Tag Archives: Montreal

#437751 Startup and Academics Find Path to ...

Engineers have been chasing a form of AI that could drastically lower the energy required to do typical AI things like recognize words and images. This analog form of machine learning does one of the key mathematical operations of neural networks using the physics of a circuit instead of digital logic. But one of the main things limiting this approach is that deep learning’s training algorithm, back propagation, has to be done by GPUs or other separate digital systems.

Now University of Montreal AI expert Yoshua Bengio, his student Benjamin Scellier, and colleagues at startup Rain Neuromorphics have come up with way for analog AIs to train themselves. That method, called equilibrium propagation, could lead to continuously learning, low-power analog systems of a far greater computational ability than most in the industry now consider possible, according to Rain CTO Jack Kendall.

Analog circuits could save power in neural networks in part because they can efficiently perform a key calculation, called multiply and accumulate. That calculation multiplies values from inputs according to various weights, and then it sums all those values up. Two fundamental laws of electrical engineering can basically do that, too. Ohm’s Law multiplies voltage and conductance to give current, and Kirchoff’s Current Law sums the currents entering a point. By storing a neural network’s weights in resistive memory devices, such as memristors, multiply-and-accumulate can happen completely in analog, potentially reducing power consumption by orders of magnitude.

The reason analog AI systems can’t train themselves today has a lot to do with the variability of their components. Just like real neurons, those in analog neural networks don’t all behave exactly alike. To do back propagation with analog components, you must build two separate circuit pathways. One going forward to come up with an answer (called inferencing), the other going backward to do the learning so that the answer becomes more accurate. But because of the variability of analog components, the pathways don't match up.

“You end up accumulating error as you go backwards through the network,” says Bengio. To compensate, a network would need lots of power-hungry analog-to-digital and digital-to-analog circuits, defeating the point of going analog.

Equilibrium propagation allows learning and inferencing to happen on the same network, partly by adjusting the behavior of the network as a whole. “What [equilibrium propagation] allows us to do is to say how we should modify each of these devices so that the overall circuit performs the right thing,” he says. “We turn the physical computation that is happening in the analog devices directly to our advantage.”

Right now, equilibrium propagation is only working in simulation. But Rain plans to have a hardware proof-of-principle in late 2021, according to CEO and cofounder Gordon Wilson. “We are really trying to fundamentally reimagine the hardware computational substrate for artificial intelligence, find the right clues from the brain, and use those to inform the design of this,” he says. The result could be what they call end-to-end analog AI systems that capable of running sophisticated robots or even playing a role in data centers. Both of those are currently considered beyond the capabilities of analog AI, which is now focused only on adding inferencing abilities to sensors and other low-power “edge” devices, while leaving the learning to GPUs. Continue reading

Posted in Human Robots

#435748 Video Friday: This Robot Is Like a ...

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!):

RSS 2019 – June 22-26, 2019 – Freiburg, Germany
Hamlyn Symposium on Medical Robotics – June 23-26, 2019 – London, U.K.
ETH Robotics Summer School – June 27-1, 2019 – Zurich, Switzerland
MARSS 2019 – July 1-5, 2019 – Helsinki, Finland
ICRES 2019 – July 29-30, 2019 – London, U.K.
DARPA SubT Tunnel Circuit – August 15-22, 2019 – Pittsburgh, Pa., USA
Let us know if you have suggestions for next week, and enjoy today’s videos.

It’s been a while since we last spoke to Joe Jones, the inventor of Roomba, about his solar-powered, weed-killing robot, called Tertill, which he was launching as a Kickstarter project. Tertill is now available for purchase (US $300) and is shipping right now.

[ Tertill ]

Usually, we don’t post videos that involve drone use that looks to be either illegal or unsafe. These flights over the protests in Hong Kong are almost certainly both. However, it’s also a unique perspective on the scale of these protests.

[ Team BlackSheep ]

ICYMI: iRobot announced this week that it has acquired Root Robotics.

[ iRobot ]

This Boston Dynamics parody video went viral this week.

The CGI is good but the gratuitous violence—even if it’s against a fake robot—is a bit too much?

This is still our favorite Boston Dynamics parody video:

[ Corridor ]

Biomedical Engineering Department Head Bin He and his team have developed the first-ever successful non-invasive mind-controlled robotic arm to continuously track a computer cursor.

[ CMU ]

Organic chemists, prepare to meet your replacement:

Automated chemical synthesis carries great promises of safety, efficiency and reproducibility for both research and industry laboratories. Current approaches are based on specifically-designed automation systems, which present two major drawbacks: (i) existing apparatus must be modified to be integrated into the automation systems; (ii) such systems are not flexible and would require substantial re-design to handle new reactions or procedures. In this paper, we propose a system based on a robot arm which, by mimicking the motions of human chemists, is able to perform complex chemical reactions without any modifications to the existing setup used by humans. The system is capable of precise liquid handling, mixing, filtering, and is flexible: new skills and procedures could be added with minimum effort. We show that the robot is able to perform a Michael reaction, reaching a yield of 34%, which is comparable to that obtained by a junior chemist (undergraduate student in Chemistry).

[ arXiv ] via [ NTU ]

So yeah, ICRA 2019 was huge and awesome. Here are some brief highlights.

[ Montreal Gazette ]

For about US $5, this drone will deliver raw meat and beer to you if you live on an uninhabited island in Tokyo Bay.

[ Nikkei ]

The Smart Microsystems Lab at Michigan State University has a new version of their Autonomous Surface Craft. It’s autonomous, open source, and awfully hard to sink.

[ SML ]

As drone shows go, this one is pretty good.

[ CCTV ]

Here’s a remote controlled robot shooting stuff with a very large gun.

[ HDT ]

Over a period of three quarters (September 2018 thru May 2019), we’ve had the opportunity to work with five graduating University of Denver students as they brought their idea for a Misty II arm extension to life.

[ Misty Robotics ]

If you wonder how it looks to inspect burners and superheaters of a boiler with an Elios 2, here you are! This inspection was performed by Svenska Elektrod in a peat-fired boiler for Vattenfall in Sweden. Enjoy!

[ Flyability ]

The newest Soft Robotics technology, mGrip mini fingers, made for tight spaces, small packaging, and delicate items, giving limitless opportunities for your applications.

[ Soft Robotics ]

What if legged robots were able to generate dynamic motions in real-time while interacting with a complex environment? Such technology would represent a significant step forward the deployment of legged systems in real world scenarios. This means being able to replace humans in the execution of dangerous tasks and to collaborate with them in industrial applications.

This workshop aims to bring together researchers from all the relevant communities in legged locomotion such as: numerical optimization, machine learning (ML), model predictive control (MPC) and computational geometry in order to chart the most promising methods to address the above-mentioned scientific challenges.

[ Num Opt Wkshp ]

Army researchers teamed with the U.S. Marine Corps to fly and test 3-D printed quadcopter prototypes a the Marine Corps Air Ground Combat Center in 29 Palms, California recently.

[ CCDC ARL ]

Lex Fridman’s Artificial Intelligence podcast featuring Rosalind Picard.

[ AI Podcast ]

In this week’s episode of Robots in Depth, per speaks with Christian Guttmann, executive director of the Nordic AI Artificial Intelligence Institute.

Christian Guttmann talks about AI and wanting to understand intelligence enough to recreate it. Christian has be focusing on AI in healthcare and has recently started to communicate the opportunities and challenges in artificial intelligence to the general public. This is something that the host Per Sjöborg is also very passionate about. We also get to hear about the Nordic AI institute and the work it does to inform all parts of society about AI.

[ Robots in Depth ] Continue reading

Posted in Human Robots

#435733 Robot Squid and Robot Scallop Showcase ...

Most underwater robots use one of two ways of getting around. Way one is with propellers, and way two is with fins. But animals have shown us that there are many more kinds of underwater locomotion, potentially offering unique benefits to robots. We’ll take a look at two papers from ICRA this year that showed bioinspired underwater robots moving in creative new ways: A jet-powered squid robot that can leap out of the water, plus a robotic scallop that moves just like the real thing.

Image: Beihang University

Prototype of the squid robot in (a) open and (b) folded states. The soft fins and arms are controlled by pneumatic actuators.

This “squid-like aquatic-aerial vehicle” from Beihang University in China is modeled after flying squids. Real squids, in addition to being tasty, propel themselves using water jets, and these jets are powerful enough that some squids can not only jump out of the water, but actually achieve controlled flight for a brief period by continuing to jet while in the air. The flight phase is extended through the use of fins as arms and wings to generate a little bit of lift. Real squids use this multimodal propulsion to escape predators, and it’s also much faster—a squid can double its normal swimming speed while in the air, flying at up to 50 body lengths per second.

The squid robot is powered primarily by compressed air, which it stores in a cylinder in its nose (do squids have noses?). The fins and arms are controlled by pneumatic actuators. When the robot wants to move through the water, it opens a value to release a modest amount of compressed air; releasing the air all at once generates enough thrust to fire the robot squid completely out of the water.

The jumping that you see at the end of the video is preliminary work; we’re told that the robot squid can travel between 10 and 20 meters by jumping, whereas using its jet underwater will take it just 10 meters. At the moment, the squid can only fire its jet once, but the researchers plan to replace the compressed air with something a bit denser, like liquid CO2, which will allow for extended operation and multiple jumps. There’s also plenty of work to do with using the fins for dynamic control, which the researchers say will “reveal the superiority of the natural flying squid movement.”

“Design and Experiments of a Squid-like Aquatic-aerial Vehicle With Soft Morphing Fins and Arms,” by Taogang Hou, Xingbang Yang, Haohong Su, Buhui Jiang, Lingkun Chen, Tianmiao Wang, and Jianhong Liang from Beihang University in China, was presented at ICRA 2019 in Montreal.

Image: EPFL

The EPFL researchers studied the morphology and function of a real scallop (a) to design their robot scallop (b), which consists of two shells connected at a hinge and enclosed by a flexible elastic membrane. The robot and animal both swim by rapidly, cyclicly opening and closing their shells to generate water jets for propulsion. When the robot shells open, water is drawn into the body through rear openings near the hinge. When the shells close rapidly, the water is forced out, propelling the robot forward (c).

RoboScallop, a “bivalve inspired swimming robot,” comes from EPFL’s Reconfigurable Robotics Laboratory, headed by Jamie Paik. Real scallops, in addition to being tasty, propel themselves by opening and closing their shells to generate jets of water out of their backsides. By repetitively opening their shells slowly and then closing quickly, scallops can generate forward thrust in a way that’s completely internal to their bodies. Relative to things like fins or spinning propellers, a scallop is simple and robust, especially as you scale down or start looking at large swarms of robots. The EPFL researchers describe their robotic scallop as representing “a unique combination of robust to hazards or sustained use, safe in delicate environments, and simple by design.”

And here’s how the real thing looks:

As you can see from the video, RoboScallop is safe to handle even while it’s operating, although a gentle nibbling is possible if you get too handsy with it. Since the robot sucks water in and then jets it out immediately, the design is resistant to fouling, which can be a significant problem in marine environments. The RoboScallop prototype weighs 65 grams, and tops out at a brisk 16 centimeters per second, while clapping (that’s the actual technical) at just over 2.5 Hz. While RoboScallop doesn’t yet steer, real scallops can change direction by jetting out more water on one side than the other, and RoboScallop should be able to do this as well. The researchers also suggest that RoboScallop itself could even double as a gripper, which as far as I know, is not something that real scallops can do.

“RoboScallop: A Bivalve-Inspired Swimming Robot,” by Matthew A. Robertson, Filip Efremov, and Jamie Paik, was presented at ICRA 2019 in Montreal. Continue reading

Posted in Human Robots

#435634 Robot Made of Clay Can Sculpt Its Own ...

We’re very familiar with a wide variety of transforming robots—whether for submarines or drones, transformation is a way of making a single robot adaptable to different environments or tasks. Usually, these robots are restricted to a discrete number of configurations—perhaps two or three different forms—because of the constraints imposed by the rigid structures that robots are typically made of.

Soft robotics has the potential to change all this, with robots that don’t have fixed forms but instead can transform themselves into whatever shape will enable them to do what they need to do. At ICRA in Montreal earlier this year, researchers from Yale University demonstrated a creative approach toward a transforming robot powered by string and air, with a body made primarily out of clay.

Photo: Evan Ackerman

The robot is actuated by two different kinds of “skin,” one layered on top of another. There’s a locomotion skin, made of a pattern of pneumatic bladders that can roll the robot forward or backward when the bladders are inflated sequentially. On top of that is the morphing skin, which is cable-driven, and can sculpt the underlying material into a variety of shapes, including spheres, cylinders, and dumbbells. The robot itself consists of both of those skins wrapped around a chunk of clay, with the actuators driven by offboard power and control. Here it is in action:

The Yale researchers have been experimenting with morphing robots that use foams and tensegrity structures for their bodies, but that stuff provides a “restoring force,” springing back into its original shape once the actuation stops. Clay is different because it holds whatever shape it’s formed into, making the robot more energy efficient. And if the dumbbell shape stops being useful, the morphing layer can just squeeze it back into a cylinder or a sphere.

While this robot, and the sample transformation shown in the video, are relatively simplistic, the researchers suggest some ways in which a more complex version could be used in the future:

Photo: IEEE Xplore

This robot’s morphing skin sculpts its clay body into different shapes.

Applications where morphing and locomotion might serve as complementary functions are abundant. For the example skins presented in this work, a search-and-rescue operation could use the clay as a medium to hold a payload such as sensors or transmitters. More broadly, applications include resource-limited conditions where supply chains for materiel are sparse. For example, the morphing sequence shown in Fig. 4 [above] could be used to transform from a rolling sphere to a pseudo-jointed robotic arm. With such a morphing system, it would be possible to robotically morph matter into different forms to perform different functions.

Read this article for free on IEEE Xplore until 5 September 2019

Morphing Robots Using Robotic Skins That Sculpt Clay, by Dylan S. Shah, Michelle C. Yuen, Liana G. Tilton, Ellen J. Yang, and Rebecca Kramer-Bottiglio from Yale University, was presented at ICRA 2019 in Montreal.

[ Yale Faboratory ]

< Back to IEEE Journal Watch Continue reading

Posted in Human Robots