Tag Archives: attention

#437992 This Week’s Awesome Tech Stories From ...

ARTIFICIAL INTELLIGENCE
This Chinese Lab Is Aiming for Big AI Breakthroughs
Will Knight | Wired
“China produces as many artificial intelligence researchers as the US, but it lags in key fields like machine learning. The government hopes to make up ground. …It set AI researchers the goal of making ‘fundamental breakthroughs by 2025’ and called for the country to be ‘the world’s primary innovation center by 2030.’ BAAI opened a year later, in Zhongguancun, a neighborhood of Beijing designed to replicate US innovation hubs such as Boston and Silicon Valley.”

ENVIRONMENT
What Elon Musk’s $100 Million Carbon Capture Prize Could Mean
James Temple | MIT Technology Review
“[Elon Musk] announced on Twitter that he plans to give away $100 million of [his $180 billion net worth] as a prize for the ‘best carbon capture technology.’ …Another $100 million could certainly help whatever venture, or ventures, clinch Musk’s prize. But it’s a tiny fraction of his wealth and will also only go so far. …Money aside, however, one thing Musk has a particular knack for is generating attention. And this is a space in need of it.”

HEALTH
Synthetic Cornea Helped a Legally Blind Man Regain His Sight
Steve Dent | Engadget
“While the implant doesn’t contain any electronics, it could help more people than any robotic eye. ‘After years of hard work, seeing a colleague implant the CorNeat KPro with ease and witnessing a fellow human being regain his sight the following day was electrifying and emotionally moving, there were a lot of tears in the room,’ said CorNeat Vision co-founder Dr. Gilad Litvin.”

BIOTECH
MIT Develops Method for Lab-Grown Plants That May Eventually Lead to Alternatives to Forestry and Farming
Darrell Etherington | TechCrunch
“If the work of these researchers can eventually be used to create a way to produce lab-grown wood for use in construction and fabrication in a way that’s scalable and efficient, then there’s tremendous potential in terms of reducing the impact on forestry globally. Eventually, the team even theorizes you could coax the growth of plant-based materials into specific target shapes, so you could also do some of the manufacturing in the lab, by growing a wood table directly for instance.”

AUTOMATION
FAA Approves First Fully Automated Commercial Drone Flights
Andy Pasztor and Katy Stech Ferek | The Wall Street Journal
“US aviation regulators have approved the first fully automated commercial drone flights, granting a small Massachusetts-based company permission to operate drones without hands-on piloting or direct observation by human controllers or observers. …The company’s Scout drones operate under predetermined flight programs and use acoustic technology to detect and avoid drones, birds, and other obstacles.”

SPACE
China’s Surging Private Space Industry Is Out to Challenge the US
Neel V. Patel | MIT Technology Review
“[The Ceres-1] was a commercial rocket—only the second from a Chinese company ever to go into space. And the launch happened less than three years after the company was founded. The achievement is a milestone for China’s fledgling—but rapidly growing—private space industry, an increasingly critical part of the country’s quest to dethrone the US as the world’s preeminent space power.”

CRYPTOCURRENCY
Janet Yellen Will Consider Limiting Use of Cryptocurrency
Timothy B. Lee | Ars Technica
“Cryptocurrencies could come under renewed regulatory scrutiny over the next four years if Janet Yellen, Joe Biden’s pick to lead the Treasury Department, gets her way. During Yellen’s Tuesday confirmation hearing before the Senate Finance Committee, Sen. Maggie Hassan (D-N.H.) asked Yellen about the use of cryptocurrency by terrorists and other criminals. ‘Cryptocurrencies are a particular concern,’ Yellen responded. ‘I think many are used—at least in a transactions sense—mainly for illicit financing.’i”

SCIENCE
Secret Ingredient Found to Power Supernovas
Thomas Lewton | Quanta
“…Only in the last few years, with the growth of supercomputers, have theorists had enough computing power to model massive stars with the complexity needed to achieve explosions. …These new simulations are giving researchers a better understanding of exactly how supernovas have shaped the universe we see today.”

Image Credit: Ricardo Gomez Angel / Unsplash Continue reading

Posted in Human Robots

#437924 How a Software Map of the Entire Planet ...

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“3D map data is the scaffolding of the 21st century.”

–Edward Miller, Founder, Scape Technologies, UK

Covered in cameras, sensors, and a distinctly spaceship looking laser system, Google’s autonomous vehicles were easy to spot when they first hit public roads in 2015. The key hardware ingredient is a spinning laser fixed to the roof, called lidar, which provides the car with a pair of eyes to see the world. Lidar works by sending out beams of light and measuring the time it takes to bounce off objects back to the source. By timing the light’s journey, these depth-sensing systems construct fully 3D maps of their surroundings.

3D maps like these are essentially software copies of the real world. They will be crucial to the development of a wide range of emerging technologies including autonomous driving, drone delivery, robotics, and a fast-approaching future filled with augmented reality.

Like other rapidly improving technologies, lidar is moving quickly through its development cycle. What was an expensive technology on the roof of a well-funded research project is now becoming cheaper, more capable, and readily available to consumers. At some point, lidar will come standard on most mobile devices and is now available to early-adopting owners of the iPhone 12 Pro.

Consumer lidar represents the inevitable shift from wealthy tech companies generating our world’s map data, to a more scalable crowd-sourced approach. To develop the repository for their Street View Maps product, Google reportedly spent $1-2 billion sending cars across continents photographing every street. Compare that to a live-mapping service like Waze, which uses crowd-sourced user data from its millions of users to generate accurate and real-time traffic conditions. Though these maps serve different functions, one is a static, expensive, unchanging map of the world while the other is dynamic, real-time, and constructed by users themselves.

Soon millions of people may be scanning everything from bedrooms to neighborhoods, resulting in 3D maps of significant quality. An online search for lidar room scans demonstrates just how richly textured these three-dimensional maps are compared to anything we’ve had before. With lidar and other depth-sensing systems, we now have the tools to create exact software copies of everywhere and everything on earth.

At some point, likely aided by crowdsourcing initiatives, these maps will become living breathing, real-time representations of the world. Some refer to this idea as a “digital twin” of the planet. In a feature cover story, Kevin Kelly, the cofounder of Wired magazine, calls this concept the “mirrorworld,” a one-to-one software map of everything.

So why is that such a big deal? Take augmented reality as an example.

Of all the emerging industries dependent on such a map, none are more invested in seeing this concept emerge than those within the AR landscape. Apple, for example, is not-so-secretly developing a pair of AR glasses, which they hope will deliver a mainstream turning point for the technology.

For Apple’s AR devices to work as anticipated, they will require virtual maps of the world, a concept AR insiders call the “AR cloud,” which is synonymous with the “mirrorworld” concept. These maps will be two things. First, they will be a tool that creators use to place AR content in very specific locations; like a world canvas to paint on. Second, they will help AR devices both locate and understand the world around them so they can render content in a believable way.

Imagine walking down a street wanting to check the trading hours of a local business. Instead of pulling out your phone to do a tedious search online, you conduct the equivalent of a visual google search simply by gazing at the store. Albeit a trivial example, the AR cloud represents an entirely non-trivial new way of managing how we organize the world’s information. Access to knowledge can be shifted away from the faraway monitors in our pocket, to its relevant real-world location.

Ultimately this describes a blurring of physical and digital infrastructure. Our public and private spaces will thus be comprised equally of both.

No example demonstrates this idea better than Pokémon Go. The game is straightforward enough; users capture virtual characters scattered around the real world. Today, the game relies on traditional GPS technology to place its characters, but GPS is accurate only to within a few meters of a location. For a car navigating on a highway or locating Pikachus in the world, that level of precision is sufficient. For drone deliveries, driverless cars, or placing a Pikachu in a specific location, say on a tree branch in a park, GPS isn’t accurate enough. As astonishing as it may seem, many experimental AR cloud concepts, even entirely mapped cities, are location specific down to the centimeter.

Niantic, the $4 billion publisher behind Pokémon Go, is aggressively working on developing a crowd-sourced approach to building better AR Cloud maps by encouraging their users to scan the world for them. Their recent acquisition of 6D.ai, a mapping software company developed by the University of Oxford’s Victor Prisacariu through his work at Oxford’s Active Vision Lab, indicates Niantic’s ambition to compete with the tech giants in this space.

With 6D.ai’s technology, Niantic is developing the in-house ability to generate their own 3D maps while gaining better semantic understanding of the world. By going beyond just knowing there’s a temporary collection of orange cones in a certain location, for example, the game may one day understand the meaning behind this; that a temporary construction zone means no Pokémon should spawn here to avoid drawing players to this location.

Niantic is not the only company working on this. Many of the big tech firms you would expect have entire teams focused on map data. Facebook, for example, recently acquired the UK-based Scape technologies, a computer vision startup mapping entire cities with centimeter precision.

As our digital maps of the world improve, expect a relentless and justified discussion of privacy concerns as well. How will society react to the idea of a real-time 3D map of their bedroom living on a Facebook or Amazon server? Those horrified by the use of facial recognition AI being used in public spaces are unlikely to find comfort in the idea of a machine-readable world subject to infinite monitoring.

The ability to build high-precision maps of the world could reshape the way we engage with our planet and promises to be one of the biggest technology developments of the next decade. While these maps may stay hidden as behind-the-scenes infrastructure powering much flashier technologies that capture the world’s attention, they will soon prop up large portions of our technological future.

Keep that in mind when a car with no driver is sharing your road.

Image credit: sergio souza / Pexels Continue reading

Posted in Human Robots

#437882 Video Friday: MIT Mini-Cheetah Robots ...

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):

ICCR 2020 – December 26-29, 2020 – [Online Conference]
HRI 2021 – March 8-11, 2021 – [Online Conference]
RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
Let us know if you have suggestions for next week, and enjoy today's videos.

What a lovely Christmas video from Norlab.

[ Norlab ]

Thanks Francois!

MIT Mini-Cheetahs are looking for a new home. Our new cheetah cubs, born at NAVER LABS, are for the MIT Mini-Cheetah workshop. MIT professor Sangbae Kim and his research team are supporting joint research by distributing Mini-Cheetahs to researchers all around the world.

[ NAVER Labs ]

For several years, NVIDIA’s research teams have been working to leverage GPU technology to accelerate reinforcement learning (RL). As a result of this promising research, NVIDIA is pleased to announce a preview release of Isaac Gym – NVIDIA’s physics simulation environment for reinforcement learning research. RL-based training is now more accessible as tasks that once required thousands of CPU cores can now instead be trained using a single GPU.

[ NVIDIA ]

At SINTEF in Norway, they're working on ways of using robots to keep tabs on giant floating cages of tasty fish:

One of the tricky things about operating robots in an environment like this is localization, so SINTEF is working on a solution that uses beacons:

While that video shows a lot of simulation (because otherwise there are tons of fish in the way), we're told that the autonomous navigation has been successfully demonstrated with an ROV in “a full scale fish farm with up to 200.000 salmon swimming around the robot.”

[ SINTEF ]

Thanks Eleni!

We’ve been getting ready for the snow in the most BG way possible. Wishing all of you a happy and healthy holiday season.

[ Berkshire Grey ]

ANYbotics doesn’t care what time of the year it is, so Happy Easter!

And here's a little bit about why ANYmal C looks the way it does.

[ ANYbotics ]

Robert “Buz” Chmielewski is using two modular prosthetic limbs developed by APL to feed himself dessert. Smart software puts his utensils in roughly the right spot, and then Buz uses his brain signals to cut the food with knife and fork. Once he is done cutting, the software then brings the food near his mouth, where he again uses brain signals to bring the food the last several inches to his mouth so that he can eat it.

[ JHUAPL ]

Introducing VESPER: a new military-grade small drone that is designed, sourced and built in the United States. Vesper offers a 50-minutes flight time, with speeds up to 45 mph (72 kph) and a total flight range of 25 miles (45 km). The magnetic snap-together architecture enables extremely fast transitions: the battery, props and rotor set can each be swapped in <5 seconds.

[ Vantage Robotics ]

In this video, a multi-material robot simulator is used to design a shape-changing robot, which is then transferred to physical hardware. The simulated and real robots can use shape change to switch between rolling gaits and inchworm gaits, to locomote in multiple environments.

[ Yale Faboratory ]

Get a preview of the cave environments that are being used to inspire the Final Event competition course of the DARPA Subterranean Challenge. In the Final Event, teams will deploy their robots to rapidly map, navigate, and search in competition courses that combine elements of man-made tunnel systems, urban underground, and natural cave networks!

The reason to pay attention this particular video is that it gives us some idea of what DARPA means when they say "cave."

[ SubT ]

MQ25 takes another step toward unmanned aerial refueling for the U.S. Navy. The MQ-25 test asset has flown for the first time with an aerial refueling pod containing the hose and basket that will make it an aerial refueler.

[ Boeing ]

We present a unified model-based and data-driven approach for quadrupedal planning and control to achieve dynamic locomotion over uneven terrain. We utilize on-board proprioceptive and exteroceptive feedback to map sensory information and desired base velocity commands into footstep plans using a reinforcement learning (RL) policy trained in simulation over a wide range of procedurally generated terrains.

[ DRS ]

The video shows the results of the German research project RoPHa. Within the project, the partners developed technologies for two application scenarios with the service robot Care-O-bot 4 in order to support people in need of help when eating.

[ RoPHa Project ]

Thanks Jenny!

This looks like it would be fun, if you are a crazy person.

[ Team BlackSheep ]

Robot accuracy is the limiting factor in many industrial applications. Manufacturers often only specify the pose repeatability values of their robotic systems. Fraunhofer IPA has set up a testing environment for automated measuring of accuracy performance criteria of industrial robots. Following the procedures defined in norm ISO 9283 allows generating reliable and repeatable results. They can be the basis for targeted measures increasing the robotic system’s accuracy.

[ Fraunhofer ]

Thanks Jenny!

The IEEE Women in Engineering – Robotics and Automation Society (WIE-RAS) hosted an online panel on best practices for teaching robotics. The diverse panel boasts experts in robotics education from a variety of disciplines, institutions, and areas of expertise.

[ IEEE RAS ]

Northwestern researchers have developed a first-of-its-kind soft, aquatic robot that is powered by light and rotating magnetic fields. These life-like robotic materials could someday be used as "smart" microscopic systems for production of fuels and drugs, environmental cleanup or transformative medical procedures.

[ Northwestern ]

Tech United Eindhoven's soccer robots now have eight wheels instead of four wheels, making them tweleve times better, if my math is right.

[ TU Eindhoven ] Continue reading

Posted in Human Robots

#437872 AlphaFold Proves That AI Can Crack ...

Any successful implementation of artificial intelligence hinges on asking the right questions in the right way. That’s what the British AI company DeepMind (a subsidiary of Alphabet) accomplished when it used its neural network to tackle one of biology’s grand challenges, the protein-folding problem. Its neural net, known as AlphaFold, was able to predict the 3D structures of proteins based on their amino acid sequences with unprecedented accuracy.

AlphaFold’s predictions at the 14th Critical Assessment of protein Structure Prediction (CASP14) were accurate to within an atom’s width for most of the proteins. The competition consisted of blindly predicting the structure of proteins that have only recently been experimentally determined—with some still awaiting determination.

Called the building blocks of life, proteins consist of 20 different amino acids in various combinations and sequences. A protein's biological function is tied to its 3D structure. Therefore, knowledge of the final folded shape is essential to understanding how a specific protein works—such as how they interact with other biomolecules, how they may be controlled or modified, and so on. “Being able to predict structure from sequence is the first real step towards protein design,” says Janet M. Thornton, director emeritus of the European Bioinformatics Institute. It also has enormous benefits in understanding disease-causing pathogens. For instance, at the moment only about 18 of the 26 proteins in the SARS-CoV-2 virus are known.

Predicting a protein’s 3D structure is a computational nightmare. In 1969 Cyrus Levinthal estimated that there are 10300 possible conformational combinations for a single protein, which would take longer than the age of the known universe to evaluate by brute force calculation. AlphaFold can do it in a few days.

As scientific breakthroughs go, AlphaFold’s discovery is right up there with the likes of James Watson and Francis Crick’s DNA double-helix model, or, more recently, Jennifer Doudna and Emmanuelle Charpentier’s CRISPR-Cas9 genome editing technique.

How did a team that just a few years ago was teaching an AI to master a 3,000-year-old game end up training one to answer a question plaguing biologists for five decades? That, says Briana Brownell, data scientist and founder of the AI company PureStrategy, is the beauty of artificial intelligence: The same kind of algorithm can be used for very different things.

“Whenever you have a problem that you want to solve with AI,” she says, “you need to figure out how to get the right data into the model—and then the right sort of output that you can translate back into the real world.”

DeepMind’s success, she says, wasn’t so much a function of picking the right neural nets but rather “how they set up the problem in a sophisticated enough way that the neural network-based modeling [could] actually answer the question.”

AlphaFold showed promise in 2018, when DeepMind introduced a previous iteration of their AI at CASP13, achieving the highest accuracy among all participants. The team had trained its to model target shapes from scratch, without using previously solved proteins as templates.

For 2020 they deployed new deep learning architectures into the AI, using an attention-based model that was trained end-to-end. Attention in a deep learning network refers to a component that manages and quantifies the interdependence between the input and output elements, as well as between the input elements themselves.

The system was trained on public datasets of the approximately 170,000 known experimental protein structures in addition to databases with protein sequences of unknown structures.

“If you look at the difference between their entry two years ago and this one, the structure of the AI system was different,” says Brownell. “This time, they’ve figured out how to translate the real world into data … [and] created an output that could be translated back into the real world.”

Like any AI system, AlphaFold may need to contend with biases in the training data. For instance, Brownell says, AlphaFold is using available information about protein structure that has been measured in other ways. However, there are also many proteins with as yet unknown 3D structures. Therefore, she says, a bias could conceivably creep in toward those kinds of proteins that we have more structural data for.

Thornton says it’s difficult to predict how long it will take for AlphaFold’s breakthrough to translate into real-world applications.

“We only have experimental structures for about 10 per cent of the 20,000 proteins [in] the human body,” she says. “A powerful AI model could unveil the structures of the other 90 per cent.”

Apart from increasing our understanding of human biology and health, she adds, “it is the first real step toward… building proteins that fulfill a specific function. From protein therapeutics to biofuels or enzymes that eat plastic, the possibilities are endless.” Continue reading

Posted in Human Robots

#437869 Video Friday: Japan’s Gundam Robot ...

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):

ACRA 2020 – December 8-10, 2020 – [Online]
Let us know if you have suggestions for next week, and enjoy today’s videos.

Another BIG step for Japan’s Gundam project.

[ Gundam Factory ]

We present an interactive design system that allows users to create sculpting styles and fabricate clay models using a standard 6-axis robot arm. Given a general mesh as input, the user iteratively selects sub-areas of the mesh through decomposition and embeds the design expression into an initial set of toolpaths by modifying key parameters that affect the visual appearance of the sculpted surface finish. We demonstrate the versatility of our approach by designing and fabricating different sculpting styles over a wide range of clay models.

[ Disney Research ]

China’s Chang’e-5 completed the drilling, sampling and sealing of lunar soil at 04:53 BJT on Wednesday, marking the first automatic sampling on the Moon, the China National Space Administration (CNSA) announced Wednesday.

[ CCTV ]

Red Hat’s been putting together an excellent documentary on Willow Garage and ROS, and all five parts have just been released. We posted Part 1 a little while ago, so here’s Part 2 and Part 3.

Parts 4 and 5 are at the link below!

[ Red Hat ]

Congratulations to ANYbotics on a well-deserved raise!

ANYbotics has origins in the Robotic Systems Lab at ETH Zurich, and ANYmal’s heritage can be traced back at least as far as StarlETH, which we first met at ICRA 2013.

[ ANYbotics ]

Most conventional robots are working with 0.05-0.1mm accuracy. Such accuracy requires high-end components like low-backlash gears, high-resolution encoders, complicated CNC parts, powerful motor drives, etc. Those in combination end up an expensive solution, which is either unaffordable or unnecessary for many applications. As a result, we found the Apicoo Robotics to provide our customers solutions with a much lower cost and higher stability.

[ Apicoo Robotics ]

The Skydio 2 is an incredible drone that can take incredible footage fully autonomously, but it definitely helps if you do incredible things in incredible places.

[ Skydio ]

Jueying is the first domestic sensitive quadruped robot for industry applications and scenarios. It can coordinate (replace) humans to reach any place that can be reached. It has superior environmental adaptability, excellent dynamic balance capabilities and precise Environmental perception capabilities. By carrying functional modules for different application scenarios in the safe load area, the mobile superiority of the quadruped robot can be organically integrated with the commercialization of functional modules, providing smart factories, smart parks, scene display and public safety application solutions.

[ DeepRobotics ]

We have developed semi-autonomous quadruped robot, called LASER-D (Legged-Agile-Smart-Efficient Robot for Disinfection) for performing disinfection in cluttered environments. The robot is equipped with a spray-based disinfection system and leverages the body motion to controlling the spray action without the need for an extra stabilization mechanism. The system includes an image processing capability to verify disinfected regions with high accuracy. This system allows the robot to successfully carry out effective disinfection tasks while safely traversing through cluttered environments, climb stairs/slopes, and navigate on slippery surfaces.

[ USC Viterbi ]

We propose the “multi-vision hand”, in which a number of small high-speed cameras are mounted on the robot hand of a common 7 degrees-of-freedom robot. Also, we propose visual-servoing control by using a multi-vision system that combines the multi-vision hand and external fixed high-speed cameras. The target task was ball catching motion, which requires high-speed operation. In the proposed catching control, the catch position of the ball, which is estimated by the external fixed high-speed cameras, is corrected by the multi-vision hand in real-time.

More details available through IROS on-demand.

[ Namiki Laboratory ]

Shunichi Kurumaya wrote in to share his work on PneuFinger, a pneumatically actuated compliant robotic gripping system.

[ Nakamura Lab ]

Thanks Shunichi!

Motivated by insights into the human teaching process, we introduce a method for incorporating unstructured natural language into imitation learning. At training time, the expert can provide demonstrations along with verbal descriptions in order to describe the underlying intent, e.g., “Go to the large green bowl’’. The training process, then, interrelates the different modalities to encode the correlations between language, perception, and motion. The resulting language-conditioned visuomotor policies can be conditioned at run time on new human commands and instructions, which allows for more fine-grained control over the trained policies while also reducing situational ambiguity.

[ ASU ]

Thanks Heni!

Gita is on sale for the holidays for only $2,000.

[ Gita ]

This video introduces a computational approach for routing thin artificial muscle actuators through hyperelastic soft robots, in order to achieve a desired deformation behavior. Provided with a robot design, and a set of example deformations, we continuously co-optimize the routing of actuators, and their actuation, to approximate example deformations as closely as possible.

[ Disney Research ]

Researchers and mountain rescuers in Switzerland are making huge progress in the field of autonomous drones as the technology becomes more in-demand for global search-and-rescue operations.

[ SWI ]

This short clip of the Ghost Robotics V60 features an interesting, if awkward looking, righting behavior at the end.

[ Ghost Robotics ]

Europe’s Rosalind Franklin ExoMars rover has a younger ’sibling’, ExoMy. The blueprints and software for this mini-version of the full-size Mars explorer are available for free so that anyone can 3D print, assemble and program their own ExoMy.

[ ESA ]

The holiday season is here, and with the added impact of Covid-19 consumer demand is at an all-time high. Berkshire Grey is the partner that today’s leading organizations turn to when it comes to fulfillment automation.

[ Berkshire Grey ]

Until very recently, the vast majority of studies and reports on the use of cargo drones for public health were almost exclusively focused on the technology. The driving interest from was on the range that these drones could travel, how much they could carry and how they worked. Little to no attention was placed on the human side of these projects. Community perception, community engagement, consent and stakeholder feedback were rarely if ever addressed. This webinar presents the findings from a very recent study that finally sheds some light on the human side of drone delivery projects.

[ WeRobotics ] Continue reading

Posted in Human Robots