals.”
Photo Credit: Servosila – www.servosila.com
Coupling a programmable mobile robot with a software-defined radio creates a powerful platform for developing innovative applications that mix mobility and artificial intelligence with modern radio technologies. The new robotic radio applications include localized frequency hopping pattern analysis, OFDM waveform recognition, outdoor signal triangulation, cognitive mesh networking, automatic area search for radio emitters, passive or active mobile robotic radars, mobile base stations, mobile radio scanners, and many others.

A rotating head of the robot with mounts for external antennae acts as a pan-and-tilt device thus enabling various scanning and tracking applications. The neck of the robotic head is equipped with a pair of highly accurate Servosila-made servos with a pointing precision of 3.0 angular minutes. This means that the robot can point its antennae with an unprecedented accuracy.

Researchers and academia can benefit from the platform’s support for GnuRadio, an open source software framework for developing SDR applications. An on-board Intel i7 computer capable of executing OpenCL code, is internally connected to the SDR payload module. This makes it possible to execute most existing GnuRadio applications directly on the robot’s on-board computer. Other sensors of the robot such as a GPS sensor, an IMU or a thermal vision camera contribute into sensor fusion algorithms.

Since Servosila “Engineer” mobile robots are primarily designed for outdoor use, the SDR module is fully enclosed into a hardened body of the robot which provides protection in case of dust, rain, snow or impacts with obstacles while the robot is on the move. The robot and its SDR payload module are both powered by an on-board battery thus making the entire robotic radio platform independent of external power supplies.

Servosila plans to start shipping the SDR-equipped robots to international customers in October, 2017.

Web: https://www.servosila.com
YouTube: https://www.youtube.com/user/servosila/videos

About the Company
Servosila is a robotics technology company that designs, produces and markets a range of mobile robots, robotic arms, servo drives, harmonic reduction gears, robotic control systems as well as software packages that make the robots intelligent. Servosila provides consulting, training and operations support services to various customers around the world. The company markets its products and services directly or through a network of partners who provide tailored and localized services that meet specific procurement, support or operational needs.
Press Release above is by: Servosila
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Posted in Human Robots