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#439036 Video Friday: Shadow Plays Jenga, and ...

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!):

RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
ICRA 2021 – May 30-5, 2021 – Xi'an, China
DARPA SubT Finals – September 21-23, 2021 – Louisville, KY, USA
WeRobot 2021 – September 23-25, 2021 – Coral Gables, FL, USA
Let us know if you have suggestions for next week, and enjoy today’s videos.

The Shadow Robot team couldn't resist! Our Operator, Joanna, is using the Shadow Teleoperation System which, fun and games aside, can help those in difficult, dangerous and distant jobs.

Shadow could challenge this MIT Jenga-playing robot, but I bet they wouldn't win:

[ Shadow Robot ]

Digit is gradually stomping the Agility Robotics logo into a big grassy field fully autonomously.

[ Agility Robotics ]

This is a pretty great and very short robotic magic show.

[ Mario the Magician ]

A research team at the Georgia Institute of Technology has developed a modular solution for drone delivery of larger packages without the need for a complex fleet of drones of varying sizes. By allowing teams of small drones to collaboratively lift objects using an adaptive control algorithm, the strategy could allow a wide range of packages to be delivered using a combination of several standard-sized vehicles.

[ GA Tech ]

I've seen this done using vision before, but Flexiv's Rizon 4s can keep a ball moving along a specific trajectory using only force sensing and control.

[ Flexiv ]

Thanks Yunfan!

This combination of a 3D aerial projection system and a sensing interface can be used as an interactive and intuitive control system for things like robot arms, but in this case, it's being used to make simulated pottery. Much less messy than the traditional way of doing it.

More details on Takafumi Matsumaru's work at the Bio-Robotics & Human-Mechatronics Laboratory at Waseda University at the link below.

[ BLHM ]

U.S. Vice President Kamala Harris called astronauts Shannon Walker and Kate Rubins on the ISS, and they brought up Astrobee, at which point Shannon reaches over and rips Honey right off of her charging dock to get her on camera.

[ NASA ]

Here's a quick three minute update on Perseverance and Ingenuity from JPL.

[ Mars 2020 ]

Rigid grippers used in existing aerial manipulators require precise positioning to achieve successful grasps and transmit large contact forces that may destabilize the drone. This limits the speed during grasping and prevents “dynamic grasping,” where the drone attempts to grasp an object while moving. On the other hand, biological systems (e.g. birds) rely on compliant and soft parts to dampen contact forces and compensate for grasping inaccuracy, enabling impressive feats. This paper presents the first prototype of a soft drone—a quadrotor where traditional (i.e. rigid) landing gears are replaced with a soft tendon-actuated gripper to enable aggressive grasping.

[ MIT ]

In this video we present results from a field deployment inside the Løkken Mine underground pyrite mine in Norway. The Løkken mine was operative from 1654 to 1987 and contains narrow but long corridors, alongside vast rooms and challenging vertical stopes. In this field study we evaluated selected autonomous exploration and visual search capabilities of a subset of the aerial robots of Team CERBERUS towards the goal of complete subterranean autonomy.

[ Team CERBERUS ]

What you can do with a 1,000 FPS projector with a high speed tracking system.

[ Ishikawa Group ]

ANYbotics’ collaboration with BASF, one of the largest global chemical manufacturers, displays the efficiency, quality, and scalability of robotic inspection and data-collection capabilities in complex industrial environments.

[ ANYbotics ]

Does your robot arm need a stylish jacket?

[ Fraunhofer ]

Trossen Robotics unboxes a Unitree A1, and it's actually an unboxing where they have to figure out everything from scratch.

[ Trossen ]

Robots have learned to drive cars, assist in surgeries―and vacuum our floors. But can they navigate the unwritten rules of a busy sidewalk? Until they can, robotics experts Leila Takayama and Chris Nicholson believe, robots won’t be able to fulfill their immense potential. In this conversation, Chris and Leila explore the future of robotics and the role open source will play in it.

[ Red Hat ]

Christoph Bartneck's keynote at the 6th Joint UAE Symposium on Social Robotics, focusing on what roles robots can play during the Covid crisis and why so many social robots fail in the market.

[ HIT Lab ]

Decision-making based on arbitrary criteria is legal in some contexts, such as employment, and not in others, such as criminal sentencing. As algorithms replace human deciders, HAI-EIS fellow Kathleen Creel argues arbitrariness at scale is morally and legally problematic. In this HAI seminar, she explains how the heart of this moral issue relates to domination and a lack of sufficient opportunity for autonomy. It relates in interesting ways to the moral wrong of discrimination. She proposes technically informed solutions that can lessen the impact of algorithms at scale and so mitigate or avoid the moral harm identified.

[ Stanford HAI ]

Sawyer B. Fuller speaks on Autonomous Insect-Sized Robots at the UC Berkeley EECS Colloquium series.

Sub-gram (insect-sized) robots have enormous potential that is largely untapped. From a research perspective, their extreme size, weight, and power (SWaP) constraints also forces us to reimagine everything from how they compute their control laws to how they are fabricated. These questions are the focus of the Autonomous Insect Robotics Laboratory at the University of Washington. I will discuss potential applications for insect robots and recent advances from our group. These include the first wireless flights of a sub-gram flapping-wing robot that weighs barely more than a toothpick. I will describe efforts to expand its capabilities, including the first multimodal ground-flight locomotion, the first demonstration of steering control, and how to find chemical plume sources by integrating the smelling apparatus of a live moth. I will also describe a backpack for live beetles with a steerable camera and conceptual design of robots that could scale all the way down to the “gnat robots” first envisioned by Flynn & Brooks in the ‘80s.

[ UC Berkeley ]

Thanks Fan!

Joshua Vander Hook, Computer Scientist, NIAC Fellow, and Technical Group Supervisor at NASA JPL, presents an overview of the AI Group(s) at JPL, and recent work on single and multi-agent autonomous systems supporting space exploration, Earth science, NASA technology development, and national defense programs.

[ UMD ] Continue reading

Posted in Human Robots

#439012 Video Friday: Man-Machine Synergy ...

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!):

RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
ICRA 2021 – May 30-5, 2021 – Xi'an, China
DARPA SubT Finals – September 21-23, 2021 – Louisville, KY, USA
WeRobot 2021 – September 23-25, 2021 – Coral Gables, FL, USA
Let us know if you have suggestions for next week, and enjoy today's videos.

Man-Machine Synergy Effectors, Inc. is a Japanese company working on an absolutely massive “human machine synergistic effect device,” which is a huge robot controlled by a nearby human using a haptic rig.

From the look of things, the next generation will be able to move around. Whoa.

[ MMSE ]

This method of loading and unloading AMRs without having them ever stop moving is so obvious that there must be some equally obvious reason why I've never seen it done in practice.

The LoadRunner is able to transport and sort parcels weighing up to 30 kilograms. This makes it the perfect luggage carrier for airports. These AI-driven go-carts can also work in concert as larger collectives to carry large, heavy and bulky objects. Every LoadRunner can also haul up to four passive trailers. Powered by four electric motors, the LoadRunner sharply brakes at just the right moment right in front of its destination and the payload slides from the robot onto the delivery platform.

[ Fraunhofer ] via [ Gizmodo ]

Ayato Kanada at Kyushu University wrote in to share this clever “dislocatable joint,” a way of combining continuum and rigid robots.

[ Paper ]

Thanks Ayato!

The DodgeDrone challenge revisits the popular dodgeball game in the context of autonomous drones. Specifically, participants will have to code navigation policies to fly drones between waypoints while avoiding dynamic obstacles. Drones are fast but fragile systems: as soon as something hits them, they will crash! Since objects will move towards the drone with different speeds and acceleration, smart algorithms are required to avoid them!

This could totally happen in real life, and we need to be prepared for it!

[ DodgeDrone Challenge ]

In addition to winning the Best Student Design Competition CREATIVITY Award at HRI 2021, this paper would also have won the Best Paper Title award, if that award existed.

[ Paper ]

Robots are traditionally bound by a fixed morphology during their operational lifetime, which is limited to adapting only their control strategies. Here we present the first quadrupedal robot that can morphologically adapt to different environmental conditions in outdoor, unstructured environments.

We show that the robot exploits its training to effectively transition between different morphological configurations, exhibiting substantial performance improvements over a non-adaptive approach. The demonstrated benefits of real-world morphological adaptation demonstrate the potential for a new embodied way of incorporating adaptation into future robotic designs.

[ Nature ]

A drone video shot in a Minneapolis bowling alley was hailed as an instant classic. One Hollywood veteran said it “adds to the language and vocabulary of cinema.” One IEEE Spectrum editor said “hey that's pretty cool.”

[ Bryant Lake Bowl ]

It doesn't take a robot to convince me to buy candy, but I think if I buy candy from Relay it's a business expense, right?

[ RIS ]

DARPA is making progress on its AI dogfighting program, with physical flight tests expected this year.

[ DARPA ACE ]

Unitree Robotics has realized that the Empire needs to be overthrown!

[ Unitree ]

Windhover Labs, an emerging leader in open and reliable flight software and hardware, announces the upcoming availability of its first hardware product, a low cost modular flight computer for commercial drones and small satellites.

[ Windhover ]

As robots and autonomous systems are poised to become part of our everyday lives, the University of Michigan and Ford are opening a one-of-a-kind facility where they’ll develop robots and roboticists that help make lives better, keep people safer and build a more equitable society.

[ U Michigan ]

The adaptive robot Rizon combined with a new hybrid electrostatic and gecko-inspired gripping pad developed by Stanford BDML can manipulate bulky, non-smooth items in the most effort-saving way, which broadens the applications in retail and household environments.

[ Flexiv ]

Thanks Yunfan!

I don't know why anyone would want things to get MORE icy, but if you do for some reason, you can make it happen with a Husky.

Is winter over yet?

[ Clearpath ]

Skip ahead to about 1:20 to see a pair of Gita robots following a Spot following a human like a chain of lil’ robot duckings.

[ PFF ]

Here are a couple of retro robotics videos, one showing teleoperated humanoids from 2000, and the other showing a robotic guide dog from 1976 (!)

[ Tachi Lab ]

Thanks Fan!

If you missed Chad Jenkins' talk “That Ain’t Right: AI Mistakes and Black Lives” last time, here's another opportunity to watch from Robotics Today, and it includes a top notch panel discussion at the end.

[ Robotics Today ]

Since its founding in 1979, the Robotics Institute (RI) at Carnegie Mellon University has been leading the world in robotics research and education. In the mid 1990s, RI created NREC as the applied R&D center within the Institute with a specific mission to apply robotics technology in an impactful way on real-world applications. In this talk, I will go over numerous R&D programs that I have led at NREC in the past 25 years.

[ CMU ] Continue reading

Posted in Human Robots

#439010 Video Friday: Nanotube-Powered Insect ...

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 Conference]
RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
ICRA 2021 – May 30-5, 2021 – Xi'an, China
Let us know if you have suggestions for next week, and enjoy today's videos.

If you’ve ever swatted a mosquito away from your face, only to have it return again (and again and again), you know that insects can be remarkably acrobatic and resilient in flight. Those traits help them navigate the aerial world, with all of its wind gusts, obstacles, and general uncertainty. Such traits are also hard to build into flying robots, but MIT Assistant Professor Kevin Yufeng Chen has built a system that approaches insects’ agility.

Chen’s actuators can flap nearly 500 times per second, giving the drone insect-like resilience. “You can hit it when it’s flying, and it can recover,” says Chen. “It can also do aggressive maneuvers like somersaults in the air.” And it weighs in at just 0.6 grams, approximately the mass of a large bumble bee. The drone looks a bit like a tiny cassette tape with wings, though Chen is working on a new prototype shaped like a dragonfly.

[ MIT ]

National Robotics Week is April 3-11, 2021!

[ NRW ]

This is in a motion capture environment, but still, super impressive!

[ Paper ]

Thanks Fan!

Why wait for Boston Dynamics to add an arm to your Spot if you can just do it yourself?

[ ETHZ ]

This video shows the deep-sea free swimming of soft robot in the South China Sea. The soft robot was grasped by a robotic arm on ‘HAIMA’ ROV and reached the bottom of the South China Sea (depth of 3,224 m). After the releasing, the soft robot was actuated with an on-board AC voltage of 8 kV at 1 Hz and demonstrated free swimming locomotion with its flapping fins.

Um, did they bring it back?

[ Nature ]

Quadruped Yuki Mini is 12 DOF robot equipped with a Raspberry Pi that runs ROS. Also, BUNNIES!

[ Lingkang Zhang ]

Thanks Lingkang!

Deployment of drone swarms usually relies on inter-agent communication or visual markers that are mounted on the vehicles to simplify their mutual detection. The vswarm package enables decentralized vision-based control of drone swarms without relying on inter-agent communication or visual fiducial markers. The results show that the drones can safely navigate in an outdoor environment despite substantial background clutter and difficult lighting conditions.

[ Vswarm ]

A conventional adopted method for operating a waiter robot is based on the static position control, where pre-defined goal positions are marked on a map. However, this solution is not optimal in a dynamic setting, such as in a coffee shop or an outdoor catering event, because the customers often change their positions. We explore an alternative human-robot interface design where a human operator communicates the identity of the customer to the robot instead. Inspired by how [a] human communicates, we propose a framework for communicating a visual goal to the robot, through interactive two-way communications.

[ Paper ]

Thanks Poramate!

In this video, LOLA reacts to undetected ground height changes, including a drop and leg-in-hole experiment. Further tests show the robustness to vertical disturbances using a seesaw. The robot is technically blind, not using any camera-based or prior information on the terrain.

[ TUM ]

RaiSim is a cross-platform multi-body physics engine for robotics and AI. It fully supports Linux, Mac OS, and Windows.

[ RaiSim ]

Thanks Fan!

The next generation of LoCoBot is here. The LoCoBot is an ROS research rover for mapping, navigation and manipulation (optional) that enables researchers, educators and students alike to focus on high level code development instead of hardware and building out lower level code. Development on the LoCoBot is simplified with open source software, full ROS-mapping and navigation packages and modular opensource Python API that allows users to move the platform as well as (optional) manipulator in as few as 10 lines of code.

[ Trossen ]

MIT Media Lab Research Specialist Dr. Kate Darling looks at how robots are portrayed in popular film and TV shows.

Kate's book, The New Breed: What Our History with Animals Reveals about Our Future with Robots can be pre-ordered now and comes out next month.

[ Kate Darling ]

The current autonomous mobility systems for planetary exploration are wheeled rovers, limited to flat, gently-sloping terrains and agglomerate regolith. These vehicles cannot tolerate instability and operate within a low-risk envelope (i.e., low-incline driving to avoid toppling). Here, we present ‘Mars Dogs’ (MD), four-legged robotic dogs, the next evolution of extreme planetary exploration.

[ Team CoSTAR ]

In 2020, first-year PhD students at the MIT Media Lab were tasked with a special project—to reimagine the Lab and write sci-fi stories about the MIT Media Lab in the year 2050. “But, we are researchers. We don't only write fiction, we also do science! So, we did what scientists do! We used a secret time machine under the MIT dome to go to the year 2050 and see what’s going on there! Luckily, the Media Lab still exists and we met someone…really cool!” Enjoy this interview of Cyber Joe, AI Mentor for MIT Media Lab Students of 2050.

[ MIT ]

In this talk, we will give an overview of the diverse research we do at CSIRO’s Robotics and Autonomous Systems Group and delve into some specific technologies we have developed including SLAM and Legged robotics. We will also give insights into CSIRO’s participation in the current DARPA Subterranean Challenge where we are deploying a fleet of heterogeneous robots into GPS-denied unknown underground environments.

[ GRASP Seminar ]

Marco Hutter (ETH) and Hae-Won Park (KAIST) talk about “Robotics Inspired by Nature.”

[ Swiss-Korean Science Club ]

Thanks Fan!

In this keynote, Guy Hoffman Assistant Professor and the Mills Family Faculty Fellow in the Sibley School of Mechanical and Aerospace Engineering at Cornell University, discusses “The Social Uncanny of Robotic Companions.”

[ Designerly HRI ] Continue reading

Posted in Human Robots

#439004 Video Friday: A Walking, Wheeling ...

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!):

RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
ICRA 2021 – May 30-5, 2021 – Xi'an, China
Let us know if you have suggestions for next week, and enjoy today's videos.

This is a pretty terrible video, I think because it was harvested from WeChat, which is where Tencent decided to premiere its new quadruped robot.

Not bad, right? Its name is Max, it has a top speed of 25 kph thanks to its elbow wheels, and we know almost nothing else about it.

[ Tencent ]

Thanks Fan!

Can't bring yourself to mask-shame others? Build a robot to do it for you instead!

[ GitHub ]

Researchers at Georgia Tech have recently developed an entirely soft, long-stroke electromagnetic actuator using liquid metal, compliant magnetic composites, and silicone polymers. The robot was inspired by the motion of the Xenia coral, which pulses its polyps to circulate oxygen under water to promote photosynthesis.

In this work, power applied to soft coils generates an electromagnetic field, which causes the internal compliant magnet to move upward. This forces the squishy silicone linkages to convert linear to the rotational motion with an arclength of up to 42 mm with a bandwidth up to 30 Hz. This highly deformable, fast, and long-stroke actuator topology can be utilized for a variety of applications from biomimicry to fully-soft grasping to wearables applications.

[ Paper ] via [ Georgia Tech ]

Thanks Noah!

Jueying Mini Lite may look a little like a Boston Dynamics Spot, but according to DeepRobotics, its coloring is based on Bruce Lee's Kung Fu clothes.

[ DeepRobotics ]

Henrique writes, “I would like to share with you the supplementary video of our recent work accepted to ICRA 2021. The video features a quadruped and a full-size humanoid performing dynamic jumps, after a brief animated intro of what direct transcription is. Me and my colleagues have put a lot of hard work into this, and I am very proud of the results.”

Making big robots jump is definitely something to be proud of!

[ SLMC Edinburgh ]

Thanks Henrique!

The finals of the Powered Exoskeleton Race for Cybathlon Global 2020.

[ Cybathlon ]

Thanks Fan!

It's nice that every once in a while, the world can get excited about science and robots.

[ NASA ]

Playing the Imperial March over footage of an army of black quadrupeds may not be sending quite the right message.

[ Unitree ]

Kod*lab PhD students Abriana Stewart-Height, Diego Caporale and Wei-Hsi Chen, with former Kod*lab student Garrett Wenger were on set in the summer of 2019 to operate RHex for the filming of Lapsis, a first feature film by director and screenwriter Noah Hutton.

[ Kod*lab ]

In class 2.008, Design and Manufacturing II, mechanical engineering students at MIT learn the fundamental principles of manufacturing at scale by designing and producing their own yo-yos. Instructors stress the importance of sustainable practices in the global supply chain.

[ MIT ]

A short history of robotics, from ABB.

[ ABB ]

In this paper, we propose a whole-body planning framework that unifies dynamic locomotion and manipulation tasks by formulating a single multi-contact optimal control problem. This is demonstrated in a set of real hardware experiments done in free-motion, such as base or end-effector pose tracking, and while pushing/pulling a heavy resistive door. Robustness against model mismatches and external disturbances is also verified during these test cases.

[ Paper ]

This paper presents PANTHER, a real-time perception-aware (PA) trajectory planner in dynamic environments. PANTHER plans trajectories that avoid dynamic obstacles while also keeping them in the sensor field of view (FOV) and minimizing the blur to aid in object tracking.

Extensive hardware experiments in unknown dynamic environments with all the computation running onboard are presented, with velocities of up to 5.8 m/s, and with relative velocities (with respect to the obstacles) of up to 6.3 m/s. The only sensors used are an IMU, a forward-facing depth camera, and a downward-facing monocular camera.

[ MIT ]

With our SaaS solution, we enable robots to inspect industrial facilities. One of the robots our software supports, is the Boston Dynamics Spot robot. In this video we demonstrate how autonomous industrial inspection with the Boston Dynamics Spot Robot is performed with our teach and repeat solution.

[ Energy Robotics ]

In this week’s episode of Tech on Deck, learn about our first technology demonstration sent to Station: The Robotic Refueling Mission. This tech demo helped us develop the tools and techniques needed to robotically refuel a satellite in space, an important capability for space exploration.

[ NASA ]

At Covariant we are committed to research and development that will bring AI Robotics to the real world. As a part of this, we believe it's important to educate individuals on how these exciting innovations will make a positive, fundamental and global impact for years to come. In this presentation, our co-founder Pieter Abbeel breaks down his thoughts on the current state of play for AI robotics.

[ Covariant ]

How do you fly a helicopter on Mars? It takes Ingenuity and Perseverance. During this technology demo, Farah Alibay and Tim Canham will get into the details of how these craft will manage this incredible task.

[ NASA ]

Complex real-world environments continue to present significant challenges for fielding robotic teams, which often face expansive spatial scales, difficult and dynamic terrain, degraded environmental conditions, and severe communication constraints. Breakthrough technologies call for integrated solutions across autonomy, perception, networking, mobility, and human teaming thrusts. As such, the DARPA OFFSET program and the DARPA Subterranean Challenge seek novel approaches and new insights for discovering and demonstrating these innovative technologies, to help close critical gaps for robotic operations in complex urban and underground environments.

[ UPenn ] Continue reading

Posted in Human Robots

#438982 Quantum Computing and Reinforcement ...

Deep reinforcement learning is having a superstar moment.

Powering smarter robots. Simulating human neural networks. Trouncing physicians at medical diagnoses and crushing humanity’s best gamers at Go and Atari. While far from achieving the flexible, quick thinking that comes naturally to humans, this powerful machine learning idea seems unstoppable as a harbinger of better thinking machines.

Except there’s a massive roadblock: they take forever to run. Because the concept behind these algorithms is based on trial and error, a reinforcement learning AI “agent” only learns after being rewarded for its correct decisions. For complex problems, the time it takes an AI agent to try and fail to learn a solution can quickly become untenable.

But what if you could try multiple solutions at once?

This week, an international collaboration led by Dr. Philip Walther at the University of Vienna took the “classic” concept of reinforcement learning and gave it a quantum spin. They designed a hybrid AI that relies on both quantum and run-of-the-mill classic computing, and showed that—thanks to quantum quirkiness—it could simultaneously screen a handful of different ways to solve a problem.

The result is a reinforcement learning AI that learned over 60 percent faster than its non-quantum-enabled peers. This is one of the first tests that shows adding quantum computing can speed up the actual learning process of an AI agent, the authors explained.

Although only challenged with a “toy problem” in the study, the hybrid AI, once scaled, could impact real-world problems such as building an efficient quantum internet. The setup “could readily be integrated within future large-scale quantum communication networks,” the authors wrote.

The Bottleneck
Learning from trial and error comes intuitively to our brains.

Say you’re trying to navigate a new convoluted campground without a map. The goal is to get from the communal bathroom back to your campsite. Dead ends and confusing loops abound. We tackle the problem by deciding to turn either left or right at every branch in the road. One will get us closer to the goal; the other leads to a half hour of walking in circles. Eventually, our brain chemistry rewards correct decisions, so we gradually learn the correct route. (If you’re wondering…yeah, true story.)

Reinforcement learning AI agents operate in a similar trial-and-error way. As a problem becomes more complex, the number—and time—of each trial also skyrockets.

“Even in a moderately realistic environment, it may simply take too long to rationally respond to a given situation,” explained study author Dr. Hans Briegel at the Universität Innsbruck in Austria, who previously led efforts to speed up AI decision-making using quantum mechanics. If there’s pressure that allows “only a certain time for a response, an agent may then be unable to cope with the situation and to learn at all,” he wrote.

Many attempts have tried speeding up reinforcement learning. Giving the AI agent a short-term “memory.” Tapping into neuromorphic computing, which better resembles the brain. In 2014, Briegel and colleagues showed that a “quantum brain” of sorts can help propel an AI agent’s decision-making process after learning. But speeding up the learning process itself has eluded our best attempts.

The Hybrid AI
The new study went straight for that previously untenable jugular.

The team’s key insight was to tap into the best of both worlds—quantum and classical computing. Rather than building an entire reinforcement learning system using quantum mechanics, they turned to a hybrid approach that could prove to be more practical. Here, the AI agent uses quantum weirdness as it’s trying out new approaches—the “trial” in trial and error. The system then passes the baton to a classical computer to give the AI its reward—or not—based on its performance.

At the heart of the quantum “trial” process is a quirk called superposition. Stay with me. Our computers are powered by electrons, which can represent only two states—0 or 1. Quantum mechanics is far weirder, in that photons (particles of light) can simultaneously be both 0 and 1, with a slightly different probability of “leaning towards” one or the other.

This noncommittal oddity is part of what makes quantum computing so powerful. Take our reinforcement learning example of navigating a new campsite. In our classic world, we—and our AI—need to decide between turning left or right at an intersection. In a quantum setup, however, the AI can (in a sense) turn left and right at the same time. So when searching for the correct path back to home base, the quantum system has a leg up in that it can simultaneously explore multiple routes, making it far faster than conventional, consecutive trail and error.

“As a consequence, an agent that can explore its environment in superposition will learn significantly faster than its classical counterpart,” said Briegel.

It’s not all theory. To test out their idea, the team turned to a programmable chip called a nanophotonic processor. Think of it as a CPU-like computer chip, but it processes particles of light—photons—rather than electricity. These light-powered chips have been a long time in the making. Back in 2017, for example, a team from MIT built a fully optical neural network into an optical chip to bolster deep learning.

The chips aren’t all that exotic. Nanophotonic processors act kind of like our eyeglasses, which can carry out complex calculations that transform light that passes through them. In the glasses case, they let people see better. For a light-based computer chip, it allows computation. Rather than using electrical cables, the chips use “wave guides” to shuttle photons and perform calculations based on their interactions.

The “error” or “reward” part of the new hardware comes from a classical computer. The nanophotonic processor is coupled to a traditional computer, where the latter provides the quantum circuit with feedback—that is, whether to reward a solution or not. This setup, the team explains, allows them to more objectively judge any speed-ups in learning in real time.

In this way, a hybrid reinforcement learning agent alternates between quantum and classical computing, trying out ideas in wibbly-wobbly “multiverse” land while obtaining feedback in grounded, classic physics “normality.”

A Quantum Boost
In simulations using 10,000 AI agents and actual experimental data from 165 trials, the hybrid approach, when challenged with a more complex problem, showed a clear leg up.

The key word is “complex.” The team found that if an AI agent has a high chance of figuring out the solution anyway—as for a simple problem—then classical computing works pretty well. The quantum advantage blossoms when the task becomes more complex or difficult, allowing quantum mechanics to fully flex its superposition muscles. For these problems, the hybrid AI was 63 percent faster at learning a solution compared to traditional reinforcement learning, decreasing its learning effort from 270 guesses to 100.

Now that scientists have shown a quantum boost for reinforcement learning speeds, the race for next-generation computing is even more lit. Photonics hardware required for long-range light-based communications is rapidly shrinking, while improving signal quality. The partial-quantum setup could “aid specifically in problems where frequent search is needed, for example, network routing problems” that’s prevalent for a smooth-running internet, the authors wrote. With a quantum boost, reinforcement learning may be able to tackle far more complex problems—those in the real world—than currently possible.

“We are just at the beginning of understanding the possibilities of quantum artificial intelligence,” said lead author Walther.

Image Credit: Oleg Gamulinskiy from Pixabay Continue reading

Posted in Human Robots