Tag Archives: report

#438998 Foam Sword Fencing With a PR2 Is the ...

Most of what we cover in the Human Robot Interaction (HRI) space involves collaboration, because collaborative interactions tend to be productive, positive, and happy. Yay! But sometimes, collaboration is not what you want. Sometimes, you want competition.

Competition between humans and robots doesn’t have to be a bad thing, in the same way that competition between humans and humans doesn’t have to be a bad thing. There are all kinds of scenarios in which humans respond favorably to competition, and exercise is an obvious example.

Studies have shown that humans can perform significantly better when they’re exercising competitively as opposed to when they’re exercising individually. And while researchers have looked at whether robots can be effective exercise coaches (they can be), there hasn’t been a lot of exploration of physical robots actually competing directly with humans. Roboticists from the University of Washington decided to put adversarial exercise robots to the test, and they did it by giving a PR2 a giant foam sword. Awesome.

This exercise game matches a PR2 with a human in a zero-sum competitive fencing game with foam swords. Expecting the PR2 to actually be a competitive fencer isn’t realistic because, like, it’s a PR2. Instead, the objective of the game is for the human to keep their foam sword within a target area near the PR2 while also avoiding the PR2’s low-key sword-waving. A VR system allows the user to see the target area, while also giving the system a way to track the user’s location and pose.

Looks like fun, right? It’s also exercise, at least in the sense that the user’s heart rate nearly doubled over their resting heart rate during the highest scoring game. This is super preliminary research, though, and there’s still a lot of work to do. It’ll be important to figure out how skilled a competitive robot should be in order to keep providing a reasonable challenge to a human who gradually improves over time, while also being careful to avoid generating any negative reactions. For example, the robot should probably not beat you over the head with its foam sword, even if that’s a highly effective strategy for getting your heart rate up.

Competitive Physical Human-Robot Game Play, by Boling Yang, Xiangyu Xie, Golnaz Habibi, and Joshua R. Smith from the University of Washington and MIT, was presented as a late-breaking report at the ACM/IEEE International Conference on Human-Robot Interaction. Continue reading

Posted in Human Robots

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

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

#438738 This Week’s Awesome Tech Stories From ...

ARTIFICIAL INTELLIGENCE
A New Artificial Intelligence Makes Mistakes—on Purpose
Will Knight | Wired
“It took about 50 years for computers to eviscerate humans in the venerable game of chess. A standard smartphone can now play the kind of moves that make a grandmaster’s head spin. But one artificial intelligence program is taking a few steps backward, to appreciate how average humans play—blunders and all.”

CRYPTOCURRENCY
Bitcoin’s Price Rises to $50,000 as Mainstream Institutions Hop On
Timothy B. Lee | Ars Technica
“Bitcoin’s price is now far above the previous peak of $19,500 reached in December 2017. Bitcoin’s value has risen by almost 70 percent since the start of 2021. No single factor seems to be driving the cryptocurrency’s rise. Instead, the price is rising as more and more mainstream organizations are deciding to treat it as an ordinary investment asset.”

SCIENCE
Million-Year-Old Mammoth Teeth Contain Oldest DNA Ever Found
Jeanne Timmons | Gizmodo
“An international team of scientists has sequenced DNA from mammoth teeth that is at least a million years old, if not older. This research, published today in Nature, not only provides exciting new insight into mammoth evolutionary history, it reveals an entirely unknown lineage of ancient mammoth.”

SCIENCE
Scientists Accidentally Discover Strange Creatures Under a Half Mile of Ice
Matt Simon | Wired
“i‘It’s like, bloody hell!’ Smith says. ‘It’s just one big boulder in the middle of a relatively flat seafloor. It’s not as if the seafloor is littered with these things.’ Just his luck to drill in the only wrong place. Wrong place for collecting seafloor muck, but the absolute right place for a one-in-a-million shot at finding life in an environment that scientists didn’t reckon could support much of it.”

BIOTECH
Highest-Resolution Images of DNA Reveal It’s Surprisingly Jiggly
George Dvorsky | Gizmodo
“Scientists have captured the highest-resolution images ever taken of DNA, revealing previously unseen twisting and squirming behaviors. …These hidden movements were revealed by computer simulations fed with the highest-resolution images ever taken of a single molecule of DNA. The new study is exposing previously unseen behaviors in the self-replicating molecule, and this research could eventually lead to the development of powerful new genetic therapies.”

TRANSPORTATION
The First Battery-Powered Tanker Is Coming to Tokyo
Maria Gallucci | IEEE Spectrum
“The Japanese tanker is Corvus’s first fully-electric coastal freighter project; the company hopes the e5 will be the first of hundreds more just like it. ‘We see it [as] a beachhead for the coastal shipping market globally,’ Puchalski said. ‘There are many other coastal freighter types that are similar in size and energy demand.’ The number of battery-powered ships has ballooned from virtually zero a decade ago to hundreds worldwide.”

SPACE
Report: NASA’s Only Realistic Path for Humans on Mars Is Nuclear Propulsion
Eric Berger | Ars Technica
“Conducted at the request of NASA, a broad-based committee of experts assessed the viability of two means of propulsion—nuclear thermal and nuclear electric—for a human mission launching to Mars in 2039. ‘One of the primary takeaways of the report is that if we want to send humans to Mars, and we want to do so repeatedly and in a sustainable way, nuclear space propulsion is on the path,’ said [JPL’s] Bobby Braun.”

NASA’s Perseverance Rover Successfully Lands on Mars
Joey Roulette | The Verge
“Perseverance hit Mars’ atmosphere on time at 3:48PM ET at speeds of about 12,100 miles per hour, diving toward the surface in an infamously challenging sequence engineers call the “seven minutes of terror.” With an 11-minute comms delay between Mars and Earth, the spacecraft had to carry out its seven-minute plunge at all by itself with a wickedly complex set of pre-programmed instructions.”

ENVIRONMENT
A First-of-Its-Kind Geoengineering Experiment Is About to Take Its First Step
James Temple | MIT Technology Review
“When I visited Frank Keutsch in the fall of 2019, he walked me down to the lab, where the tube, wrapped in gray insulation, ran the length of a bench in the back corner. By filling it with the right combination of gases, at particular temperatures and pressures, Keutsch and his colleagues had simulated the conditions some 20 kilometers above Earth’s surface. In testing how various chemicals react in this rarefied air, the team hoped to conduct a crude test of a controversial scheme known as solar geoengineering.”

Image Credit: Garcia / Unsplash Continue reading

Posted in Human Robots

#438553 New Drone Software Handles Motor ...

Good as some drones are becoming at obstacle avoidance, accidents do still happen. And as far as robots go, drones are very much on the fragile side of things. Any sort of significant contact between a drone and almost anything else usually results in a catastrophic, out-of-control spin followed by a death plunge to the ground. Bad times. Bad, expensive times.

A few years ago, we saw some interesting research into software that can keep the most common drone form factor, the quadrotor, aloft and controllable even after the failure of one motor. The big caveat to that software was that it relied on GPS for state estimation, meaning that without a GPS signal, the drone is unable to get the information it needs to keep itself under control. In a paper recently accepted to RA-L, researchers at the University of Zurich report that they have developed a vision-based system that brings state estimation completely on-board. The upshot: potentially any drone with some software and a camera can keep itself safe even under the most challenging conditions.

A few years ago, we wrote about first author Sihao Sun’s work on high speed controlled flight of a quadrotor with a non-functional motor. But that innovation relied on an external motion capture system. Since then, Sun has moved from Tu Delft to Davide Scaramuzza’s lab at UZH, and it looks like he’s been able to combine his work on controlled spinning flight with the Robotics and Perception Group’s expertise in vision. Now, a downward-facing camera is all it takes for a spinning drone to remain stable and controllable:

Remember, this software isn’t just about guarding against motor failure. Drone motors themselves don’t just up and fail all that often, either with respect to their software or hardware. But they do represent the most likely point of failure for any drone, usually because when you run into something, what ultimately causes your drone to crash is damage to a motor or a propeller that causes loss of control.

The reason that earlier solutions relied on GPS was because the spinning drone needs a method of state estimation—that is, in order to be closed-loop controllable, the drone needs to have a reasonable understanding of what its position is and how that position is changing over time. GPS is an easy way to take care of this, but GPS is also an external system that doesn’t work everywhere. Having a state estimation system that’s completely internal to the drone itself is much more fail safe, and Sun got his onboard system to work through visual feature tracking with a downward-facing camera, even as the drone is spinning at over 20 rad/s.

While the system works well enough with a regular downward-facing camera—something that many consumer drones are equipped with for stabilization purposes—replacing it with an event camera (you remember event cameras, right?) makes the performance even better, especially in low light.

For more details on this, including what you’re supposed to do with a rapidly spinning partially disabled quadrotor (as well as what it’ll take to make this a standard feature on consumer hardware), we spoke with Sihao Sun via email.

IEEE Spectrum: what usually happens when a drone spinning this fast lands? Is there any way to do it safely?

Sihao Sun: Our experience shows that we can safely land the drone while it is spinning. When the range sensor measurements are lower than a threshold (around 10 cm, indicating that the drone is close to the ground), we switch off the rotors. During the landing procedure, despite the fast spinning motion, the thrust direction oscillates around the gravity vector, thus the drone touches the ground with its legs without damaging other components.

Can your system handle more than one motor failure?

Yes, the system can also handle the failure of two opposing rotors. However, if two adjacent rotors or more than two rotors fail, our method cannot save the quadrotor. Some research has shown that it is possible to control a quadrotor with only one remaining rotor. But the drone requires a very special inertial property, which is hard to satisfy in real applications.

How different is your system's performance from a similar system that relies on GPS, in a favorable environment?

In a favorable environment, our system outperforms those relying on GPS signals because it obtains better position estimates. Since a damaged quadrotor spins fast, the accelerometer readings are largely affected by centrifugal forces. When the GPS signal is lost or degraded, a drone relying on GPS needs to integrate these biased accelerometer measurements for position estimation, leading to large position estimation errors. Feeding these erroneous estimates to the flight controller can easily crash the drone.

When you say that your solution requires “only onboard sensors and computation,” are those requirements specialized, or would they be generally compatible with the current generation of recreational and commercial quadrotors?

We use an NVIDIA Jetson TX2 to run our solution, which includes two parts: the control algorithm and the vision-based state estimation algorithm. The control algorithm is lightweight; thus, we believe that it is compatible with the current generation of quadrotors. On the other hand, the vision-based state estimation requires relatively more computational resources, which may not be affordable for cheap recreational platforms. But this is not an issue for commercial quadrotors because many of them have more powerful processors than a TX2.

What else can event cameras be used for, in recreational or commercial applications?

Many drone applications can benefit from event cameras, especially those in high-speed or low-light conditions, such as autonomous drone racing, cave exploration, drone delivery during night time, etc. Event cameras also consume very little power, which is a significant advantage for energy-critical missions, such as planetary aerial vehicles for Mars explorations. Regarding space applications, we are currently collaborating with JPL to explore the use of event cameras to address the key limitations of standard cameras for the next Mars helicopter.

[ UZH RPG ] Continue reading

Posted in Human Robots

#437990 Video Friday: Record-Breaking Drone Show ...

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!):

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

A new parent STAR robot is presented. The parent robot has a tail on which the child robot can climb. By collaborating together, the two robots can reach locations that neither can reach on its own.

The parent robot can also supply the child robot with energy by recharging its batteries. The parent STAR can dispatch and recuperate the child STAR automatically (when aligned). The robots are fitted with sensors and controllers and have automatic capabilities but make no decisions on their own.

[ Bio-Inspired and Medical Robotics Lab ]

How TRI trains its robots.

[ TRI ]

The only thing more satisfying than one SCARA robot is two SCARA robots working together.

[ Fanuc ]

I'm not sure that this is strictly robotics, but it's so cool that it's worth a watch anyway.

[ Shinoda & Makino Lab ]

Flying insects heavily rely on optical flow for visual navigation and flight control. Roboticists have endowed small flying robots with optical flow control as well, since it requires just a tiny vision sensor. However, when using optical flow, the robots run into two problems that insects appear to have overcome. Firstly, since optical flow only provides mixed information on distances and velocities, using it for control leads to oscillations when getting closer to obstacles. Secondly, since optical flow provides very little information on obstacles in the direction of motion, it is hardest to detect obstacles that the robot is actually going to collide with! We propose a solution to these problems by means of a learning process.

[ Nature ]

A new Guinness World Record was set on Friday in north China for the longest animation performed by 600 unmanned aerial vehicles (UAVs).

[ Xinhua ]

Translucency is prevalent in everyday scenes. As such, perception of transparent objects is essential for robots to perform manipulation. In this work, we propose LIT, a two-stage method for transparent object pose estimation using light-field sensing and photorealistic rendering.

[ University of Michigan ] via [ Fetch Robotics ]

This paper reports the technological progress and performance of team “CERBERUS” after participating in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge.

And here's a video report on the SubT Urban Beta Course performance:

[ CERBERUS ]

Congrats to Energy Robotics on 2 million euros in seed funding!

[ Energy Robotics ]

Thanks Stefan!

In just 2 minutes, watch HEBI robotics spending 23 minutes assembling a robot arm.

HEBI Robotics is hosting a webinar called 'Redefining the Robotic Arm' next week, which you can check out at the link below.

[ HEBI Robotics ]

Thanks Hardik!

Achieving versatile robot locomotion requires motor skills which can adapt to previously unseen situations. We propose a Multi-Expert Learning Architecture (MELA) that learns to generate adaptive skills from a group of representative expert skills. During training, MELA is first initialised by a distinct set of pre-trained experts, each in a separate deep neural network (DNN). Then by learning the combination of these DNNs using a Gating Neural Network (GNN), MELA can acquire more specialised experts and transitional skills across various locomotion modes.

[ Paper ]

Since the dawn of history, advances in science and technology have pursued “power” and “accuracy.” Initially, “hardness” in machines and materials was sought for reliable operations. In our area of Science of Soft Robots, we have combined emerging academic fields aimed at “softness” to increase the exposure and collaboration of researchers in different fields.

[ Science of Soft Robots ]

A team from the Laboratory of Robotics and IoT for Smart Precision Agriculture and Forestry at INESC TEC – Technology and Science are creating a ROS stack solution using Husky UGV for precision field crop agriculture.

[ Clearpath Robotics ]

Associate Professor Christopher J. Hasson in the Department of Physical Therapy is the director Neuromotor Systems Laboratory at Northeastern University. There he is working with a robotic arm to provide enhanced assistance to physical therapy patients, while maintaining the intimate therapist and patient relationship.

[ Northeastern ]

Mobile Robotic telePresence (MRP) systems aim to support enhanced collaboration between remote and local members of a given setting. But MRP systems also put the remote user in positions where they frequently rely on the help of local partners. Getting or ‘recruiting’ such help can be done with various verbal and embodied actions ranging in explicitness. In this paper, we look at how such recruitment occurs in video data drawn from an experiment where pairs of participants (one local, one remote) performed a timed searching task.

[ Microsoft Research ]

A presentation [from Team COSTAR] for the American Geophysical Union annual fall meeting on the application of robotic multi-sensor 3D Mapping for scientific exploration of caves. Lidar-based 3D maps are combined with visual/thermal/spectral/gas sensors to provide rich 3D context for scientific measurements map.

[ COSTAR ] Continue reading

Posted in Human Robots