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#438779 Meet Catfish Charlie, the CIA’s ...

Posted on February 27, 2021 by Android

Photo: CIA Museum

CIA roboticists designed Catfish Charlie to take water samples undetected. Why they wanted a spy fish for such a purpose remains classified.

In 1961, Tom Rogers of the Leo Burnett Agency created Charlie the Tuna, a jive-talking cartoon mascot and spokesfish for the StarKist brand. The popular ad campaign ran for several decades, and its catchphrase “Sorry, Charlie” quickly hooked itself in the American lexicon.

When the CIA’s Office of Advanced Technologies and Programs started conducting some fish-focused research in the 1990s, Charlie must have seemed like the perfect code name. Except that the CIA’s Charlie was a catfish. And it was a robot.

More precisely, Charlie was an unmanned underwater vehicle (UUV) designed to surreptitiously collect water samples. Its handler controlled the fish via a line-of-sight radio handset. Not much has been revealed about the fish’s construction except that its body contained a pressure hull, ballast system, and communications system, while its tail housed the propulsion. At 61 centimeters long, Charlie wouldn’t set any biggest-fish records. (Some species of catfish can grow to 2 meters.) Whether Charlie reeled in any useful intel is unknown, as details of its missions are still classified.

For exploring watery environments, nothing beats a robot
The CIA was far from alone in its pursuit of UUVs nor was it the first agency to do so. In the United States, such research began in earnest in the 1950s, with the U.S. Navy’s funding of technology for deep-sea rescue and salvage operations. Other projects looked at sea drones for surveillance and scientific data collection.

Aaron Marburg, a principal electrical and computer engineer who works on UUVs at the University of Washington’s Applied Physics Laboratory, notes that the world’s oceans are largely off-limits to crewed vessels. “The nature of the oceans is that we can only go there with robots,” he told me in a recent Zoom call. To explore those uncharted regions, he said, “we are forced to solve the technical problems and make the robots work.”

Image: Thomas Wells/Applied Physics Laboratory/University of Washington

An oil painting commemorates SPURV, a series of underwater research robots built by the University of Washington’s Applied Physics Lab. In nearly 400 deployments, no SPURVs were lost.

One of the earliest UUVs happens to sit in the hall outside Marburg’s office: the Self-Propelled Underwater Research Vehicle, or SPURV, developed at the applied physics lab beginning in the late ’50s. SPURV’s original purpose was to gather data on the physical properties of the sea, in particular temperature and sound velocity. Unlike Charlie, with its fishy exterior, SPURV had a utilitarian torpedo shape that was more in line with its mission. Just over 3 meters long, it could dive to 3,600 meters, had a top speed of 2.5 m/s, and operated for 5.5 hours on a battery pack. Data was recorded to magnetic tape and later transferred to a photosensitive paper strip recorder or other computer-compatible media and then plotted using an IBM 1130.

Over time, SPURV’s instrumentation grew more capable, and the scope of the project expanded. In one study, for example, SPURV carried a fluorometer to measure the dispersion of dye in the water, to support wake studies. The project was so successful that additional SPURVs were developed, eventually completing nearly 400 missions by the time it ended in 1979.

Working on underwater robots, Marburg says, means balancing technical risks and mission objectives against constraints on funding and other resources. Support for purely speculative research in this area is rare. The goal, then, is to build UUVs that are simple, effective, and reliable. “No one wants to write a report to their funders saying, ‘Sorry, the batteries died, and we lost our million-dollar robot fish in a current,’ ” Marburg says.

A robot fish called SoFi
Since SPURV, there have been many other unmanned underwater vehicles, of various shapes and sizes and for various missions, developed in the United States and elsewhere. UUVs and their autonomous cousins, AUVs, are now routinely used for scientific research, education, and surveillance.

At least a few of these robots have been fish-inspired. In the mid-1990s, for instance, engineers at MIT worked on a RoboTuna, also nicknamed Charlie. Modeled loosely on a blue-fin tuna, it had a propulsion system that mimicked the tail fin of a real fish. This was a big departure from the screws or propellers used on UUVs like SPURV. But this Charlie never swam on its own; it was always tethered to a bank of instruments. The MIT group’s next effort, a RoboPike called Wanda, overcame this limitation and swam freely, but never learned to avoid running into the sides of its tank.

Fast-forward 25 years, and a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) unveiled SoFi, a decidedly more fishy robot designed to swim next to real fish without disturbing them. Controlled by a retrofitted Super Nintendo handset, SoFi could dive more than 15 meters, control its own buoyancy, and swim around for up to 40 minutes between battery charges. Noting that SoFi’s creators tested their robot fish in the gorgeous waters off Fiji, IEEE Spectrum’s Evan Ackerman noted, “Part of me is convinced that roboticists take on projects like these…because it’s a great way to justify a trip somewhere exotic.”

SoFi, Wanda, and both Charlies are all examples of biomimetics, a term coined in 1974 to describe the study of biological mechanisms, processes, structures, and substances. Biomimetics looks to nature to inspire design.

Sometimes, the resulting technology proves to be more efficient than its natural counterpart, as Richard James Clapham discovered while researching robotic fish for his Ph.D. at the University of Essex, in England. Under the supervision of robotics expert Huosheng Hu, Clapham studied the swimming motion of Cyprinus carpio, the common carp. He then developed four robots that incorporated carplike swimming, the most capable of which was iSplash-II. When tested under ideal conditions—that is, a tank 5 meters long, 2 meters wide, and 1.5 meters deep—iSpash-II obtained a maximum velocity of 11.6 body lengths per second (or about 3.7 m/s). That’s faster than a real carp, which averages a top velocity of 10 body lengths per second. But iSplash-II fell short of the peak performance of a fish darting quickly to avoid a predator.

Of course, swimming in a test pool or placid lake is one thing; surviving the rough and tumble of a breaking wave is another matter. The latter is something that roboticist Kathryn Daltorio has explored in depth.

Daltorio, an assistant professor at Case Western Reserve University and codirector of the Center for Biologically Inspired Robotics Research there, has studied the movements of cockroaches, earthworms, and crabs for clues on how to build better robots. After watching a crab navigate from the sandy beach to shallow water without being thrown off course by a wave, she was inspired to create an amphibious robot with tapered, curved feet that could dig into the sand. This design allowed her robot to withstand forces up to 138 percent of its body weight.

Photo: Nicole Graf

This robotic crab created by Case Western’s Kathryn Daltorio imitates how real crabs grab the sand to avoid being toppled by waves.

In her designs, Daltorio is following architect Louis Sullivan’s famous maxim: Form follows function. She isn’t trying to imitate the aesthetics of nature—her robot bears only a passing resemblance to a crab—but rather the best functionality. She looks at how animals interact with their environments and steals evolution’s best ideas.

And yet, Daltorio admits, there is also a place for realistic-looking robotic fish, because they can capture the imagination and spark interest in robotics as well as nature. And unlike a hyperrealistic humanoid, a robotic fish is unlikely to fall into the creepiness of the uncanny valley.

In writing this column, I was delighted to come across plenty of recent examples of such robotic fish. Ryomei Engineering, a subsidiary of Mitsubishi Heavy Industries, has developed several: a robo-coelacanth, a robotic gold koi, and a robotic carp. The coelacanth was designed as an educational tool for aquariums, to present a lifelike specimen of a rarely seen fish that is often only known by its fossil record. Meanwhile, engineers at the University of Kitakyushu in Japan created Tai-robot-kun, a credible-looking sea bream. And a team at Evologics, based in Berlin, came up with the BOSS manta ray.

Whatever their official purpose, these nature-inspired robocreatures can inspire us in return. UUVs that open up new and wondrous vistas on the world’s oceans can extend humankind’s ability to explore. We create them, and they enhance us, and that strikes me as a very fair and worthy exchange.

This article appears in the March 2021 print issue as “Catfish, Robot, Swimmer, Spy.”

About the Author
Allison Marsh is an associate professor of history at the University of South Carolina and codirector of the university’s Ann Johnson Institute for Science, Technology & Society. Continue reading →

Posted in Human Robots

#437620 The Trillion-Transistor Chip That Just ...

Posted on November 22, 2020 by Android

The history of computer chips is a thrilling tale of extreme miniaturization.

The smaller, the better is a trend that’s given birth to the digital world as we know it. So, why on earth would you want to reverse course and make chips a lot bigger? Well, while there’s no particularly good reason to have a chip the size of an iPad in an iPad, such a chip may prove to be genius for more specific uses, like artificial intelligence or simulations of the physical world.

At least, that’s what Cerebras, the maker of the biggest computer chip in the world, is hoping.

The Cerebras Wafer-Scale Engine is massive any way you slice it. The chip is 8.5 inches to a side and houses 1.2 trillion transistors. The next biggest chip, NVIDIA’s A100 GPU, measures an inch to a side and has a mere 54 billion transistors. The former is new, largely untested and, so far, one-of-a-kind. The latter is well-loved, mass-produced, and has taken over the world of AI and supercomputing in the last decade.

So can Goliath flip the script on David? Cerebras is on a mission to find out.

Big Chips Beyond AI
When Cerebras first came out of stealth last year, the company said it could significantly speed up the training of deep learning models.

Since then, the WSE has made its way into a handful of supercomputing labs, where the company’s customers are putting it through its paces. One of those labs, the National Energy Technology Laboratory, is looking to see what it can do beyond AI.

So, in a recent trial, researchers pitted the chip—which is housed in an all-in-one system about the size of a dorm room mini-fridge called the CS-1—against a supercomputer in a fluid dynamics simulation. Simulating the movement of fluids is a common supercomputer application useful for solving complex problems like weather forecasting and airplane wing design.

The trial was described in a preprint paper written by a team led by Cerebras’s Michael James and NETL’s Dirk Van Essendelft and presented at the supercomputing conference SC20 this week. The team said the CS-1 completed a simulation of combustion in a power plant roughly 200 times faster than it took the Joule 2.0 supercomputer to do a similar task.

The CS-1 was actually faster-than-real-time. As Cerebrus wrote in a blog post, “It can tell you what is going to happen in the future faster than the laws of physics produce the same result.”

The researchers said the CS-1’s performance couldn’t be matched by any number of CPUs and GPUs. And CEO and cofounder Andrew Feldman told VentureBeat that would be true “no matter how large the supercomputer is.” At a point, scaling a supercomputer like Joule no longer produces better results in this kind of problem. That’s why Joule’s simulation speed peaked at 16,384 cores, a fraction of its total 86,400 cores.

A comparison of the two machines drives the point home. Joule is the 81st fastest supercomputer in the world, takes up dozens of server racks, consumes up to 450 kilowatts of power, and required tens of millions of dollars to build. The CS-1, by comparison, fits in a third of a server rack, consumes 20 kilowatts of power, and sells for a few million dollars.

While the task is niche (but useful) and the problem well-suited to the CS-1, it’s still a pretty stunning result. So how’d they pull it off? It’s all in the design.

Cut the Commute
Computer chips begin life on a big piece of silicon called a wafer. Multiple chips are etched onto the same wafer and then the wafer is cut into individual chips. While the WSE is also etched onto a silicon wafer, the wafer is left intact as a single, operating unit. This wafer-scale chip contains almost 400,000 processing cores. Each core is connected to its own dedicated memory and its four neighboring cores.

Putting that many cores on a single chip and giving them their own memory is why the WSE is bigger; it’s also why, in this case, it’s better.

Most large-scale computing tasks depend on massively parallel processing. Researchers distribute the task among hundreds or thousands of chips. The chips need to work in concert, so they’re in constant communication, shuttling information back and forth. A similar process takes place within each chip, as information moves between processor cores, which are doing the calculations, and shared memory to store the results.

It’s a little like an old-timey company that does all its business on paper.

The company uses couriers to send and collect documents from other branches and archives across town. The couriers know the best routes through the city, but the trips take some minimum amount of time determined by the distance between the branches and archives, the courier’s top speed, and how many other couriers are on the road. In short, distance and traffic slow things down.

Now, imagine the company builds a brand new gleaming skyscraper. Every branch is moved into the new building and every worker gets a small filing cabinet in their office to store documents. Now any document they need can be stored and retrieved in the time it takes to step across the office or down the hall to their neighbor’s office. The information commute has all but disappeared. Everything’s in the same house.

Cerebras’s megachip is a bit like that skyscraper. The way it shuttles information—aided further by its specially tailored compiling software—is far more efficient compared to a traditional supercomputer that needs to network a ton of traditional chips.

Simulating the World as It Unfolds
It’s worth noting the chip can only handle problems small enough to fit on the wafer. But such problems may have quite practical applications because of the machine’s ability to do high-fidelity simulation in real-time. The authors note, for example, the machine should in theory be able to accurately simulate the air flow around a helicopter trying to land on a flight deck and semi-automate the process—something not possible with traditional chips.

Another opportunity, they note, would be to use a simulation as input to train a neural network also residing on the chip. In an intriguing and related example, a Caltech machine learning technique recently proved to be 1,000 times faster at solving the same kind of partial differential equations at play here to simulate fluid dynamics.

They also note that improvements in the chip (and others like it, should they arrive) will push back the limits of what can be accomplished. Already, Cerebras has teased the release of its next-generation chip, which will have 2.6 trillion transistors, 850,00 cores, and more than double the memory.

Of course, it still remains to be seen whether wafer-scale computing really takes off. The idea has been around for decades, but Cerebras is the first to pursue it seriously. Clearly, they believe they’ve solved the problem in a way that’s useful and economical.

Other new architectures are also being pursued in the lab. Memristor-based neuromorphic chips, for example, mimic the brain by putting processing and memory into individual transistor-like components. And of course, quantum computers are in a separate lane, but tackle similar problems.

It could be that one of these technologies eventually rises to rule them all. Or, and this seems just as likely, computing may splinter into a bizarre quilt of radical chips, all stitched together to make the most of each depending on the situation.

Image credit: Cerebras Continue reading →

Posted in Human Robots

#436234 Robot Gift Guide 2019

Posted on November 28, 2019 by Android

Welcome to the eighth edition of IEEE Spectrum’s Robot Gift Guide!

This year we’re featuring 15 robotic products that we think will make fantastic holiday gifts. As always, we tried to include a broad range of robot types and prices, focusing mostly on items released this year. (A reminder: While we provide links to places where you can buy these items, we’re not endorsing any in particular, and a little bit of research may result in better deals.)

If you need even more robot gift ideas, take a look at our past guides: 2018, 2017, 2016, 2015, 2014, 2013, and 2012. Some of those robots are still great choices and might be way cheaper now than when we first posted about them. And if you have suggestions that you’d like to share, post a comment below to help the rest of us find the perfect robot gift.

Skydio 2

Image: Skydio

What makes robots so compelling is their autonomy, and the Skydio 2 is one of the most autonomous robots we’ve ever seen. It uses an array of cameras to map its environment and avoid obstacles in real-time, making flight safe and effortless and enabling the kinds of shots that would be impossible otherwise. Seriously, this thing is magical, and it’s amazing that you can actually buy one.
$1,000
Skydio
UBTECH Jimu MeeBot 2

Image: UBTECH

The Jimu MeeBot 2.0 from UBTECH is a STEM education robot designed to be easy to build and program. It includes six servo motors, a color sensor, and LED lights. An app for iPhone or iPad provides step-by-step 3D instructions, and helps you code different behaviors for the robot. It’s available exclusively from Apple.
$130
Apple
iRobot Roomba s9+

Image: iRobot

We know that $1,400 is a crazy amount of money to spend on a robot vacuum, but the Roomba s9+ is a crazy robot vacuum. As if all of its sensors and mapping intelligence wasn’t enough, it empties itself, which means that you can have your floors vacuumed every single day for a month and you don’t have to even think about it. This is what home robots are supposed to be.
$1,400
iRobot
PFF Gita

Photo: Piaggio Fast Forward

Nobody likes carrying things, which is why Gita is perfect for everyone with an extra $3,000 lying around. Developed by Piaggio Fast Forward, this autonomous robot will follow you around with a cargo hold full of your most important stuff, and do it in a way guaranteed to attract as much attention as possible.
$3,250
Gita
DJI Mavic Mini

Photo: DJI

It’s tiny, it’s cheap, and it takes good pictures—what more could you ask for from a drone? And for $400, this is an excellent drone to get if you’re on a budget and comfortable with manual flight. Keep in mind that while the Mavic Mini is small enough that you don’t need to register it with the FAA, you do still need to follow all the same rules and regulations.
$400
DJI
LEGO Star Wars Droid Commander

Image: LEGO

Designed for kids ages 8+, this LEGO set includes more than 1,000 pieces, enough to build three different droids: R2-D2, Gonk Droid, and Mouse Droid. Using a Bluetooth-controlled robotic brick called Move Hub, which connects to the LEGO BOOST Star Wars app, kids can change how the robots behave and solve challenges, learning basic robotics and coding skills.
$200
LEGO
Sony Aibo

Photo: Sony

Robot pets don’t get much more sophisticated (or expensive) than Sony’s Aibo. Strictly speaking, it’s one of the most complex consumer robots you can buy, and Sony continues to add to Aibo’s software. Recent new features include user programmability, and the ability to “feed” it.
$2,900 (free aibone and paw pads until 12/29/2019)
Sony
Neato Botvac D4 Connected

Photo: Neato

The Neato Botvac D4 may not have all of the features of its fancier and more expensive siblings, but it does have the features that you probably care the most about: The ability to make maps of its environment for intelligent cleaning (using lasers!), along with user-defined no-go lines that keep it where you want it. And it cleans quite well, too.
$530 $350 (sale)
Neato Robotics
Cubelets Curiosity Set

Photo: Modular Robotics

Cubelets are magnetic blocks that you can snap together to make an endless variety of robots with no programming and no wires. The newest set, called Curiosity, is designed for kids ages 4+ and comes with 10 robotic cubes. These include light and distance sensors, motors, and a Bluetooth module, which connects the robot constructions to the Cubelets app.
$250
Modular Robotics
Tertill

Photo: Franklin Robotics

Tertill does one simple job: It weeds your garden. It’s waterproof, dirt proof, solar powered, and fully autonomous, meaning that you can leave it out in your garden all summer and just enjoy eating your plants rather than taking care of them.
$350
Tertill
iRobot Root

Photo: iRobot

Root was originally developed by Harvard University as a tool to help kids progressively learn to code. iRobot has taken over Root and is now supporting the curriculum, which starts for kids before they even know how to read and should keep them busy for years afterwards.
$200
iRobot
LOVOT

Image: Lovot

Let’s be honest: Nobody is really quite sure what LOVOT is. We can all agree that it’s kinda cute, though. And kinda weird. But cute. Created by Japanese robotics startup Groove X, LOVOT does have a whole bunch of tech packed into its bizarre little body and it will do its best to get you to love it.
$2,750 (¥300,000)
LOVOT
Sphero RVR

Photo: Sphero

RVR is a rugged, versatile, easy to program mobile robot. It’s a development platform designed to be a bridge between educational robots like Sphero and more sophisticated and expensive systems like Misty. It’s mostly affordable, very expandable, and comes from a company with a lot of experience making robots.
$250
Sphero
“How to Train Your Robot”

Image: Lawrence Hall of Science

Aimed at 4th and 5th graders, “How to Train Your Robot,” written by Blooma Goldberg, Ken Goldberg, and Ashley Chase, and illustrated by Dave Clegg, is a perfect introduction to robotics for kids who want to get started with designing and building robots. But the book isn’t just for beginners: It’s also a fun, inspiring read for kids who are already into robotics and want to go further—it even introduces concepts like computer simulations and deep learning. You can download a free digital copy or request hardcopies here.
Free
UC Berkeley
MIT Mini Cheetah

Photo: MIT

Yes, Boston Dynamics’ Spot, now available for lease, is probably the world’s most famous quadruped, but MIT is starting to pump out Mini Cheetahs en masse for researchers, and while we’re not exactly sure how you’d manage to get one of these things short of stealing one directly for MIT, a Mini Cheetah is our fantasy robotics gift this year. Mini Cheetah looks like a ton of fun—it’s portable, highly dynamic, super rugged, and easy to control. We want one!
Price N/A
MIT Biomimetic Robotics Lab

For more tech gift ideas, see also IEEE Spectrum’s annual Gift Guide. Continue reading →

Posted in Human Robots

#436204 We’re at IROS 2019 to Bring You ...

Posted on November 22, 2019 by Android

The 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) is taking place in Macau this week, featuring well over a thousand presentations on the newest and most amazing robotics research from around the world. There are also posters, workshops, tutorials, an exhibit hall, and plenty of social events where roboticists have the chance to get a little tipsy and talk about all the really interesting stuff.

As always, our plan is to bring you all of the coolest, weirdest, and most interesting things that we find at the show, and here are just a few of the things we’re looking forward to this week:

Flying robots with wings, tails, and… arms?
Spherical robot turtles
An update on that crazy jet-powered iCub
Agile and tiny robot insects
Metallic self-healing robot bones
How to train robots by messing with them
A weird robot sea urchin

And all that is happening just on Tuesday!

Our IROS coverage will continue beyond this week, so keep checking back for more of the best new robotics from Macau.

[ IROS 2019 ] Continue reading →

Posted in Human Robots

#436165 Video Friday: DJI’s Mavic Mini Is ...

Posted on November 2, 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!):

IROS 2019 – November 4-8, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today’s videos.

DJI’s new Mavic Mini looks like a pretty great drone for US $400 ($500 for a combo with more accessories): It’s tiny, flies for 30 minutes, and will do what you need as far as pictures and video (although not a whole lot more).

DJI seems to have put a bunch of effort into making the drone 249 grams, 1 gram under what’s required for FAA registration. That means you save $5 and a few minutes of your time, but that does not mean you don’t have to follow the FAA’s rules and regulations governing drone use.

[ DJI ]

Don’t panic, but Clearpath and HEBI Robotics have armed the Jackal:

After locking eyes across a crowded room at ICRA 2019, Clearpath Robotics and HEBI Robotics basked in that warm and fuzzy feeling that comes with starting a new and exciting relationship. Over a conference hall coffee, they learned that the two companies have many overlapping interests. The most compelling was the realization that customers across a variety of industries are hunting for an elusive true love of their own – a robust but compact robotic platform combined with a long reach manipulator for remote inspection tasks.

After ICRA concluded, Arron Griffiths, Application Engineer at Clearpath, and Matthew Tesch, Software Engineer at HEBI, kept in touch and decided there had been enough magic in the air to warrant further exploration. A couple of months later, Matthew arrived at Clearpath to formally introduce the HEBI’s X-Series Arm to Clearpath’s Jackal UGV. It was love.

[ Clearpath ]

Thanks Dave!

I’m really not a fan of the people-carrying drones, but heavy lift cargo drones seem like a more okay idea.

Volocopter, the pioneer in Urban Air Mobility, presented the demonstrator of its VoloDrone. This marks Volocopters expansion into the logistics, agriculture, infrastructure and public services industry. The VoloDrone is an unmanned, fully electric, heavy-lift utility drone capable of carrying a payload of 200 kg (440 lbs) up to 40 km (25 miles). With a standardized payload attachment, VoloDrone can serve a great variety of purposes from transporting boxes, to liquids, to equipment and beyond. It can be remotely piloted or flown in automated mode on pre-set routes.

[ Volocopter ]

JAY is a mobile service robot that projects a display on the floor and plays sound with its speaker. By playing sounds and videos, it provides visual and audio entertainment in various places such as exhibition halls, airports, hotels, department stores and more.

[ Rainbow Robotics ]

The DARPA Subterranean Challenge Virtual Tunnel Circuit concluded this week—it was the same idea as the physical challenge that took place in August, just with a lot less IRL dirt.

The awards ceremony and team presentations are in this next video, and we’ll have more on this once we get back from IROS.

[ DARPA SubT ]

NASA is sending a mobile robot to the south pole of the Moon to get a close-up view of the location and concentration of water ice in the region and for the first time ever, actually sample the water ice at the same pole where the first woman and next man will land in 2024 under the Artemis program.

About the size of a golf cart, the Volatiles Investigating Polar Exploration Rover, or VIPER, will roam several miles, using its four science instruments — including a 1-meter drill — to sample various soil environments. Planned for delivery in December 2022, VIPER will collect about 100 days of data that will be used to inform development of the first global water resource maps of the Moon.

[ NASA ]

Happy Halloween from HEBI Robotics!

[ HEBI ]

Happy Halloween from Soft Robotics!

[ Soft Robotics ]

Halloween must be really, really confusing for autonomous cars.

[ Waymo ]

Once a year at Halloween, hardworking JPL engineers put their skills to the test in a highly competitive pumpkin carving contest. The result: A pumpkin gently landed on the Moon, its retrorockets smoldering, while across the room a Nemo-inspired pumpkin explored the sub-surface ocean of Jupiter moon Europa. Suffice to say that when the scientists and engineers at NASA’s Jet Propulsion Laboratory compete in a pumpkin-carving contest, the solar system’s the limit. Take a look at some of the masterpieces from 2019.

Now in its ninth year, the contest gives teams only one hour to carve and decorate their pumpkin though they can prepare non-pumpkin materials – like backgrounds, sound effects and motorized parts – ahead of time.

[ JPL ]

The online autonomous navigation and semantic mapping experiment presented [below] is conducted with the Cassie Blue bipedal robot at the University of Michigan. The sensors attached to the robot include an IMU, a 32-beam LiDAR and an RGB-D camera. The whole online process runs in real-time on a Jetson Xavier and a laptop with an i7 processor.

[ BPL ]

Misty II is now available to anyone who wants one, and she’s on sale for a mere $2900.

[ Misty ]

We leveraged LIDAR-based slam, in conjunction with our specialized relative localization sensor UVDAR to perform a de-centralized, communication-free swarm flight without the units knowing their absolute locations. The swarming and obstacle avoidance control is based on a modified Boids-like algorithm, while the whole swarm is controlled by directing a selected leader unit.

[ MRS ]

The MallARD robot is an autonomous surface vehicle (ASV), designed for the monitoring and inspection of wet storage facilities for example spent fuel pools or wet silos. The MallARD is holonomic, uses a LiDAR for localisation and features a robust trajectory tracking controller.

The University of Manchester’s researcher Dr Keir Groves designed and built the autonomous surface vehicle (ASV) for the challenge which came in the top three of the second round in Nov 2017. The MallARD went on to compete in a final 3rd round where it was deployed in a spent fuel pond at a nuclear power plant in Finland by the IAEA, along with two other entries. The MallARD came second overall, in November 2018.

[ RNE ]

Thanks Jennifer!

I sometimes get the sense that in the robotic grasping and manipulation world, suction cups are kinda seen as cheating at times. But, their nature allows you to do some pretty interesting things.

More clever octopus footage please.

[ CMU ]

A Personal, At-Home Teacher For Playful Learning: From academic topics to child-friendly news bulletins, fun facts and more, Miko 2 is packed with relevant and freshly updated content specially designed by educationists and child-specialists. Your little one won’t even realize they’re learning.

As we point out pretty much every time we post a video like this, keep in mind that you’re seeing a heavily edited version of a hypothetical best case scenario for how this robot can function. And things like “creating a relationship that they can then learn how to form with their peers” is almost certainly overselling things. But at $300 (shipping included), this may be a decent robot as long as your expectations are appropriately calibrated.

[ Miko ]

ICRA 2018 plenary talk by Rodney Brooks: “Robots and People: the Research Challenge.”

[ IEEE RAS ]

ICRA-X 2018 talk by Ron Arkin: “Lethal Autonomous Robots and the Plight of the Noncombatant.”

[ IEEE RAS ]

On the most recent episode of the AI Podcast, Lex Fridman interviews Garry Kasparov.

[ AI Podcast ] Continue reading →

Posted in Human Robots