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#431653 9 Robot Animals Built From Nature’s ...

Millions of years of evolution have allowed animals to develop some elegant and highly efficient solutions to problems like locomotion, flight, and dexterity. As Boston Dynamics unveils its latest mechanical animals, here’s a rundown of nine recent robots that borrow from nature and why.
SpotMini – Boston Dynamics

Starting with BigDog in 2005, the US company has built a whole stable of four-legged robots in recent years. Their first product was designed to be a robotic packhorse for soldiers that borrowed the quadrupedal locomotion of animals to travel over terrain too rough for conventional vehicles.
The US Army ultimately rejected the robot for being too noisy, according to the Guardian, but since then the company has scaled down its design, first to the Spot, then a first edition of the SpotMini that came out last year.
The latter came with a robotic arm where its head should be and was touted as a domestic helper, but a sleeker second edition without the arm was released earlier this month. There’s little detail on what the new robot is designed for, but the more polished design suggests a more consumer-focused purpose.
OctopusGripper – Festo

Festo has released a long line of animal-inspired machines over the years, from a mechanical kangaroo to robotic butterflies. Its latest creation isn’t a full animal—instead it’s a gripper based on an octopus tentacle that can be attached to the end of a robotic arm.
The pneumatically-powered device is made of soft silicone and features two rows of suction cups on its inner edge. By applying compressed air the tentacle can wrap around a wide variety of differently shaped objects, just like its natural counterpart, and a vacuum can be applied to the larger suction cups to grip the object securely. Because it’s soft, it holds promise for robots required to operate safely in collaboration with humans.
CRAM – University of California, Berkeley

Cockroaches are renowned for their hardiness and ability to disappear down cracks that seem far too small for them. Researchers at UC Berkeley decided these capabilities could be useful for search and rescue missions and so set about experimenting on the insects to find out their secrets.
They found the bugs can squeeze into gaps a fifth of their normal standing height by splaying their legs out to the side without significantly slowing themselves down. So they built a palm-sized robot with a jointed plastic shell that could do the same to squeeze into crevices half its normal height.
Snake Robot – Carnegie Mellon University

Search and rescue missions are a common theme for animal-inspired robots, but the snake robot built by CMU researchers is one of the first to be tested in a real disaster.
A team of roboticists from the university helped Mexican Red Cross workers search collapsed buildings for survivors after the 7.1-magnitude earthquake that struck Mexico City in September. The snake design provides a small diameter and the ability to move in almost any direction, which makes the robot ideal for accessing tight spaces, though the team was unable to locate any survivors.
The snake currently features a camera on the front, but researchers told IEEE Spectrum that the experience helped them realize they should also add a microphone to listen for people trapped under the rubble.
Bio-Hybrid Stingray – Harvard University

Taking more than just inspiration from the animal kingdom, a group from Harvard built a robotic stingray out of silicone and rat heart muscle cells.
The robot uses the same synchronized undulations along the edge of its fins to propel itself as a ray does. But while a ray has two sets of muscles to pull the fins up and down, the new device has only one that pulls them down, with a springy gold skeleton that pulls them back up again. The cells are also genetically modified to be activated by flashes of light.
The project’s leader eventually hopes to engineer a human heart, and both his stingray and an earlier jellyfish bio-robot are primarily aimed at better understanding how that organ works.
Bat Bot – Caltech

Most recent advances in drone technology have come from quadcopters, but Caltech engineers think rigid devices with rapidly spinning propellers are probably not ideal for use in close quarters with humans.
That’s why they turned to soft-winged bats for inspiration. That’s no easy feat, though, considering bats use more than 40 joints with each flap of their wings, so the team had to optimize down to nine joints to avoid it becoming too bulky. The simplified bat can’t ascend yet, but its onboard computer and sensors let it autonomously carry out glides, turns, and dives.
Salto – UC Berkeley

While even the most advanced robots tend to plod around, tree-dwelling animals have the ability to spring from branch to branch to clear obstacles and climb quickly. This could prove invaluable for search and rescue robots by allowing them to quickly traverse disordered rubble.
UC Berkeley engineers turned to the Senegal bush baby for inspiration after determining it scored highest in “vertical jumping agility”—a combination of how high and how frequently an animal can jump. They recreated its ability to get into a super-low crouch that stores energy in its tendons to create a robot that could carry out parkour-style double jumps off walls to quickly gain height.
Pleurobot – École Polytechnique Fédérale de Lausanne

Normally robots are masters of air, land, or sea, but the robotic salamander built by researchers at EPFL can both walk and swim.
Its designers used X-ray videos to carefully study how the amphibians move before using this to build a true-to-life robotic version using 3D printed bones, motorized joints, and a synthetic nervous system made up of electronic circuitry.
The robot’s low center of mass and segmented legs make it great at navigating rough terrain without losing balance, and the ability to swim gives added versatility. They also hope it will help paleontologists gain a better understanding of the movements of the first tetrapods to transition from water to land, which salamanders are the best living analog of.
Eelume – Eelume

A snakelike body isn’t only useful on land—eels are living proof it’s an efficient way to travel underwater, too. Norwegian robotics company Eelume has borrowed these principles to build a robot capable of sub-sea inspection, maintenance, and repair.
The modular design allows operators to put together their own favored configuration of joints and payloads such as sensors and tools. And while an early version of the robot used the same method of locomotion as an eel, the latest version undergoing sea trials has added a variety of thrusters for greater speeds and more maneuverability.
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#431599 8 Ways AI Will Transform Our Cities by ...

How will AI shape the average North American city by 2030? A panel of experts assembled as part of a century-long study into the impact of AI thinks its effects will be profound.
The One Hundred Year Study on Artificial Intelligence is the brainchild of Eric Horvitz, technical fellow and a managing director at Microsoft Research.
Every five years a panel of experts will assess the current state of AI and its future directions. The first panel, comprised of experts in AI, law, political science, policy, and economics, was launched last fall and decided to frame their report around the impact AI will have on the average American city. Here’s how they think it will affect eight key domains of city life in the next fifteen years.
1. Transportation
The speed of the transition to AI-guided transport may catch the public by surprise. Self-driving vehicles will be widely adopted by 2020, and it won’t just be cars — driverless delivery trucks, autonomous delivery drones, and personal robots will also be commonplace.
Uber-style “cars as a service” are likely to replace car ownership, which may displace public transport or see it transition towards similar on-demand approaches. Commutes will become a time to relax or work productively, encouraging people to live further from home, which could combine with reduced need for parking to drastically change the face of modern cities.
Mountains of data from increasing numbers of sensors will allow administrators to model individuals’ movements, preferences, and goals, which could have major impact on the design city infrastructure.
Humans won’t be out of the loop, though. Algorithms that allow machines to learn from human input and coordinate with them will be crucial to ensuring autonomous transport operates smoothly. Getting this right will be key as this will be the public’s first experience with physically embodied AI systems and will strongly influence public perception.
2. Home and Service Robots
Robots that do things like deliver packages and clean offices will become much more common in the next 15 years. Mobile chipmakers are already squeezing the power of last century’s supercomputers into systems-on-a-chip, drastically boosting robots’ on-board computing capacity.
Cloud-connected robots will be able to share data to accelerate learning. Low-cost 3D sensors like Microsoft’s Kinect will speed the development of perceptual technology, while advances in speech comprehension will enhance robots’ interactions with humans. Robot arms in research labs today are likely to evolve into consumer devices around 2025.
But the cost and complexity of reliable hardware and the difficulty of implementing perceptual algorithms in the real world mean general-purpose robots are still some way off. Robots are likely to remain constrained to narrow commercial applications for the foreseeable future.
3. Healthcare
AI’s impact on healthcare in the next 15 years will depend more on regulation than technology. The most transformative possibilities of AI in healthcare require access to data, but the FDA has failed to find solutions to the difficult problem of balancing privacy and access to data. Implementation of electronic health records has also been poor.
If these hurdles can be cleared, AI could automate the legwork of diagnostics by mining patient records and the scientific literature. This kind of digital assistant could allow doctors to focus on the human dimensions of care while using their intuition and experience to guide the process.
At the population level, data from patient records, wearables, mobile apps, and personal genome sequencing will make personalized medicine a reality. While fully automated radiology is unlikely, access to huge datasets of medical imaging will enable training of machine learning algorithms that can “triage” or check scans, reducing the workload of doctors.
Intelligent walkers, wheelchairs, and exoskeletons will help keep the elderly active while smart home technology will be able to support and monitor them to keep them independent. Robots may begin to enter hospitals carrying out simple tasks like delivering goods to the right room or doing sutures once the needle is correctly placed, but these tasks will only be semi-automated and will require collaboration between humans and robots.
4. Education
The line between the classroom and individual learning will be blurred by 2030. Massive open online courses (MOOCs) will interact with intelligent tutors and other AI technologies to allow personalized education at scale. Computer-based learning won’t replace the classroom, but online tools will help students learn at their own pace using techniques that work for them.
AI-enabled education systems will learn individuals’ preferences, but by aggregating this data they’ll also accelerate education research and the development of new tools. Online teaching will increasingly widen educational access, making learning lifelong, enabling people to retrain, and increasing access to top-quality education in developing countries.
Sophisticated virtual reality will allow students to immerse themselves in historical and fictional worlds or explore environments and scientific objects difficult to engage with in the real world. Digital reading devices will become much smarter too, linking to supplementary information and translating between languages.
5. Low-Resource Communities
In contrast to the dystopian visions of sci-fi, by 2030 AI will help improve life for the poorest members of society. Predictive analytics will let government agencies better allocate limited resources by helping them forecast environmental hazards or building code violations. AI planning could help distribute excess food from restaurants to food banks and shelters before it spoils.
Investment in these areas is under-funded though, so how quickly these capabilities will appear is uncertain. There are fears valueless machine learning could inadvertently discriminate by correlating things with race or gender, or surrogate factors like zip codes. But AI programs are easier to hold accountable than humans, so they’re more likely to help weed out discrimination.
6. Public Safety and Security
By 2030 cities are likely to rely heavily on AI technologies to detect and predict crime. Automatic processing of CCTV and drone footage will make it possible to rapidly spot anomalous behavior. This will not only allow law enforcement to react quickly but also forecast when and where crimes will be committed. Fears that bias and error could lead to people being unduly targeted are justified, but well-thought-out systems could actually counteract human bias and highlight police malpractice.
Techniques like speech and gait analysis could help interrogators and security guards detect suspicious behavior. Contrary to concerns about overly pervasive law enforcement, AI is likely to make policing more targeted and therefore less overbearing.
7. Employment and Workplace
The effects of AI will be felt most profoundly in the workplace. By 2030 AI will be encroaching on skilled professionals like lawyers, financial advisers, and radiologists. As it becomes capable of taking on more roles, organizations will be able to scale rapidly with relatively small workforces.
AI is more likely to replace tasks rather than jobs in the near term, and it will also create new jobs and markets, even if it’s hard to imagine what those will be right now. While it may reduce incomes and job prospects, increasing automation will also lower the cost of goods and services, effectively making everyone richer.
These structural shifts in the economy will require political rather than purely economic responses to ensure these riches are shared. In the short run, this may include resources being pumped into education and re-training, but longer term may require a far more comprehensive social safety net or radical approaches like a guaranteed basic income.
8. Entertainment
Entertainment in 2030 will be interactive, personalized, and immeasurably more engaging than today. Breakthroughs in sensors and hardware will see virtual reality, haptics and companion robots increasingly enter the home. Users will be able to interact with entertainment systems conversationally, and they will show emotion, empathy, and the ability to adapt to environmental cues like the time of day.
Social networks already allow personalized entertainment channels, but the reams of data being collected on usage patterns and preferences will allow media providers to personalize entertainment to unprecedented levels. There are concerns this could endow media conglomerates with unprecedented control over people’s online experiences and the ideas to which they are exposed.
But advances in AI will also make creating your own entertainment far easier and more engaging, whether by helping to compose music or choreograph dances using an avatar. Democratizing the production of high-quality entertainment makes it nearly impossible to predict how highly fluid human tastes for entertainment will develop.
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#431371 Amazon Is Quietly Building the Robots of ...

Science fiction is the siren song of hard science. How many innocent young students have been lured into complex, abstract science, technology, engineering, or mathematics because of a reckless and irresponsible exposure to Arthur C. Clarke at a tender age? Yet Arthur C. Clarke has a very famous quote: “Any sufficiently advanced technology is indistinguishable from magic.”
It’s the prospect of making that… ahem… magic leap that entices so many people into STEM in the first place. A magic leap that would change the world. How about, for example, having humanoid robots? They could match us in dexterity and speed, perceive the world around them as we do, and be programmed to do, well, more or less anything we can do.
Such a technology would change the world forever.
But how will it arrive? While true sci-fi robots won’t get here right away—the pieces are coming together, and the company best developing them at the moment is Amazon. Where others have struggled to succeed, Amazon has been quietly progressing. Notably, Amazon has more than just a dream, it has the most practical of reasons driving it into robotics.
This practicality matters. Technological development rarely proceeds by magic; it’s a process filled with twists, turns, dead-ends, and financial constraints. New technologies often have to answer questions like “What is this good for, are you being realistic?” A good strategy, then, can be to build something more limited than your initial ambition, but useful for a niche market. That way, you can produce a prototype, have a reasonable business plan, and turn a profit within a decade. You might call these “stepping stone” applications that allow for new technologies to be developed in an economically viable way.
You need something you can sell to someone, soon: that’s how you get investment in your idea. It’s this model that iRobot, developers of the Roomba, used: migrating from military prototypes to robotic vacuum cleaners to become the “boring, successful robot company.” Compare this to Willow Garage, a genius factory if ever there was one: they clearly had ambitions towards a general-purpose, multi-functional robot. They built an impressive device—PR2—and programmed the operating system, ROS, that is still the industry and academic standard to this day.
But since they were unable to sell their robot for much less than $250,000, it was never likely to be a profitable business. This is why Willow Garage is no more, and many workers at the company went into telepresence robotics. Telepresence is essentially videoconferencing with a fancy robot attached to move the camera around. It uses some of the same software (for example, navigation and mapping) without requiring you to solve difficult problems of full autonomy for the robot, or manipulating its environment. It’s certainly one of the stepping-stone areas that various companies are investigating.
Another approach is to go to the people with very high research budgets: the military.
This was the Boston Dynamics approach, and their incredible achievements in bipedal locomotion saw them getting snapped up by Google. There was a great deal of excitement and speculation about Google’s “nightmare factory” whenever a new slick video of a futuristic militarized robot surfaced. But Google broadly backed away from Replicant, their robotics program, and Boston Dynamics was sold. This was partly due to PR concerns over the Terminator-esque designs, but partly because they didn’t see the robotics division turning a profit. They hadn’t found their stepping stones.
This is where Amazon comes in. Why Amazon? First off, they just announced that their profits are up by 30 percent, and yet the company is well-known for their constantly-moving Day One philosophy where a great deal of the profits are reinvested back into the business. But lots of companies have ambition.
One thing Amazon has that few other corporations have, as well as big financial resources, is viable stepping stones for developing the technologies needed for this sort of robotics to become a reality. They already employ 100,000 robots: these are of the “pragmatic, boring, useful” kind that we’ve profiled, which move around the shelves in warehouses. These robots are allowing Amazon to develop localization and mapping software for robots that can autonomously navigate in the simple warehouse environment.
But their ambitions don’t end there. The Amazon Robotics Challenge is a multi-million dollar competition, open to university teams, to produce a robot that can pick and package items in warehouses. The problem of grasping and manipulating a range of objects is not a solved one in robotics, so this work is still done by humans—yet it’s absolutely fundamental for any sci-fi dream robot.
Google, for example, attempted to solve this problem by hooking up 14 robot hands to machine learning algorithms and having them grasp thousands of objects. Although results were promising, the 10 to 20 percent failure rate for grasps is too high for warehouse use. This is a perfect stepping stone for Amazon; should they crack the problem, they will likely save millions in logistics.
Another area where humanoid robotics—especially bipedal locomotion, or walking, has been seriously suggested—is in the last mile delivery problem. Amazon has shown willingness to be creative in this department with their notorious drone delivery service. In other words, it’s all very well to have your self-driving car or van deliver packages to people’s doors, but who puts the package on the doorstep? It’s difficult for wheeled robots to navigate the full range of built environments that exist. That’s why bipedal robots like CASSIE, developed by Oregon State, may one day be used to deliver parcels.
Again: no one more than Amazon stands to profit from cracking this technology. The line from robotics research to profit is very clear.
So, perhaps one day Amazon will have robots that can move around and manipulate their environments. But they’re also working on intelligence that will guide those robots and make them truly useful for a variety of tasks. Amazon has an AI, or at least the framework for an AI: it’s called Alexa, and it’s in tens of millions of homes. The Alexa Prize, another multi-million-dollar competition, is attempting to make Alexa more social.
To develop a conversational AI, at least using the current methods of machine learning, you need data on tens of millions of conversations. You need to understand how people will try to interact with the AI. Amazon has access to this in Alexa, and they’re using it. As owners of the leading voice-activated personal assistant, they have an ecosystem of developers creating apps for Alexa. It will be integrated with the smart home and the Internet of Things. It is a very marketable product, a stepping stone for robot intelligence.
What’s more, the company can benefit from its huge sales infrastructure. For Amazon, having an AI in your home is ideal, because it can persuade you to buy more products through its website. Unlike companies like Google, Amazon has an easy way to make a direct profit from IoT devices, which could fuel funding.
For a humanoid robot to be truly useful, though, it will need vision and intelligence. It will have to understand and interpret its environment, and react accordingly. The way humans learn about our environment is by getting out and seeing it. This is something that, for example, an Alexa coupled to smart glasses would be very capable of doing. There are rumors that Alexa’s AI will soon be used in security cameras, which is an ideal stepping stone task to train an AI to process images from its environment, truly perceiving the world and any threats it might contain.
It’s a slight exaggeration to say that Amazon is in the process of building a secret robot army. The gulf between our sci-fi vision of robots that can intelligently serve us, rather than mindlessly assemble cars, is still vast. But in quietly assembling many of the technologies needed for intelligent, multi-purpose robotics—and with the unique stepping stones they have along the way—Amazon might just be poised to leap that gulf. As if by magic.
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#431327 CNN Uses Vantage Robotics’ Snap ...

The news network is now allowed to film over crowds using a lightweight video drone Continue reading

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#431170 This Week’s Awesome Stories From ...

AUGMENTED REALITY
ZED Mini Turns Rift and Vive Into an AR Headset From the FutureBen Lang | Road to VR“When attached, the camera provides stereo pass-through video and real-time depth and environment mapping, turning the headsets into dev kits emulating the capabilities of high-end AR headsets of the future. The ZED Mini will launch in November.”
ROBOTICS
Life-Size Humanoid Robot Is Designed to Fall Over (and Over and Over)Evan Ackerman | IEEE Spectrum “The researchers came up with a new strategy for not worrying about falls: not worrying about falls. Instead, they’ve built their robot from the ground up with an armored structure that makes it totally okay with falling over and getting right back up again.”
SPACE
Russia Will Team up With NASA to Build a Lunar Space StationAnatoly Zak | Popular Mechanics “NASA and its partner agencies plan to begin the construction of the modular habitat known as the Deep-Space Gateway in orbit around the Moon in the early 2020s. It will become the main destination for astronauts for at least a decade, extending human presence beyond the Earth’s orbit for the first time since the end of the Apollo program in 1972. Launched on NASA’s giant SLS rocket and serviced by the crews of the Orion spacecraft, the outpost would pave the way to a mission to Mars in the 2030s.”
TRANSPORTATION
Dubai Starts Testing Crewless Two-Person ‘Flying Taxis’Thuy Ong | The Verge“The drone was uncrewed and hovered 200 meters high during the test flight, according to Reuters. The AAT, which is about two meters high, was supplied by specialist German manufacturer Volocopter, known for its eponymous helicopter drone hybrid with 18 rotors…Dubai has a target for autonomous transport to account for a quarter of total trips by 2030.”
AUTONOMOUS CARS
Toyota Is Trusting a Startup for a Crucial Part of Its Newest Self-Driving CarsJohana Bhuiyan | Recode “Toyota unveiled the next generation of its self-driving platform today, which features more accurate object detection technology and mapping, among other advancements. These test cars—which Toyota is testing on both a closed driving course and on some public roads—will also be using Luminar’s lidar sensors, or radars that use lasers to detect the distance to an object.”
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