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#435308 Brain-Machine Interfaces Are Getting ...

Posted on July 26, 2019 by Android

Elon Musk grabbed a lot of attention with his July 16 announcement that his company Neuralink plans to implant electrodes into the brains of people with paralysis by next year. Their first goal is to create assistive technology to help people who can’t move or are unable to communicate.

If you haven’t been paying attention, brain-machine interfaces (BMIs) that allow people to control robotic arms with their thoughts might sound like science fiction. But science and engineering efforts have already turned it into reality.

In a few research labs around the world, scientists and physicians have been implanting devices into the brains of people who have lost the ability to control their arms or hands for over a decade. In our own research group at the University of Pittsburgh, we’ve enabled people with paralyzed arms and hands to control robotic arms that allow them to grasp and move objects with relative ease. They can even experience touch-like sensations from their own hand when the robot grasps objects.

At its core, a BMI is pretty straightforward. In your brain, microscopic cells called neurons are sending signals back and forth to each other all the time. Everything you think, do and feel as you interact with the world around you is the result of the activity of these 80 billion or so neurons.

If you implant a tiny wire very close to one of these neurons, you can record the electrical activity it generates and send it to a computer. Record enough of these signals from the right area of the brain and it becomes possible to control computers, robots, or anything else you might want, simply by thinking about moving. But doing this comes with tremendous technical challenges, especially if you want to record from hundreds or thousands of neurons.

What Neuralink Is Bringing to the Table
Elon Musk founded Neuralink in 2017, aiming to address these challenges and raise the bar for implanted neural interfaces.

Perhaps the most impressive aspect of Neuralink’s system is the breadth and depth of their approach. Building a BMI is inherently interdisciplinary, requiring expertise in electrode design and microfabrication, implantable materials, surgical methods, electronics, packaging, neuroscience, algorithms, medicine, regulatory issues, and more. Neuralink has created a team that spans most, if not all, of these areas.

With all of this expertise, Neuralink is undoubtedly moving the field forward, and improving their technology rapidly. Individually, many of the components of their system represent significant progress along predictable paths. For example, their electrodes, that they call threads, are very small and flexible; many researchers have tried to harness those properties to minimize the chance the brain’s immune response would reject the electrodes after insertion. Neuralink has also developed high-performance miniature electronics, another focus area for labs working on BMIs.

Often overlooked in academic settings, however, is how an entire system would be efficiently implanted in a brain.

Neuralink’s BMI requires brain surgery. This is because implanted electrodes that are in intimate contact with neurons will always outperform non-invasive electrodes where neurons are far away from the electrodes sitting outside the skull. So, a critical question becomes how to minimize the surgical challenges around getting the device into a brain.

Maybe the most impressive aspect of Neuralink’s announcement was that they created a 3,000-electrode neural interface where electrodes could be implanted at a rate of between 30 and 200 per minute. Each thread of electrodes is implanted by a sophisticated surgical robot that essentially acts like a sewing machine. This all happens while specifically avoiding blood vessels that blanket the surface of the brain. The robotics and imaging that enable this feat, with tight integration to the entire device, is striking.

Neuralink has thought through the challenge of developing a clinically viable BMI from beginning to end in a way that few groups have done, though they acknowledge that many challenges remain as they work towards getting this technology into human patients in the clinic.

Figuring Out What More Electrodes Gets You
The quest for implantable devices with thousands of electrodes is not only the domain of private companies. DARPA, the NIH BRAIN Initiative, and international consortiums are working on neurotechnologies for recording and stimulating in the brain with goals of tens of thousands of electrodes. But what might scientists do with the information from 1,000, 3,000, or maybe even 100,000 neurons?

At some level, devices with more electrodes might not actually be necessary to have a meaningful impact in people’s lives. Effective control of computers for access and communication, of robotic limbs to grasp and move objects as well as of paralyzed muscles is already happening—in people. And it has been for a number of years.

Since the 1990s, the Utah Array, which has just 100 electrodes and is manufactured by Blackrock Microsystems, has been a critical device in neuroscience and clinical research. This electrode array is FDA-cleared for temporary neural recording. Several research groups, including our own, have implanted Utah Arrays in people that lasted multiple years.

Currently, the biggest constraints are related to connectors, electronics, and system-level engineering, not the implanted electrode itself—although increasing the electrodes’ lifespan to more than five years would represent a significant advance. As those technical capabilities improve, it might turn out that the ability to accurately control computers and robots is limited more by scientists’ understanding of what the neurons are saying—that is, the neural code—than by the number of electrodes on the device.

Even the most capable implanted system, and maybe the most capable devices researchers can reasonably imagine, might fall short of the goal of actually augmenting skilled human performance. Nevertheless, Neuralink’s goal of creating better BMIs has the potential to improve the lives of people who can’t move or are unable to communicate. Right now, Musk’s vision of using BMIs to meld physical brains and intelligence with artificial ones is no more than a dream.

So, what does the future look like for Neuralink and other groups creating implantable BMIs? Devices with more electrodes that last longer and are connected to smaller and more powerful wireless electronics are essential. Better devices themselves, however, are insufficient. Continued public and private investment in companies and academic research labs, as well as innovative ways for these groups to work together to share technologies and data, will be necessary to truly advance scientists’ understanding of the brain and deliver on the promise of BMIs to improve peoples’ lives.

While researchers need to keep the future societal implications of advanced neurotechnologies in mind—there’s an essential role for ethicists and regulation—BMIs could be truly transformative as they help more people overcome limitations caused by injury or disease in the brain and body.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Image Credit: UPMC/Pitt Health Sciences, / CC BY-NC-ND Continue reading →

Posted in Human Robots

#435260 How Tech Can Help Curb Emissions by ...

Posted on July 16, 2019 by Android

Trees are a low-tech, high-efficiency way to offset much of humankind’s negative impact on the climate. What’s even better, we have plenty of room for a lot more of them.

A new study conducted by researchers at Switzerland’s ETH-Zürich, published in Science, details how Earth could support almost an additional billion hectares of trees without the new forests pushing into existing urban or agricultural areas. Once the trees grow to maturity, they could store more than 200 billion metric tons of carbon.

Great news indeed, but it still leaves us with some huge unanswered questions. Where and how are we going to plant all the new trees? What kind of trees should we plant? How can we ensure that the new forests become a boon for people in those areas?

Answers to all of the above likely involve technology.

Math + Trees = Challenges
The ETH-Zürich research team combined Google Earth mapping software with a database of nearly 80,000 existing forests to create a predictive model for optimal planting locations. In total, 0.9 billion hectares of new, continuous forest could be planted. Once mature, the 500 billion new trees in these forests would be capable of storing about two-thirds of the carbon we have emitted since the industrial revolution.

Other researchers have noted that the study may overestimate how efficient trees are at storing carbon, as well as underestimate how much carbon humans have emitted over time. However, all seem to agree that new forests would offset much of our cumulative carbon emissions—still an impressive feat as the target of keeping global warming this century at under 1.5 degrees Celsius becomes harder and harder to reach.

Recently, there was a story about a Brazilian couple who replanted trees in the valley where they live. The couple planted about 2.7 million trees in two decades. Back-of-the-napkin math shows that they on average planted 370 trees a day, meaning planting 500 billion trees would take about 3.7 million years. While an over-simplification, the point is that planting trees by hand is not realistic. Even with a million people going at a rate of 370 trees a day, it would take 83 years. Current technologies are also not likely to be able to meet the challenge, especially in remote locations.

Tree-Bombing Drones
Technology can speed up the planting process, including a new generation of drones that take tree planting to the skies. Drone planting generally involves dropping biodegradable seed pods at a designated area. The pods dissolve over time, and the tree seeds grow in the earth below. DroneSeed is one example; its 55-pound drones can plant up to 800 seeds an hour. Another startup, Biocarbon Engineering, has used various techniques, including drones, to plant 38 different species of trees across three continents.

Drone planting has distinct advantages when it comes to planting in hard-to-access areas—one example is mangrove forests, which are disappearing rapidly, increasing the risk of floods and storm surges.

Challenges include increasing the range and speed of drone planting, and perhaps most importantly, the success rate, as automatic planting from a height is still likely to be less accurate when it comes to what depth the tree saplings are planted. However, drones are already showing impressive numbers for sapling survival rates.

AI, Sensors, and Eye-In-the-Sky
Planting the trees is the first step in a long road toward an actual forest. Companies are leveraging artificial intelligence and satellite imagery in a multitude of ways to increase protection and understanding of forested areas.

20tree.ai, a Portugal-based startup, uses AI to analyze satellite imagery and monitor the state of entire forests at a fraction of the cost of manual monitoring. The approach can lead to faster identification of threats like pest infestation and a better understanding of the state of forests.

AI can also play a pivotal role in protecting existing forest areas by predicting where deforestation is likely to occur.

Closer to the ground—and sometimes in it—new networks of sensors can provide detailed information about the state and needs of trees. One such project is Trace, where individual trees are equipped with a TreeTalker, an internet of things-based device that can provide real-time monitoring of the tree’s functions and well-being. The information can be used to, among other things, optimize the use of available resources, such as providing the exact amount of water a tree needs.

Budding Technologies Are Controversial
Trees are in many ways fauna’s marathon runners—slow-growing and sturdy, but still susceptible to sickness and pests. Many deforested areas are likely not as rich in nutrients as they once were, which could slow down reforestation. Much of the positive impact that said trees could have on carbon levels in the atmosphere is likely decades away.

Bioengineering, for example through CRISPR, could provide solutions, making trees more resistant and faster-growing. Such technologies are being explored in relation to Ghana’s at-risk cocoa trees. Other exponential technologies could also hold much future potential—for instance micro-robots to assist the dwindling number of bees with pollination.

These technologies remain mired in controversy, and perhaps rightfully so. Bioengineering’s massive potential is for many offset by the inherent risks of engineered plants out-competing existing fauna or growing beyond our control. Micro-robots for pollination may solve a problem, but don’t do much to address the root cause: that we seem to be disrupting and destroying integral parts of natural cycles.

Tech Not The Whole Answer
So, is it realistic to plant 500 billion new trees? The short answer would be that yes, it’s possible—with the help of technology.

However, there are many unanswered challenges. For example, many of areas identified by the ETH-Zürich research team are not readily available for reforestation. Some are currently reserved for grazing, others owned by private entities, and others again are located in remote areas or areas prone to political instability, beyond the reach of most replanting efforts.

If we do wish to plant 500 billion trees to offset some of the negative impacts we have had on the planet, we might well want to combine the best of exponential technology with reforestation as well as a move to other forms of agriculture.

Such an approach might also help address a major issue: that few of the proposed new forests will likely succeed without ensuring that people living in and around the areas where reforestation takes place become involved, and can reap rewards from turning arable land into forests.

Image Credit: Lillac/Shutterstock.com Continue reading →

Posted in Human Robots

#435224 Can AI Save the Internet from Fake News?

Posted on June 30, 2019 by Android

There’s an old proverb that says “seeing is believing.” But in the age of artificial intelligence, it’s becoming increasingly difficult to take anything at face value—literally.

The rise of so-called “deepfakes,” in which different types of AI-based techniques are used to manipulate video content, has reached the point where Congress held its first hearing last month on the potential abuses of the technology. The congressional investigation coincided with the release of a doctored video of Facebook CEO Mark Zuckerberg delivering what appeared to be a sinister speech.

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Scientists are scrambling for solutions on how to combat deepfakes, while at the same time others are continuing to refine the techniques for less nefarious purposes, such as automating video content for the film industry.

At one end of the spectrum, for example, researchers at New York University’s Tandon School of Engineering have proposed implanting a type of digital watermark using a neural network that can spot manipulated photos and videos.

The idea is to embed the system directly into a digital camera. Many smartphone cameras and other digital devices already use AI to boost image quality and make other corrections. The authors of the study out of NYU say their prototype platform increased the chances of detecting manipulation from about 45 percent to more than 90 percent without sacrificing image quality.

On the other hand, researchers at Carnegie Mellon University recently hit on a technique for automatically and rapidly converting large amounts of video content from one source into the style of another. In one example, the scientists transferred the facial expressions of comedian John Oliver onto the bespectacled face of late night show host Stephen Colbert.

The CMU team says the method could be a boon to the movie industry, such as by converting black and white films to color, though it also conceded that the technology could be used to develop deepfakes.

Words Matter with Fake News
While the current spotlight is on how to combat video and image manipulation, a prolonged trench warfare on fake news is being fought by academia, nonprofits, and the tech industry.

This isn’t the fake news that some have come to use as a knee-jerk reaction to fact-based information that might be less than flattering to the subject of the report. Rather, fake news is deliberately-created misinformation that is spread via the internet.

In a recent Pew Research Center poll, Americans said fake news is a bigger problem than violent crime, racism, and terrorism. Fortunately, many of the linguistic tools that have been applied to determine when people are being deliberately deceitful can be baked into algorithms for spotting fake news.

That’s the approach taken by a team at the University of Michigan (U-M) to develop an algorithm that was better than humans at identifying fake news—76 percent versus 70 percent—by focusing on linguistic cues like grammatical structure, word choice, and punctuation.

For example, fake news tends to be filled with hyperbole and exaggeration, using terms like “overwhelming” or “extraordinary.”

“I think that’s a way to make up for the fact that the news is not quite true, so trying to compensate with the language that’s being used,” Rada Mihalcea, a computer science and engineering professor at U-M, told Singularity Hub.

The paper “Automatic Detection of Fake News” was based on the team’s previous studies on how people lie in general, without necessarily having the intention of spreading fake news, she said.

“Deception is a complicated and complex phenomenon that requires brain power,” Mihalcea noted. “That often results in simpler language, where you have shorter sentences or shorter documents.”

AI Versus AI
While most fake news is still churned out by humans with identifiable patterns of lying, according to Mihalcea, other researchers are already anticipating how to detect misinformation manufactured by machines.

A group led by Yejin Choi, with the Allen Institute of Artificial Intelligence and the University of Washington in Seattle, is one such team. The researchers recently introduced the world to Grover, an AI platform that is particularly good at catching autonomously-generated fake news because it’s equally good at creating it.

“This is due to a finding that is perhaps counterintuitive: strong generators for neural fake news are themselves strong detectors of it,” wrote Rowan Zellers, a PhD student and team member, in a Medium blog post. “A generator of fake news will be most familiar with its own peculiarities, such as using overly common or predictable words, as well as the peculiarities of similar generators.”

The team found that the best current discriminators can classify neural fake news from real, human-created text with 73 percent accuracy. Grover clocks in with 92 percent accuracy based on a training set of 5,000 neural network-generated fake news samples. Zellers wrote that Grover got better at scale, identifying 97.5 percent of made-up machine mumbo jumbo when trained on 80,000 articles.

It performed almost as well against fake news created by a powerful new text-generation system called GPT-2 built by OpenAI, a nonprofit research lab founded by Elon Musk, classifying 96.1 percent of the machine-written articles.

OpenAI had so feared that the platform could be abused that it has only released limited versions of the software. The public can play with a scaled-down version posted by a machine learning engineer named Adam King, where the user types in a short prompt and GPT-2 bangs out a short story or poem based on the snippet of text.

No Silver AI Bullet
While real progress is being made against fake news, the challenges of using AI to detect and correct misinformation are abundant, according to Hugo Williams, outreach manager for Logically, a UK-based startup that is developing different detectors using elements of deep learning and natural language processing, among others. He explained that the Logically models analyze information based on a three-pronged approach.

Publisher metadata: Is the article from a known, reliable, and trustworthy publisher with a history of credible journalism?
Network behavior: Is the article proliferating through social platforms and networks in ways typically associated with misinformation?
Content: The AI scans articles for hundreds of known indicators typically found in misinformation.

“There is no single algorithm which is capable of doing this,” Williams wrote in an email to Singularity Hub. “Even when you have a collection of different algorithms which—when combined—can give you relatively decent indications of what is unreliable or outright false, there will always need to be a human layer in the pipeline.”

The company released a consumer app in India back in February just before that country’s election cycle that was a “great testing ground” to refine its technology for the next app release, which is scheduled in the UK later this year. Users can submit articles for further scrutiny by a real person.

“We see our technology not as replacing traditional verification work, but as a method of simplifying and streamlining a very manual process,” Williams said. “In doing so, we’re able to publish more fact checks at a far quicker pace than other organizations.”

“With heightened analysis and the addition of more contextual information around the stories that our users are reading, we are not telling our users what they should or should not believe, but encouraging critical thinking based upon reliable, credible, and verified content,” he added.

AI may never be able to detect fake news entirely on its own, but it can help us be smarter about what we read on the internet.

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Posted in Human Robots

#435174 Revolt on the Horizon? How Young People ...

Posted on June 6, 2019 by Android

As digital technologies facilitate the growth of both new and incumbent organizations, we have started to see the darker sides of the digital economy unravel. In recent years, many unethical business practices have been exposed, including the capture and use of consumers’ data, anticompetitive activities, and covert social experiments.

But what do young people who grew up with the internet think about this development? Our research with 400 digital natives—19- to 24-year-olds—shows that this generation, dubbed “GenTech,” may be the one to turn the digital revolution on its head. Our findings point to a frustration and disillusionment with the way organizations have accumulated real-time information about consumers without their knowledge and often without their explicit consent.

Many from GenTech now understand that their online lives are of commercial value to an array of organizations that use this insight for the targeting and personalization of products, services, and experiences.

This era of accumulation and commercialization of user data through real-time monitoring has been coined “surveillance capitalism” and signifies a new economic system.

Artificial Intelligence
A central pillar of the modern digital economy is our interaction with artificial intelligence (AI) and machine learning algorithms. We found that 47 percent of GenTech do not want AI technology to monitor their lifestyle, purchases, and financial situation in order to recommend them particular things to buy.

In fact, only 29 percent see this as a positive intervention. Instead, they wish to maintain a sense of autonomy in their decision making and have the opportunity to freely explore new products, services, and experiences.

As individuals living in the digital age, we constantly negotiate with technology to let go of or retain control. This pendulum-like effect reflects the ongoing battle between humans and technology.

My Life, My Data?
Our research also reveals that 54 percent of GenTech are very concerned about the access organizations have to their data, while only 19 percent were not worried. Despite the EU General Data Protection Regulation being introduced in May 2018, this is still a major concern, grounded in a belief that too much of their data is in the possession of a small group of global companies, including Google, Amazon, and Facebook. Some 70 percent felt this way.

In recent weeks, both Facebook and Google have vowed to make privacy a top priority in the way they interact with users. Both companies have faced public outcry for their lack of openness and transparency when it comes to how they collect and store user data. It wasn’t long ago that a hidden microphone was found in one of Google’s home alarm products.

Google now plans to offer auto-deletion of users’ location history data, browsing, and app activity as well as extend its “incognito mode” to Google Maps and search. This will enable users to turn off tracking.

At Facebook, CEO Mark Zuckerberg is keen to reposition the platform as a “privacy focused communications platform” built on principles such as private interactions, encryption, safety, interoperability (communications across Facebook-owned apps and platforms), and secure data storage. This will be a tough turnaround for the company that is fundamentally dependent on turning user data into opportunities for highly individualized advertising.

Privacy and transparency are critically important themes for organizations today, both for those that have “grown up” online as well as the incumbents. While GenTech want organizations to be more transparent and responsible, 64 percent also believe that they cannot do much to keep their data private. Being tracked and monitored online by organizations is seen as part and parcel of being a digital consumer.

Despite these views, there is a growing revolt simmering under the surface. GenTech want to take ownership of their own data. They see this as a valuable commodity, which they should be given the opportunity to trade with organizations. Some 50 percent would willingly share their data with companies if they got something in return, for example a financial incentive.

Rewiring the Power Shift
GenTech are looking to enter into a transactional relationship with organizations. This reflects a significant change in attitudes from perceiving the free access to digital platforms as the “product” in itself (in exchange for user data), to now wishing to use that data to trade for explicit benefits.

This has created an opportunity for companies that seek to empower consumers and give them back control of their data. Several companies now offer consumers the opportunity to sell the data they are comfortable sharing or take part in research that they get paid for. More and more companies are joining this space, including People.io, Killi, and Ocean Protocol.

Sir Tim Berners Lee, the creator of the world wide web, has also been working on a way to shift the power from organizations and institutions back to citizens and consumers. The platform, Solid, offers users the opportunity to be in charge of where they store their data and who can access it. It is a form of re-decentralization.

The Solid POD (Personal Online Data storage) is a secure place on a hosted server or the individual’s own server. Users can grant apps access to their POD as a person’s data is stored centrally and not by an app developer or on an organization’s server. We see this as potentially being a way to let people take back control from technology and other companies.

GenTech have woken up to a reality where a life lived “plugged in” has significant consequences for their individual privacy and are starting to push back, questioning those organizations that have shown limited concern and continue to exercise exploitative practices.

It’s no wonder that we see these signs of revolt. GenTech is the generation with the most to lose. They face a life ahead intertwined with digital technology as part of their personal and private lives. With continued pressure on organizations to become more transparent, the time is now for young people to make their move.

Dr Mike Cooray, Professor of Practice, Hult International Business School and Dr Rikke Duus, Research Associate and Senior Teaching Fellow, UCL

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Posted in Human Robots

#435167 A Closer Look at the Robots Helping Us ...

Posted on June 5, 2019 by Android

Buck Rogers had Twiki. Luke Skywalker palled around with C-3PO and R2-D2. And astronauts aboard the International Space Station (ISS) now have their own robotic companions in space—Astrobee.

A pair of the cube-shaped robots were launched to the ISS during an April re-supply mission and are currently being commissioned for use on the space station. The free-flying space robots, dubbed Bumble and Honey, are the latest generation of robotic machines to join the human crew on the ISS.

Exploration of the solar system and beyond will require autonomous machines that can assist humans with numerous tasks—or go where we cannot. NASA has said repeatedly that robots will be instrumental in future space missions to the moon, Mars, and even to the icy moon Europa.

The Astrobee robots will specifically test robotic capabilities in zero gravity, replacing the SPHERES (Synchronized Position Hold, Engage, Reorient, Experimental Satellite) robots that have been on the ISS for more than a decade to test various technologies ranging from communications to navigation.

The 18-sided robots, each about the size of a volleyball or an oversized Dungeons and Dragons die, use CO2-based cold-gas thrusters for movement and a series of ultrasonic beacons for orientation. The Astrobee robots, on the other hand, can propel themselves autonomously around the interior of the ISS using electric fans and six cameras.

The modular design of the Astrobee robots means they are highly plug-and-play, capable of being reconfigured with different hardware modules. The robots’ software is also open-source, encouraging scientists and programmers to develop and test new algorithms and features.

And, yes, the Astrobee robots will be busy as bees once they are fully commissioned this fall, with experiments planned to begin next year. Scientists hope to learn more about how robots can assist space crews and perform caretaking duties on spacecraft.

Robots Working Together
The Astrobee robots are expected to be joined by a familiar “face” on the ISS later this year—the humanoid robot Robonaut.

Robonaut, also known as R2, was the first US-built robot on the ISS. It joined the crew back in 2011 without legs, which were added in 2014. However, the installation never entirely worked, as R2 experienced power failures that eventually led to its return to Earth last year to fix the problem. If all goes as planned, the space station’s first humanoid robot will return to the ISS to lend a hand to the astronauts and the new robotic arrivals.

In particular, NASA is interested in how the two different robotic platforms can complement each other, with an eye toward outfitting the agency’s proposed lunar orbital space station with various robots that can supplement a human crew.

“We don’t have definite plans for what would happen on the Gateway yet, but there’s a general recognition that intra-vehicular robots are important for space stations,” Astrobee technical lead Trey Smith in the NASA Intelligent Robotics Group told IEEE Spectrum. “And so, it would not be surprising to see a mobile manipulator like Robonaut, and a free flyer like Astrobee, on the Gateway.”

While the focus on R2 has been to test its capabilities in zero gravity and to use it for mundane or dangerous tasks in space, the technology enabling the humanoid robot has proven to be equally useful on Earth.

For example, R2 has amazing dexterity for a robot, with sensors, actuators, and tendons comparable to the nerves, muscles, and tendons in a human hand. Based on that design, engineers are working on a robotic glove that can help factory workers, for instance, do their jobs better while reducing the risk of repetitive injuries. R2 has also inspired development of a robotic exoskeleton for both astronauts in space and paraplegics on Earth.

Working Hard on Soft Robotics
While innovative and technologically sophisticated, Astrobee and Robonaut are typical robots in that neither one would do well in a limbo contest. In other words, most robots are limited in their flexibility and agility based on current hardware and materials.

A subfield of robotics known as soft robotics involves developing robots with highly pliant materials that mimic biological organisms in how they move. Scientists at NASA’s Langley Research Center are investigating how soft robots could help with future space exploration.

Specifically, the researchers are looking at a series of properties to understand how actuators—components responsible for moving a robotic part, such as Robonaut’s hand—can be built and used in space.

The team first 3D prints a mold and then pours a flexible material like silicone into the mold. Air bladders or chambers in the actuator expand and compress using just air.

Some of the first applications of soft robotics sound more tool-like than R2-D2-like. For example, two soft robots could connect to produce a temporary shelter for astronauts on the moon or serve as an impromptu wind shield during one of Mars’ infamous dust storms.

The idea is to use soft robots in situations that are “dangerous, dirty, or dull,” according to Jack Fitzpatrick, a NASA intern working on the soft robotics project at Langley.

Working on Mars
Of course, space robots aren’t only designed to assist humans. In many instances, they are the only option to explore even relatively close celestial bodies like Mars. Four American-made robotic rovers have been used to investigate the fourth planet from the sun since 1997.

Opportunity is perhaps the most famous, covering about 25 miles of terrain across Mars over 15 years. A dust storm knocked it out of commission last year, with NASA officially ending the mission in February.

However, the biggest and baddest of the Mars rovers, Curiosity, is still crawling across the Martian surface, sending back valuable data since 2012. The car-size robot carries 17 cameras, a laser to vaporize rocks for study, and a drill to collect samples. It is on the hunt for signs of biological life.

The next year or two could see a virtual traffic jam of robots to Mars. NASA’s Mars 2020 Rover is next in line to visit the Red Planet, sporting scientific gadgets like an X-ray fluorescence spectrometer for chemical analyses and ground-penetrating radar to see below the Martian surface.

This diagram shows the instrument payload for the Mars 2020 mission. Image Credit: NASA.
Meanwhile, the Europeans have teamed with the Russians on a rover called Rosalind Franklin, named after a famed British chemist, that will drill down into the Martian ground for evidence of past or present life as soon as 2021.

The Chinese are also preparing to begin searching for life on Mars using robots as soon as next year, as part of the country’s Mars Global Remote Sensing Orbiter and Small Rover program. The mission is scheduled to be the first in a series of launches that would culminate with bringing samples back from Mars to Earth.

Perhaps there is no more famous utterance in the universe of science fiction as “to boldly go where no one has gone before.” However, the fact is that human exploration of the solar system and beyond will only be possible with robots of different sizes, shapes, and sophistication.

Image Credit: NASA. Continue reading →

Posted in Human Robots