Tag Archives: crash

#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

#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

#438014 Meet Blueswarm, a Smart School of ...

Anyone who’s seen an undersea nature documentary has marveled at the complex choreography that schooling fish display, a darting, synchronized ballet with a cast of thousands.

Those instinctive movements have inspired researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), and the Wyss Institute for Biologically Inspired Engineering. The results could improve the performance and dependability of not just underwater robots, but other vehicles that require decentralized locomotion and organization, such as self-driving cars and robotic space exploration.

The fish collective called Blueswarm was created by a team led by Radhika Nagpal, whose lab is a pioneer in self-organizing systems. The oddly adorable robots can sync their movements like biological fish, taking cues from their plastic-bodied neighbors with no external controls required. Nagpal told IEEE Spectrum that this marks a milestone, demonstrating complex 3D behaviors with implicit coordination in underwater robots.

“Insights from this research will help us develop future miniature underwater swarms that can perform environmental monitoring and search in visually-rich but fragile environments like coral reefs,” Nagpal said. “This research also paves a way to better understand fish schools, by synthetically recreating their behavior.”

The research is published in Science Robotics, with Florian Berlinger as first author. Berlinger said the “Bluedot” robots integrate a trio of blue LED lights, a lithium-polymer battery, a pair of cameras, a Raspberry Pi computer and four controllable fins within a 3D-printed hull. The fish-lens cameras detect LED’s of their fellow swimmers, and apply a custom algorithm to calculate distance, direction and heading.

Based on that simple production and detection of LED light, the team proved that Blueswarm could self-organize behaviors, including aggregation, dispersal and circle formation—basically, swimming in a clockwise synchronization. Researchers also simulated a successful search mission, an autonomous Finding Nemo. Using their dispersion algorithm, the robot school spread out until one could detect a red light in the tank. Its blue LEDs then flashed, triggering the aggregation algorithm to gather the school around it. Such a robot swarm might prove valuable in search-and-rescue missions at sea, covering miles of open water and reporting back to its mates.

“Each Bluebot implicitly reacts to its neighbors’ positions,” Berlinger said. The fish—RoboCod, perhaps?—also integrate a Wifi module to allow uploading new behaviors remotely. The lab’s previous efforts include a 1,000-strong army of “Kilobots,” and a robotic construction crew inspired by termites. Both projects operated in two-dimensional space. But a 3D environment like air or water posed a tougher challenge for sensing and movement.

In nature, Berlinger notes, there’s no scaly CEO to direct the school’s movements. Nor do fish communicate their intentions. Instead, so-called “implicit coordination” guides the school’s collective behavior, with individual members executing high-speed moves based on what they see their neighbors doing. That decentralized, autonomous organization has long fascinated scientists, including in robotics.

“In these situations, it really benefits you to have a highly autonomous robot swarm that is self-sufficient. By using implicit rules and 3D visual perception, we were able to create a system with a high degree of autonomy and flexibility underwater where things like GPS and WiFi are not accessible.”

Berlinger adds the research could one day translate to anything that requires decentralized robots, from self-driving cars and Amazon warehouse vehicles to exploration of faraway planets, where poor latency makes it impossible to transmit commands quickly. Today’s semi-autonomous cars face their own technical hurdles in reliably sensing and responding to their complex environments, including when foul weather obscures onboard sensors or road markers, or when they can’t fix position via GPS. An entire subset of autonomous-car research involves vehicle-to-vehicle (V2V) communications that could give cars a hive mind to guide individual or collective decisions— avoiding snarled traffic, driving safely in tight convoys, or taking group evasive action during a crash that’s beyond their sensory range.

“Once we have millions of cars on the road, there can’t be one computer orchestrating all the traffic, making decisions that work for all the cars,” Berlinger said.

The miniature robots could also work long hours in places that are inaccessible to humans and divers, or even large tethered robots. Nagpal said the synthetic swimmers could monitor and collect data on reefs or underwater infrastructure 24/7, and work into tiny places without disturbing fragile equipment or ecosystems.

“If we could be as good as fish in that environment, we could collect information and be non-invasive, in cluttered environments where everything is an obstacle,” Nagpal said. Continue reading

Posted in Human Robots

#437851 Boston Dynamics’ Spot Robot Dog ...

Boston Dynamics has been fielding questions about when its robots are going to go on sale and how much they’ll cost for at least a dozen years now. I can say this with confidence, because that’s how long I’ve been a robotics journalist, and I’ve been pestering them about it the entire time. But it’s only relatively recently that the company started to make a concerted push away from developing robots exclusively for the likes of DARPA into platforms with more commercial potential, starting with a compact legged robot called Spot, first introduced in 2016.

Since then, we’ve been following closely as Spot has gone from a research platform to a product, and today, Boston Dynamics is announcing the final step in that process: commercial availability. You can now order a Spot Explorer Kit from the Boston Dynamics online store for US $74,500 (plus tax), shipping included, with delivery in 6 to 8 weeks. FINALLY!

Over the past 10 months or so, Boston Dynamics has leased Spot robots to carefully selected companies, research groups, and even a few individuals as part of their early adopter program—that’s where all of the clips in the video below came from. While there are over 100 Spots out in the world right now, getting one of them has required convincing Boston Dynamics up front that you knew more or less exactly what you wanted to do and how you wanted to do it. If you’re a big construction company or the Jet Propulsion Laboratory or Adam Savage, that’s all well and good, but for other folks who think that a Spot could be useful for them somehow and want to give it a shot, this new availability provides a fewer-strings attached opportunity to do some experimentation with the robot.

There’s a lot of cool stuff going on in that video, but we were told that the one thing that really stood out to the folks at Boston Dynamics was a 2-second clip that you can see on the left-hand side of the screen from 0:19 to 0:21. In it, Spot is somehow managing to walk across a spider web of rebar without getting tripped up, at faster than human speed. This isn’t something that Spot was specifically programmed to do, and in fact the Spot User Guide specifically identifies “rebar mesh” as an unsafe operating environment. But the robot just handles it, and that’s a big part of what makes Spot so useful—its ability to deal with (almost) whatever you can throw at it.

Before you get too excited, Boston Dynamics is fairly explicit that the current license for the robot is intended for commercial use, and the company specifically doesn’t want people to be just using it at home for fun. We know this because we asked (of course we asked), and they told us “we specifically don’t want people to just be using it at home for fun.” Drat. You can still buy one as an individual, but you have to promise that you’ll follow the terms of use and user guidelines, and it sounds like using a robot in your house might be the second-fastest way to invalidate your warranty:

SPOT IS AN AMAZING ROBOT, BUT IS NOT CERTIFIED SAFE FOR IN-HOME USE OR INTENDED FOR USE NEAR CHILDREN OR OTHERS WHO MAY NOT APPRECIATE THE HAZARDS ASSOCIATED WITH ITS OPERATION.

Not being able to get Spot to play with your kids may be disappointing, but for those of you with the sort of kids who are also students, the good news is that Boston Dynamics has carved out a niche for academic institutions, which can buy Spot at a discounted price. And if you want to buy a whole pack of Spots, there’s a bulk discount for Enterprise users as well.

What do you get for $74,500? All this!

Spot robot
Spot battery (2x)
Spot charger
Tablet controller and charger
Robot case for storage and transportation
FREE SHIPPING!

Photo: Boston Dynamics

The basic package includes the robot, two batteries, charger, a tablet controller, and a storage case.

You can view detailed specs here.

So is $75k a lot of money for a robot like Spot, or not all that much? We don’t have many useful points of comparison, partially because it’s not clear to what extent other pre-commercial quadrupedal robots (like ANYmal or Aliengo) share capabilities and features with Spot. For more perspective on Spot’s price tag, we spoke to Michael Perry, vice president of business development at Boston Dynamics.

IEEE Spectrum: Why is Spot so affordable?

Michael Perry: The main goal of selling the robot at this stage is to try to get it into the hands of as many application developers as possible, so that we can learn from the community what the biggest driver of value is for Spot. As a platform, unlocking the value of an ecosystem is our core focus right now.

Spectrum: Why is Spot so expensive?

Perry: Expensive is relative, but compared to the initial prototypes of Spot, we’ve been able to drop down the cost pretty significantly. One key thing has been designing it for robustness—we’ve put hundreds and hundreds of hours on the robot to make sure that it’s able to be successful when it falls, or when it has an electrostatic discharge. We’ve made sure that it’s able to perceive a wide variety of environments that are difficult for traditional vision-based sensors to handle. A lot of that engineering is baked into the core product so that you don’t have to worry about the mobility or robotic side of the equation, you can just focus on application development.

Photos: Boston Dynamics

Accessories for Spot include [clockwise from top left]: Spot GXP with additional ports for payload integration; Spot CAM with panorama camera and advanced comms; Spot CAM+ with pan-tilt-zoom camera for inspections; Spot EAP with lidar to enhance autonomy on large sites; Spot EAP+ with Spot CAM camera plus lidar; and Spot CORE for additional processing power.

The $75k that you’ll pay for the Spot Explorer Kit, it’s important to note, is just the base price for the robot. As with other things that fall into this price range (like a luxury car), there are all kinds of fun ways to drive that cost up with accessories, although for Spot, some of those accessories will be necessary for many (if not most) applications. For example, a couple of expansion ports to make it easier to install your own payloads on Spot will run you $1,275. An additional battery is $4,620. And if you want to really get some work done, the Enhanced Autonomy Package (with 360 cameras, lights, better comms, and a Velodyne VLP-16) will set you back an additional $34,570. If you were hoping for an arm, you’ll have to wait until the end of the year.

Each Spot also includes a year’s worth of software updates and a warranty, although the standard warranty just covers “defects related to materials and workmanship” not “I drove my robot off a cliff” or “I tried to take my robot swimming.” For that sort of thing (user error) to be covered, you’ll need to upgrade to the $12,000 Spot CARE premium service plan to cover your robot for a year as long as you don’t subject it to willful abuse, which both of those examples I just gave probably qualify as.

While we’re on the subject of robot abuse, Boston Dynamics has very sensibly devoted a substantial amount of the Spot User Guide to help new users understand how they should not be using their robot, in order to “lessen the risk of serious injury, death, or robot and other property damage.” According to the guide, some things that could cause Spot to fall include holes, cliffs, slippery surfaces (like ice and wet grass), and cords. Spot’s sensors also get confused by “transparent, mirrored, or very bright obstacles,” and the guide specifically says Spot “may crash into glass doors and windows.” Also this: “Spot cannot predict trajectories of moving objects. Do not operate Spot around moving objects such as vehicles, children, or pets.”

We should emphasize that this is all totally reasonable, and while there are certainly a lot of things to be aware of, it’s frankly astonishing that these are the only things that Boston Dynamics explicitly warns users against. Obviously, not every potentially unsafe situation or thing is described above, but the point is that Boston Dynamics is willing to say to new users, “here’s your robot, go do stuff with it” without feeling the need to hold their hand the entire time.

There’s one more thing to be aware of before you decide to buy a Spot, which is the following:

“All orders will be subject to Boston Dynamics’ Terms and Conditions of Sale which require the beneficial use of its robots.”

Specifically, this appears to mean that you aren’t allowed to (or supposed to) use the robot in a way that could hurt living things, or “as a weapon, or to enable any weapon.” The conditions of sale also prohibit using the robot for “any illegal or ultra-hazardous purpose,” and there’s some stuff in there about it not being cool to use Spot for “nuclear, chemical, or biological weapons proliferation, or development of missile technology,” which seems weirdly specific.

“Once you make a technology more broadly available, the story of it starts slipping out of your hands. Our hope is that ahead of time we’re able to clearly articulate the beneficial uses of the robot in environments where we think the robot has a high potential to reduce the risk to people, rather than potentially causing harm.”
—Michael Perry, Boston Dynamics

I’m very glad that Boston Dynamics is being so upfront about requiring that Spot is used beneficially. However, it does put the company in a somewhat challenging position now that these robots are being sold. Boston Dynamics can (and will) perform some amount of due-diligence before shipping a Spot, but ultimately, once the robots are in someone else’s hands, there’s only so much that BD can do.

Spectrum: Why is beneficial use important to Boston Dynamics?

Perry: One of the key things that we’ve highlighted many times in our license and terms of use is that we don’t want to see the robot being used in any way that inflicts physical harm on people or animals. There are philosophical reasons for that—I think all of us don’t want to see our technology used in a way that would hurt people. But also from a business perspective, robots are really terrible at conveying intention. In order for the robot to be helpful long-term, it has to be trusted as a piece of technology. So rather than looking at a robot and wondering, “is this something that could potentially hurt me,” we want people to think “this is a robot that’s here to help me.” To the extent that people associate Boston Dynamics with cutting edge robots, we think that this is an important stance for the rollout of our first commercial product. If we find out that somebody’s violated our terms of use, their warranty is invalidated, we won’t repair their product, and we have a licensing timeout that would prevent them from accessing their robot after that timeout has expired. It’s a remediation path, but we do think that it’s important to at least provide that as something that helps enforce our position on use of our technology.

It’s very important to keep all of this in context: Spot is a tool. It’s got some autonomy and the appearance of agency, but it’s still just doing what people tell it to do, even if those things might be unsafe. If you read through the user guide, it’s clear how much of an effort Boston Dynamics is making to try to convey the importance of safety to Spot users—and ultimately, barring some unforeseen and catastrophic software or hardware issues, safety is about the users, rather than Boston Dynamics or Spot itself. I bring this up because as we start seeing more and more Spots doing things without Boston Dynamics watching over them quite so closely, accidents are likely inevitable. Spot might step on someone’s foot. It might knock someone over. If Spot was perfectly safe, it wouldn’t be useful, and we have to acknowledge that its impressive capabilities come with some risks, too.

Photo: Boston Dynamics

Each Spot includes a year’s worth of software updates and a warranty, although the standard warranty just covers “defects related to materials and workmanship” not “I drove my robot off a cliff.”

Now that Spot is on the market for real, we’re excited to see who steps up and orders one. Depending on who the potential customer is, Spot could either seem like an impossibly sophisticated piece of technology that they’d never be able to use, or a magical way of solving all of their problems overnight. In reality, it’s of course neither of those things. For the former (folks with an idea but without a lot of robotics knowledge or experience), Spot does a lot out of the box, but BD is happy to talk with people and facilitate connections with partners who might be able to integrate specific software and hardware to get Spot to do a unique task. And for the latter (who may also be folks with an idea but without a lot of robotics knowledge or experience), BD’s Perry offers a reminder Spot is not Rosie the Robot, and would be equally happy to talk about what the technology is actually capable of doing.

Looking forward a bit, we asked Perry whether Spot’s capabilities mean that customers are starting to think beyond using robots to simply replace humans, and are instead looking at them as a way of enabling a completely different way of getting things done.

Spectrum: Do customers interested in Spot tend to think of it as a way of replacing humans at a specific task, or as a system that can do things that humans aren’t able to do?

Perry: There are what I imagine as three levels of people understanding the robot applications. Right now, we’re at level one, where you take a person out of this dangerous, dull job, and put a robot in. That’s the entry point. The second level is, using the robot, can we increase the production of that task? For example, take site documentation on a construction site—right now, people do 360 image capture of a site maybe once a week, and they might do a laser scan of the site once per project. At the second level, the question is, what if you were able to get that data collection every day, or multiple times a day? What kinds of benefits would that add to your process? To continue the construction example, the third level would be, how could we completely redesign this space now that we know that this type of automation is available? To take one example, there are some things that we cannot physically build because it’s too unsafe for people to be a part of that process, but if you were to apply robotics to that process, then you could potentially open up a huge envelope of design that has been inaccessible to people.

To order a Spot of your very own, visit shop.bostondynamics.com.

A version of this post appears in the August 2020 print issue as “$74,500 Will Fetch You a Spot.” Continue reading

Posted in Human Robots

#437816 As Algorithms Take Over More of the ...

Algorithms play an increasingly prominent part in our lives, governing everything from the news we see to the products we buy. As they proliferate, experts say, we need to make sure they don’t collude against us in damaging ways.

Fears of malevolent artificial intelligence plotting humanity’s downfall are a staple of science fiction. But there are plenty of nearer-term situations in which relatively dumb algorithms could do serious harm unintentionally, particularly when they are interlocked in complex networks of relationships.

In the economic sphere a high proportion of decision-making is already being offloaded to machines, and there have been warning signs of where that could lead if we’re not careful. The 2010 “Flash Crash,” where algorithmic traders helped wipe nearly $1 trillion off the stock market in minutes, is a textbook example, and widespread use of automated trading software has been blamed for the increasing fragility of markets.

But another important place where algorithms could undermine our economic system is in price-setting. Competitive markets are essential for the smooth functioning of the capitalist system that underpins Western society, which is why countries like the US have strict anti-trust laws that prevent companies from creating monopolies or colluding to build cartels that artificially inflate prices.

These regulations were built for an era when pricing decisions could always be traced back to a human, though. As self-adapting pricing algorithms increasingly decide the value of products and commodities, those laws are starting to look unfit for purpose, say the authors of a paper in Science.

Using algorithms to quickly adjust prices in a dynamic market is not a new idea—airlines have been using them for decades—but previously these algorithms operated based on rules that were hard-coded into them by programmers.

Today the pricing algorithms that underpin many marketplaces, especially online ones, rely on machine learning instead. After being set an overarching goal like maximizing profit, they develop their own strategies based on experience of the market, often with little human oversight. The most advanced also use forms of AI whose workings are opaque even if humans wanted to peer inside.

In addition, the public nature of online markets means that competitors’ prices are available in real time. It’s well-documented that major retailers like Amazon and Walmart are engaged in a never-ending bot war, using automated software to constantly snoop on their rivals’ pricing and inventory.

This combination of factors sets the stage perfectly for AI-powered pricing algorithms to adopt collusive pricing strategies, say the authors. If given free reign to develop their own strategies, multiple pricing algorithms with real-time access to each other’s prices could quickly learn that cooperating with each other is the best way to maximize profits.

The authors note that researchers have already found evidence that pricing algorithms will spontaneously develop collusive strategies in computer-simulated markets, and a recent study found evidence that suggests pricing algorithms may be colluding in Germany’s retail gasoline market. And that’s a problem, because today’s anti-trust laws are ill-suited to prosecuting this kind of behavior.

Collusion among humans typically involves companies communicating with each other to agree on a strategy that pushes prices above the true market value. They then develop rules to determine how they maintain this markup in a dynamic market that also incorporates the threat of retaliatory pricing to spark a price war if another cartel member tries to undercut the agreed pricing strategy.

Because of the complexity of working out whether specific pricing strategies or prices are the result of collusion, prosecutions have instead relied on communication between companies to establish guilt. That’s a problem because algorithms don’t need to communicate to collude, and as a result there are few legal mechanisms to prosecute this kind of collusion.

That means legal scholars, computer scientists, economists, and policymakers must come together to find new ways to uncover, prohibit, and prosecute the collusive rules that underpin this behavior, say the authors. Key to this will be auditing and testing pricing algorithms, looking for things like retaliatory pricing, price matching, and aggressive responses to price drops but not price rises.

Once collusive pricing rules are uncovered, computer scientists need to come up with ways to constrain algorithms from adopting them without sacrificing their clear efficiency benefits. It could also be helpful to make preventing this kind of collusive behavior the responsibility of the companies deploying them, with stiff penalties for those who don’t keep their algorithms in check.

One problem, though, is that algorithms may evolve strategies that humans would never think of, which could make spotting this behavior tricky. Imbuing courts with the technical knowledge and capacity to investigate this kind of evidence will also prove difficult, but getting to grips with these problems is an even more pressing challenge than it might seem at first.

While anti-competitive pricing algorithms could wreak havoc, there are plenty of other arenas where collusive AI could have even more insidious effects, from military applications to healthcare and insurance. Developing the capacity to predict and prevent AI scheming against us will likely be crucial going forward.

Image Credit: Pexels from Pixabay Continue reading

Posted in Human Robots