Tag Archives: planning

#435619 Video Friday: Watch This Robot Dog ...

Posted on September 13, 2019 by Android

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!):

IEEE Africon 2019 – September 25-27, 2019 – Accra, Ghana
RoboBusiness 2019 – October 1-3, 2019 – Santa Clara, CA, USA
ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
ARSO 2019 – October 31-1, 2019 – Beijing, China
ROSCon 2019 – October 31-1, 2019 – Macau
IROS 2019 – November 4-8, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today’s videos.

Team PLUTO (University of Pennsylvania, Ghost Robotics, and Exyn Technologies) put together this video giving us a robot’s-eye-view (or whatever they happen to be using for eyes) of the DARPA Subterranean Challenge tunnel circuits.

[ PLUTO ]

Zhifeng Huang has been improving his jet-stepping humanoid robot, which features new hardware and the ability to take larger and more complex steps.

This video reported the last progress of an ongoing project utilizing ducted-fan propulsion system to improve humanoid robot’s ability in stepping over large ditches. The landing point of the robot’s swing foot can be not only forward but also side direction. With keeping quasi-static balance, the robot was able to step over a ditch with 450mm in width (up to 97% of the robot’s leg’s length) in 3D stepping.

[ Paper ]

Thanks Zhifeng!

These underacuated hands from Matei Ciocarlie’s lab at Columbia are magically able to reconfigure themselves to grasp different object types with just one or two motors.

[ Paper ] via [ ROAM Lab ]

This is one reason we should pursue not “autonomous cars” but “fully autonomous cars” that never require humans to take over. We can’t be trusted.

During our early days as the Google self-driving car project, we invited some employees to test our vehicles on their commutes and weekend trips. What we were testing at the time was similar to the highway driver assist features that are now available on cars today, where the car takes over the boring parts of the driving, but if something outside its ability occurs, the driver has to take over immediately.

What we saw was that our testers put too much trust in that technology. They were doing things like texting, applying makeup, and even falling asleep that made it clear they would not be ready to take over driving if the vehicle asked them to. This is why we believe that nothing short of full autonomy will do.

[ Waymo ]

Buddy is a DIY and fetchingly minimalist social robot (of sorts) that will be coming to Kickstarter this month.

We have created a new arduino kit. His name is Buddy. He is a DIY social robot to serve as a replacement for Jibo, Cozmo, or any of the other bots that are no longer available. Fully 3D printed and supported he adds much more to our series of Arduino STEM robotics kits.

Buddy is able to look around and map his surroundings and react to changes within them. He can be surprised and he will always have a unique reaction to changes. The kit can be built very easily in less than an hour. It is even robust enough to take the abuse that kids can give it in a classroom.

[ Littlebots ]

The android Mindar, based on the Buddhist deity of mercy, preaches sermons at Kodaiji temple in Kyoto, and its human colleagues predict that with artificial intelligence it could one day acquire unlimited wisdom. Developed at a cost of almost $1 million (¥106 million) in a joint project between the Zen temple and robotics professor Hiroshi Ishiguro, the robot teaches about compassion and the dangers of desire, anger and ego.

[ Japan Times ]

I’m not sure whether it’s the sound or what, but this thing scares me for some reason.

[ BIRL ]

This gripper uses magnets as a sort of adjustable spring for dynamic stiffness control, which seems pretty clever.

[ Buffalo ]

What a package of medicine sees while being flown by drone from a hospital to a remote clinic in the Dominican Republic. The drone flew 11 km horizontally and 800 meters vertically, and I can’t even imagine what it would take to make that drive.

[ WeRobotics ]

My first ride in a fully autonomous car was at Stanford in 2009. I vividly remember getting in the back seat of a descendant of Junior, and watching the steering wheel turn by itself as the car executed a perfect parking maneuver. Ten years later, it’s still fun to watch other people have that experience.

[ Waymo ]

Flirtey, the pioneer of the commercial drone delivery industry, has unveiled the much-anticipated first video of its next-generation delivery drone, the Flirtey Eagle. The aircraft designer and manufacturer also unveiled the Flirtey Portal, a sophisticated take off and landing platform that enables scalable store-to-door operations; and an autonomous software platform that enables drones to deliver safely to homes.

[ Flirtey ]

EPFL scientists are developing new approaches for improved control of robotic hands – in particular for amputees – that combines individual finger control and automation for improved grasping and manipulation. This interdisciplinary proof-of-concept between neuroengineering and robotics was successfully tested on three amputees and seven healthy subjects.

[ EPFL ]

This video is a few years old, but we’ll take any excuse to watch the majestic sage-grouse be majestic in all their majesticness.

[ UC Davis ]

I like the idea of a game of soccer (or, football to you weirdos in the rest of the world) where the ball has a mind of its own.

[ Sphero ]

Looks like the whole delivery glider idea is really taking off! Or, you know, not taking off.

Weird that they didn’t show the landing, because it sure looked like it was going to plow into the side of the hill at full speed.

[ Yates ] via [ sUAS News ]

This video is from a 2018 paper, but it’s not like we ever get tired of seeing quadrupeds do stuff, right?

[ MIT ]

Founder and Head of Product, Ian Bernstein, and Head of Engineering, Morgan Bell, have been involved in the Misty project for years and they have learned a thing or two about building robots. Hear how and why Misty evolved into a robot development platform, learn what some of the earliest prototypes did (and why they didn’t work for what we envision), and take a deep dive into the technology decisions that form the Misty II platform.

[ Misty Robotics ]

Lex Fridman interviews Vijay Kumar on the Artifiical Intelligence Podcast.

[ AI Podcast ]

This week’s CMU RI Seminar is from Ross Knepper at Cornell, on Formalizing Teamwork in Human-Robot Interaction.

Robots out in the world today work for people but not with people. Before robots can work closely with ordinary people as part of a human-robot team in a home or office setting, robots need the ability to acquire a new mix of functional and social skills. Working with people requires a shared understanding of the task, capabilities, intentions, and background knowledge. For robots to act jointly as part of a team with people, they must engage in collaborative planning, which involves forming a consensus through an exchange of information about goals, capabilities, and partial plans. Often, much of this information is conveyed through implicit communication. In this talk, I formalize components of teamwork involving collaboration, communication, and representation. I illustrate how these concepts interact in the application of social navigation, which I argue is a first-class example of teamwork. In this setting, participants must avoid collision by legibly conveying intended passing sides via nonverbal cues like path shape. A topological representation using the braid groups enables the robot to reason about a small enumerable set of passing outcomes. I show how implicit communication of topological group plans achieves rapid covergence to a group consensus, and how a robot in the group can deliberately influence the ultimate outcome to maximize joint performance, yielding pedestrian comfort with the robot.

[ CMU RI ]

In this week’s episode of Robots in Depth, Per speaks with Julien Bourgeois about Claytronics, a project from Carnegie Mellon and Intel to develop “programmable matter.”

Julien started out as a computer scientist. He was always interested in robotics privately but then had the opportunity to get into micro robots when his lab was merged into the FEMTO-ST Institute. He later worked with Seth Copen Goldstein at Carnegie Mellon on the Claytronics project.

Julien shows an enlarged mock-up of the small robots that make up programmable matter, catoms, and speaks about how they are designed. Currently he is working on a unit that is one centimeter in diameter and he shows us the very small CPU that goes into that model.

[ Robots in Depth ] Continue reading →

Posted in Human Robots

#435494 Driverless Electric Trucks Are Coming, ...

Posted on August 14, 2019 by Android

Self-driving and electric cars just don’t stop making headlines lately. Amazon invested in self-driving startup Aurora earlier this year. Waymo, Daimler, GM, along with startups like Zoox, have all launched or are planning to launch driverless taxis, many of them all-electric. People are even yanking driverless cars from their timeless natural habitat—roads—to try to teach them to navigate forests and deserts.

The future of driving, it would appear, is upon us.

But an equally important vehicle that often gets left out of the conversation is trucks; their relevance to our day-to-day lives may not be as visible as that of cars, but their impact is more profound than most of us realize.

Two recent developments in trucking point to a future of self-driving, electric semis hauling goods across the country, and likely doing so more quickly, cheaply, and safely than trucks do today.

Self-Driving in Texas
Last week, Kodiak Robotics announced it’s beginning its first commercial deliveries using self-driving trucks on a route from Dallas to Houston. The two cities sit about 240 miles apart, connected primarily by interstate 45. Kodiak is aiming to expand its reach far beyond the heart of Texas (if Dallas and Houston can be considered the heart, that is) to the state’s most far-flung cities, including El Paso to the west and Laredo to the south.

If self-driving trucks are going to be constrained to staying within state lines (and given that the laws regulating them differ by state, they will be for the foreseeable future), Texas is a pretty ideal option. It’s huge (thousands of miles of highway run both east-west and north-south), it’s warm (better than cold for driverless tech components like sensors), its proximity to Mexico means constant movement of both raw materials and manufactured goods (basically, you can’t have too many trucks in Texas), and most crucially, it’s lax on laws (driverless vehicles have been permitted there since 2017).

Spoiler, though—the trucks won’t be fully unmanned. They’ll have safety drivers to guide them onto and off of the highway, and to be there in case of any unexpected glitches.

California Goes (Even More) Electric
According to some top executives in the rideshare industry, automation is just one key component of the future of driving. Another is electricity replacing gas, and it’s not just carmakers that are plugging into the trend.

This week, Daimler Trucks North America announced completion of its first electric semis for customers Penske and NFI, to be used in the companies’ southern California operations. Scheduled to start operating later this month, the trucks will essentially be guinea pigs for testing integration of electric trucks into large-scale fleets; intel gleaned from the trucks’ performance will impact the design of later models.

Design-wise, the trucks aren’t much different from any other semi you’ve seen lumbering down the highway recently. Their range is about 250 miles—not bad if you think about how much more weight a semi is pulling than a passenger sedan—and they’ve been dubbed eCascadia, an electrified version of Freightliner’s heavy-duty Cascadia truck.

Batteries have a long way to go before they can store enough energy to make electric trucks truly viable (not to mention setting up a national charging infrastructure), but Daimler’s announcement is an important step towards an electrically-driven future.

Keep on Truckin’
Obviously, it’s more exciting to think about hailing one of those cute little Waymo cars with no steering wheel to shuttle you across town than it is to think about that 12-pack of toilet paper you ordered on Amazon cruising down the highway in a semi while the safety driver takes a snooze. But pushing driverless and electric tech in the trucking industry makes sense for a few big reasons.

Trucks mostly run long routes on interstate highways—with no pedestrians, stoplights, or other city-street obstacles to contend with, highway driving is much easier to automate. What glitches there are to be smoothed out may as well be smoothed out with cargo on board rather than people. And though you wouldn’t know it amid the frantic shouts of ‘a robot could take your job!’, the US is actually in the midst of a massive shortage of truck drivers—60,000 short as of earlier this year, to be exact.

As Todd Spencer, president of the Owner-Operator Independent Drivers Association, put it, “Trucking is an absolutely essential, critical industry to the nation, to everybody in it.” Alas, trucks get far less love than cars, but come on—probably 90 percent of the things you ate, bought, or used today were at some point moved by a truck.

Adding driverless and electric tech into that equation, then, should yield positive outcomes on all sides, whether we’re talking about cheaper 12-packs of toilet paper, fewer traffic fatalities due to human error, a less-strained labor force, a stronger economy… or something pretty cool to see as you cruise down the highway in your (driverless, electric, futuristic) car.

Image Credit: Vitpho / Shutterstock.com Continue reading →

Posted in Human Robots

#434865 5 AI Breakthroughs We’ll Likely See in ...

Posted on April 27, 2019 by Android

Convergence is accelerating disruption… everywhere! Exponential technologies are colliding into each other, reinventing products, services, and industries.

As AI algorithms such as Siri and Alexa can process your voice and output helpful responses, other AIs like Face++ can recognize faces. And yet others create art from scribbles, or even diagnose medical conditions.

Let’s dive into AI and convergence.

Top 5 Predictions for AI Breakthroughs (2019-2024)
My friend Neil Jacobstein is my ‘go-to expert’ in AI, with over 25 years of technical consulting experience in the field. Currently the AI and Robotics chair at Singularity University, Jacobstein is also a Distinguished Visiting Scholar in Stanford’s MediaX Program, a Henry Crown Fellow, an Aspen Institute moderator, and serves on the National Academy of Sciences Earth and Life Studies Committee. Neil predicted five trends he expects to emerge over the next five years, by 2024.

AI gives rise to new non-human pattern recognition and intelligence results

AlphaGo Zero, a machine learning computer program trained to play the complex game of Go, defeated the Go world champion in 2016 by 100 games to zero. But instead of learning from human play, AlphaGo Zero trained by playing against itself—a method known as reinforcement learning.

Building its own knowledge from scratch, AlphaGo Zero demonstrates a novel form of creativity, free of human bias. Even more groundbreaking, this type of AI pattern recognition allows machines to accumulate thousands of years of knowledge in a matter of hours.

While these systems can’t answer the question “What is orange juice?” or compete with the intelligence of a fifth grader, they are growing more and more strategically complex, merging with other forms of narrow artificial intelligence. Within the next five years, who knows what successors of AlphaGo Zero will emerge, augmenting both your business functions and day-to-day life.

Doctors risk malpractice when not using machine learning for diagnosis and treatment planning

A group of Chinese and American researchers recently created an AI system that diagnoses common childhood illnesses, ranging from the flu to meningitis. Trained on electronic health records compiled from 1.3 million outpatient visits of almost 600,000 patients, the AI program produced diagnosis outcomes with unprecedented accuracy.

While the US health system does not tout the same level of accessible universal health data as some Chinese systems, we’ve made progress in implementing AI in medical diagnosis. Dr. Kang Zhang, chief of ophthalmic genetics at the University of California, San Diego, created his own system that detects signs of diabetic blindness, relying on both text and medical images.

With an eye to the future, Jacobstein has predicted that “we will soon see an inflection point where doctors will feel it’s a risk to not use machine learning and AI in their everyday practices because they don’t want to be called out for missing an important diagnostic signal.”

Quantum advantage will massively accelerate drug design and testing

Researchers estimate that there are 1060 possible drug-like molecules—more than the number of atoms in our solar system. But today, chemists must make drug predictions based on properties influenced by molecular structure, then synthesize numerous variants to test their hypotheses.

Quantum computing could transform this time-consuming, highly costly process into an efficient, not to mention life-changing, drug discovery protocol.

“Quantum computing is going to have a major industrial impact… not by breaking encryption,” said Jacobstein, “but by making inroads into design through massive parallel processing that can exploit superposition and quantum interference and entanglement, and that can wildly outperform classical computing.”

AI accelerates security systems’ vulnerability and defense

With the incorporation of AI into almost every aspect of our lives, cyberattacks have grown increasingly threatening. “Deep attacks” can use AI-generated content to avoid both human and AI controls.

Previous examples include fake videos of former President Obama speaking fabricated sentences, and an adversarial AI fooling another algorithm into categorizing a stop sign as a 45 mph speed limit sign. Without the appropriate protections, AI systems can be manipulated to conduct any number of destructive objectives, whether ruining reputations or diverting autonomous vehicles.

Jacobstein’s take: “We all have security systems on our buildings, in our homes, around the healthcare system, and in air traffic control, financial organizations, the military, and intelligence communities. But we all know that these systems have been hacked periodically and we’re going to see that accelerate. So, there are major business opportunities there and there are major opportunities for you to get ahead of that curve before it bites you.”

AI design systems drive breakthroughs in atomically precise manufacturing

Just as the modern computer transformed our relationship with bits and information, AI will redefine and revolutionize our relationship with molecules and materials. AI is currently being used to discover new materials for clean-tech innovations, such as solar panels, batteries, and devices that can now conduct artificial photosynthesis.

Today, it takes about 15 to 20 years to create a single new material, according to industry experts. But as AI design systems skyrocket in capacity, these will vastly accelerate the materials discovery process, allowing us to address pressing issues like climate change at record rates. Companies like Kebotix are already on their way to streamlining the creation of chemistries and materials at the click of a button.

Atomically precise manufacturing will enable us to produce the previously unimaginable.

Final Thoughts
Within just the past three years, countries across the globe have signed into existence national AI strategies and plans for ramping up innovation. Businesses and think tanks have leaped onto the scene, hiring AI engineers and tech consultants to leverage what computer scientist Andrew Ng has even called the new ‘electricity’ of the 21st century.

As AI plays an exceedingly vital role in everyday life, how will your business leverage it to keep up and build forward?

In the wake of burgeoning markets, new ventures will quickly arise, each taking advantage of untapped data sources or unmet security needs.

And as your company aims to ride the wave of AI’s exponential growth, consider the following pointers to leverage AI and disrupt yourself before it reaches you first:

Determine where and how you can begin collecting critical data to inform your AI algorithms
Identify time-intensive processes that can be automated and accelerated within your company
Discern which global challenges can be expedited by hyper-fast, all-knowing minds

Remember: good data is vital fuel. Well-defined problems are the best compass. And the time to start implementing AI is now.

Join Me
Abundance-Digital Online Community: I’ve created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is my ‘onramp’ for exponential entrepreneurs – those who want to get involved and play at a higher level. Click here to learn more.

Image Credit: Yurchanka Siarhei / Shutterstock.com Continue reading →

Posted in Human Robots

#434616 What Games Are Humans Still Better at ...

Posted on February 10, 2019 by Android

Artificial intelligence (AI) systems’ rapid advances are continually crossing rows off the list of things humans do better than our computer compatriots.

AI has bested us at board games like chess and Go, and set astronomically high scores in classic computer games like Ms. Pacman. More complex games form part of AI’s next frontier.

While a team of AI bots developed by OpenAI, known as the OpenAI Five, ultimately lost to a team of professional players last year, they have since been running rampant against human opponents in Dota 2. Not to be outdone, Google’s DeepMind AI recently took on—and beat—several professional players at StarCraft II.

These victories beg the questions: what games are humans still better at than AI? And for how long?

The Making Of AlphaStar
DeepMind’s results provide a good starting point in a search for answers. The version of its AI for StarCraft II, dubbed AlphaStar, learned to play the games through supervised learning and reinforcement learning.

First, AI agents were trained by analyzing and copying human players, learning basic strategies. The initial agents then played each other in a sort of virtual death match where the strongest agents stayed on. New iterations of the agents were developed and entered the competition. Over time, the agents became better and better at the game, learning new strategies and tactics along the way.

One of the advantages of AI is that it can go through this kind of process at superspeed and quickly develop better agents. DeepMind researchers estimate that the AlphaStar agents went through the equivalent of roughly 200 years of game time in about 14 days.

Cheating or One Hand Behind the Back?
The AlphaStar AI agents faced off against human professional players in a series of games streamed on YouTube and Twitch. The AIs trounced their human opponents, winning ten games on the trot, before pro player Grzegorz “MaNa” Komincz managed to salvage some pride for humanity by winning the final game. Experts commenting on AlphaStar’s performance used words like “phenomenal” and “superhuman”—which was, to a degree, where things got a bit problematic.

AlphaStar proved particularly skilled at controlling and directing units in battle, known as micromanagement. One reason was that it viewed the whole game map at once—something a human player is not able to do—which made it seemingly able to control units in different areas at the same time. DeepMind researchers said the AIs only focused on a single part of the map at any given time, but interestingly, AlphaStar’s AI agent was limited to a more restricted camera view during the match “MaNA” won.

Potentially offsetting some of this advantage was the fact that AlphaStar was also restricted in certain ways. For example, it was prevented from performing more clicks per minute than a human player would be able to.

Where AIs Struggle
Games like StarCraft II and Dota 2 throw a lot of challenges at AIs. Complex game theory/ strategies, operating with imperfect/incomplete information, undertaking multi-variable and long-term planning, real-time decision-making, navigating a large action space, and making a multitude of possible decisions at every point in time are just the tip of the iceberg. The AIs’ performance in both games was impressive, but also highlighted some of the areas where they could be said to struggle.

In Dota 2 and StarCraft II, AI bots have seemed more vulnerable in longer games, or when confronted with surprising, unfamiliar strategies. They seem to struggle with complexity over time and improvisation/adapting to quick changes. This could be tied to how AIs learn. Even within the first few hours of performing a task, humans tend to gain a sense of familiarity and skill that takes an AI much longer. We are also better at transferring skill from one area to another. In other words, experience playing Dota 2 can help us become good at StarCraft II relatively quickly. This is not the case for AI—yet.

Dwindling Superiority
While the battle between AI and humans for absolute superiority is still on in Dota 2 and StarCraft II, it looks likely that AI will soon reign supreme. Similar things are happening to other types of games.

In 2017, a team from Carnegie Mellon University pitted its Libratus AI against four professionals. After 20 days of No Limit Texas Hold’em, Libratus was up by $1.7 million. Another likely candidate is the destroyer of family harmony at Christmas: Monopoly.

Poker involves bluffing, while Monopoly involves negotiation—skills you might not think AI would be particularly suited to handle. However, an AI experiment at Facebook showed that AI bots are more than capable of undertaking such tasks. The bots proved skilled negotiators, and developed negotiating strategies like pretending interest in one object while they were interested in another altogether—bluffing.

So, what games are we still better at than AI? There is no precise answer, but the list is getting shorter at a rapid pace.

The Aim Of the Game
While AI’s mastery of games might at first glance seem an odd area to focus research on, the belief is that the way AI learn to master a game is transferrable to other areas.

For example, the Libratus poker-playing AI employed strategies that could work in financial trading or political negotiations. The same applies to AlphaStar. As Oriol Vinyals, co-leader of the AlphaStar project, told The Verge:

“First and foremost, the mission at DeepMind is to build an artificial general intelligence. […] To do so, it’s important to benchmark how our agents perform on a wide variety of tasks.”

A 2017 survey of more than 350 AI researchers predicts AI could be a better driver than humans within ten years. By the middle of the century, AI will be able to write a best-selling novel, and a few years later, it will be better than humans at surgery. By the year 2060, AI may do everything better than us.

Whether you think this is a good or a bad thing, it’s worth noting that AI has an often overlooked ability to help us see things differently. When DeepMind’s AlphaGo beat human Go champion Lee Sedol, the Go community learned from it, too. Lee himself went on a win streak after the match with AlphaGo. The same is now happening within the Dota 2 and StarCraft II communities that are studying the human vs. AI games intensely.

More than anything, AI’s recent gaming triumphs illustrate how quickly artificial intelligence is developing. In 1997, Dr. Piet Hut, an astrophysicist at the Institute for Advanced Study at Princeton and a GO enthusiast, told the New York Times that:

”It may be a hundred years before a computer beats humans at Go—maybe even longer.”

Image Credit: Roman Kosolapov / Shutterstock.com Continue reading →

Posted in Human Robots

#434532 How Microrobots Will Fix Our Roads and ...

Posted on January 25, 2019 by Android

Swarms of microrobots will scuttle along beneath our roads and pavements, finding and fixing leaky pipes and faulty cables. Thanks to their efforts, we can avoid costly road work that costs billions of dollars each year—not to mention frustrating traffic delays.

That is, if a new project sponsored by the U.K. government is a success. Recent developments in the space seem to point towards a bright future for microrobots.

Microrobots Saving Billions
Each year, around 1.5 million road excavations take place across the U.K. Many are due to leaky pipes and faulty cables that necessitate excavation of road surfaces in order to fix them. The resulting repairs, alongside disruptions to traffic and businesses, are estimated to cost a whopping £6.3 billion ($8 billion).

A consortium of scientists, led by University of Sheffield Professor Kirill Horoshenkov, are planning to use microrobots to negate most of these costs. The group has received a £7.2 million ($9.2 million) grant to develop and build their bots.

According to Horoshenkov, the microrobots will come in two versions. One is an inspection bot, which will navigate along underground infrastructure and examine its condition via sonar. The inspectors will be complemented by worker bots capable of carrying out repairs with cement and adhesives or cleaning out blockages with a high-powered jet. The inspector bots will be around one centimeter long and possibly autonomous, while the worker bots will be slightly larger and steered via remote control.

If successful, it is believed the bots could potentially save the U.K. economy around £5 billion ($6.4 billion) a year.

The U.K. government has set aside a further £19 million ($24 million) for research into robots for hazardous environments, such as nuclear decommissioning, drones for oil pipeline monitoring, and artificial intelligence software to detect the need for repairs on satellites in orbit.

The Lowest-Hanging Fruit
Microrobots like the ones now under development in the U.K. have many potential advantages and use cases. Thanks to their small size they can navigate tight spaces, for example in search and rescue operations, and robot swarm technology would allow them to collaborate to perform many different functions, including in construction projects.

To date, the number of microrobots in use is relatively limited, but that could be about to change, with bots closing in on other types of inspection jobs, which could be considered one of the lowest-hanging fruits.

Engineering firm Rolls-Royce (not the car company, but the one that builds aircraft engines) is looking to use microrobots to inspect some of the up to 25,000 individual parts that make up an engine. The microrobots use the cockroach as a model, and Rolls Royce believes they could save engineers time when performing the maintenance checks that can take over a month per engine.

Even Smaller Successes
Going further down in scale, recent years have seen a string of successes for nanobots. For example, a team of researchers at the Femto-ST Institute have used nanobots to build what is likely the world’s smallest house (if this isn’t a category at Guinness, someone needs to get on the phone with them), which stands a ‘towering’ 0.015 millimeters.

One of the areas where nanobots have shown great promise is in medicine. Several studies have shown how the minute bots are capable of delivering drugs directly into dense biological tissue, which can otherwise be highly challenging to target directly. Such delivery systems have a great potential for improving the treatment of a wide range of ailments and illnesses, including cancer.

There’s no question that the ecosystem of microrobots and nanobots is evolving. While still in their early days, the above successes point to a near-future boom in the bots we may soon refer to as our ‘littlest everyday helpers.’

Image Credit: 5nikolas5 / Shutterstock.com Continue reading →

Posted in Human Robots