Tag Archives: society

#438731 Video Friday: Perseverance Lands on Mars

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.

Hmm, did anything interesting happen in robotics yesterday week?

Obviously, we're going to have tons more on the Mars Rover and Mars Helicopter over the next days, weeks, months, years, and (if JPL's track record has anything to say about it) decades. Meantime, here's what's going to happen over the next day or two:

[ Mars 2020 ]

PLEN hopes you had a happy Valentine's Day!

[ PLEN ]

Unitree dressed up a whole bunch of Laikago quadrupeds to take part in the 2021 Spring Festival Gala in China.

[ Unitree ]

Thanks Xingxing!

Marine iguanas compete for the best nesting sites on the Galapagos Islands. Meanwhile RoboSpy Iguana gets involved in a snot sneezing competition after the marine iguanas return from the sea.

[ Spy in the Wild ]

Tails, it turns out, are useful for almost everything.

[ DART Lab ]

Partnered with MD-TEC, this video demonstrates use of teleoperated robotic arms and virtual reality interface to perform closed suction for self-ventilating tracheostomy patients during COVID -19 outbreak. Use of closed suction is recommended to minimise aerosol generated during this procedure. This robotic method avoids staff exposure to virus to further protect NHS.

[ Extend Robotics ]

Fotokite is a safe, practical way to do local surveillance with a drone.

I just wish they still had a consumer version 🙁

[ Fotokite ]

How to confuse fish.

[ Harvard ]

Army researchers recently expanded their research area for robotics to a site just north of Baltimore. Earlier this year, Army researchers performed the first fully-autonomous tests onsite using an unmanned ground vehicle test bed platform, which serves as the standard baseline configuration for multiple programmatic efforts within the laboratory. As a means to transition from simulation-based testing, the primary purpose of this test event was to capture relevant data in a live, operationally-relevant environment.

[ Army ]

Flexiv's new RIZON 10 robot hopes you had a happy Valentine's Day!

[ Flexiv ]

Thanks Yunfan!

An inchworm-inspired crawling robot (iCrawl) is a 5 DOF robot with two legs; each with an electromagnetic foot to crawl on the metal pipe surfaces. The robot uses a passive foot-cap underneath an electromagnetic foot, enabling it to be a versatile pipe-crawler. The robot has the ability to crawl on the metal pipes of various curvatures in horizontal and vertical directions. The robot can be used as a new robotic solution to assist close inspection outside the pipelines, thus minimizing downtime in the oil and gas industry.

[ Paper ]

Thanks Poramate!

A short film about Robot Wars from Blender Magazine in 1995.

[ YouTube ]

While modern cameras provide machines with a very well-developed sense of vision, robots still lack such a comprehensive solution for their sense of touch. The talk will present examples of why the sense of touch can prove crucial for a wide range of robotic applications, and a tech demo will introduce a novel sensing technology targeting the next generation of soft robotic skins. The prototype of the tactile sensor developed at ETH Zurich exploits the advances in camera technology to reconstruct the forces applied to a soft membrane. This technology has the potential to revolutionize robotic manipulation, human-robot interaction, and prosthetics.

[ ETHZ ]

Thanks Markus!

Quadrupedal robotics has reached a level of performance and maturity that enables some of the most advanced real-world applications with autonomous mobile robots. Driven by excellent research in academia and industry all around the world, a growing number of platforms with different skills target different applications and markets. We have invited a selection of experts with long-standing experience in this vibrant research area

[ IFRR ]

Thanks Fan!

Since January 2020, more than 300 different robots in over 40 countries have been used to cope with some aspect of the impact of the coronavirus pandemic on society. The majority of these robots have been used to support clinical care and public safety, allowing responders to work safely and to handle the surge in infections. This panel will discuss how robots have been successfully used and what is needed, both in terms of fundamental research and policy, for robotics to be prepared for the future emergencies.

[ IFRR ]

At Skydio, we ship autonomous robots that are flown at scale in complex, unknown environments every day. We’ve invested six years of R&D into handling extreme visual scenarios not typically considered by academia nor encountered by cars, ground robots, or AR applications. Drones are commonly in scenes with few or no semantic priors on the environment and must deftly navigate thin objects, extreme lighting, camera artifacts, motion blur, textureless surfaces, vibrations, dirt, smudges, and fog. These challenges are daunting for classical vision, because photometric signals are simply inconsistent. And yet, there is no ground truth for direct supervision of deep networks. We’ll take a detailed look at these issues and how we’ve tackled them to push the state of the art in visual inertial navigation, obstacle avoidance, rapid trajectory planning. We will also cover the new capabilities on top of our core navigation engine to autonomously map complex scenes and capture all surfaces, by performing real-time 3D reconstruction across multiple flights.

[ UPenn ] Continue reading

Posted in Human Robots

#437974 China Wants to Be the World’s AI ...

China’s star has been steadily rising for decades. Besides slashing extreme poverty rates from 88 percent to under 2 percent in just 30 years, the country has become a global powerhouse in manufacturing and technology. Its pace of growth may slow due to an aging population, but China is nonetheless one of the world’s biggest players in multiple cutting-edge tech fields.

One of these fields, and perhaps the most significant, is artificial intelligence. The Chinese government announced a plan in 2017 to become the world leader in AI by 2030, and has since poured billions of dollars into AI projects and research across academia, government, and private industry. The government’s venture capital fund is investing over $30 billion in AI; the northeastern city of Tianjin budgeted $16 billion for advancing AI; and a $2 billion AI research park is being built in Beijing.

On top of these huge investments, the government and private companies in China have access to an unprecedented quantity of data, on everything from citizens’ health to their smartphone use. WeChat, a multi-functional app where people can chat, date, send payments, hail rides, read news, and more, gives the CCP full access to user data upon request; as one BBC journalist put it, WeChat “was ahead of the game on the global stage and it has found its way into all corners of people’s existence. It could deliver to the Communist Party a life map of pretty much everybody in this country, citizens and foreigners alike.” And that’s just one (albeit big) source of data.

Many believe these factors are giving China a serious leg up in AI development, even providing enough of a boost that its progress will surpass that of the US.

But there’s more to AI than data, and there’s more to progress than investing billions of dollars. Analyzing China’s potential to become a world leader in AI—or in any technology that requires consistent innovation—from multiple angles provides a more nuanced picture of its strengths and limitations. In a June 2020 article in Foreign Affairs, Oxford fellows Carl Benedikt Frey and Michael Osborne argued that China’s big advantages may not actually be that advantageous in the long run—and its limitations may be very limiting.

Moving the AI Needle
To get an idea of who’s likely to take the lead in AI, it could help to first consider how the technology will advance beyond its current state.

To put it plainly, AI is somewhat stuck at the moment. Algorithms and neural networks continue to achieve new and impressive feats—like DeepMind’s AlphaFold accurately predicting protein structures or OpenAI’s GPT-3 writing convincing articles based on short prompts—but for the most part these systems’ capabilities are still defined as narrow intelligence: completing a specific task for which the system was painstakingly trained on loads of data.

(It’s worth noting here that some have speculated OpenAI’s GPT-3 may be an exception, the first example of machine intelligence that, while not “general,” has surpassed the definition of “narrow”; the algorithm was trained to write text, but ended up being able to translate between languages, write code, autocomplete images, do math, and perform other language-related tasks it wasn’t specifically trained for. However, all of GPT-3’s capabilities are limited to skills it learned in the language domain, whether spoken, written, or programming language).

Both AlphaFold’s and GPT-3’s success was due largely to the massive datasets they were trained on; no revolutionary new training methods or architectures were involved. If all it was going to take to advance AI was a continuation or scaling-up of this paradigm—more input data yields increased capability—China could well have an advantage.

But one of the biggest hurdles AI needs to clear to advance in leaps and bounds rather than baby steps is precisely this reliance on extensive, task-specific data. Other significant challenges include the technology’s fast approach to the limits of current computing power and its immense energy consumption.

Thus, while China’s trove of data may give it an advantage now, it may not be much of a long-term foothold on the climb to AI dominance. It’s useful for building products that incorporate or rely on today’s AI, but not for pushing the needle on how artificially intelligent systems learn. WeChat data on users’ spending habits, for example, would be valuable in building an AI that helps people save money or suggests items they might want to purchase. It will enable (and already has enabled) highly tailored products that will earn their creators and the companies that use them a lot of money.

But data quantity isn’t what’s going to advance AI. As Frey and Osborne put it, “Data efficiency is the holy grail of further progress in artificial intelligence.”

To that end, research teams in academia and private industry are working on ways to make AI less data-hungry. New training methods like one-shot learning and less-than-one-shot learning have begun to emerge, along with myriad efforts to make AI that learns more like the human brain.

While not insignificant, these advancements still fall into the “baby steps” category. No one knows how AI is going to progress beyond these small steps—and that uncertainty, in Frey and Osborne’s opinion, is a major speed bump on China’s fast-track to AI dominance.

How Innovation Happens
A lot of great inventions have happened by accident, and some of the world’s most successful companies started in garages, dorm rooms, or similarly low-budget, nondescript circumstances (including Google, Facebook, Amazon, and Apple, to name a few). Innovation, the authors point out, often happens “through serendipity and recombination, as inventors and entrepreneurs interact and exchange ideas.”

Frey and Osborne argue that although China has great reserves of talent and a history of building on technologies conceived elsewhere, it doesn’t yet have a glowing track record in terms of innovation. They note that of the 100 most-cited patents from 2003 to present, none came from China. Giants Tencent, Alibaba, and Baidu are all wildly successful in the Chinese market, but they’re rooted in technologies or business models that came out of the US and were tweaked for the Chinese population.

“The most innovative societies have always been those that allowed people to pursue controversial ideas,” Frey and Osborne write. China’s heavy censorship of the internet and surveillance of citizens don’t quite encourage the pursuit of controversial ideas. The country’s social credit system rewards people who follow the rules and punishes those who step out of line. Frey adds that top-down execution of problem-solving is effective when the problem at hand is clearly defined—and the next big leaps in AI are not.

It’s debatable how strongly a culture of social conformism can impact technological innovation, and of course there can be exceptions. But a relevant historical example is the Soviet Union, which, despite heavy investment in science and technology that briefly rivaled the US in fields like nuclear energy and space exploration, ended up lagging far behind primarily due to political and cultural factors.

Similarly, China’s focus on computer science in its education system could give it an edge—but, as Frey told me in an email, “The best students are not necessarily the best researchers. Being a good researcher also requires coming up with new ideas.”

Winner Take All?
Beyond the question of whether China will achieve AI dominance is the issue of how it will use the powerful technology. Several of the ways China has already implemented AI could be considered morally questionable, from facial recognition systems used aggressively against ethnic minorities to smart glasses for policemen that can pull up information about whoever the wearer looks at.

This isn’t to say the US would use AI for purely ethical purposes. The military’s Project Maven, for example, used artificially intelligent algorithms to identify insurgent targets in Iraq and Syria, and American law enforcement agencies are also using (mostly unregulated) facial recognition systems.

It’s conceivable that “dominance” in AI won’t go to one country; each nation could meet milestones in different ways, or meet different milestones. Researchers from both countries, at least in the academic sphere, could (and likely will) continue to collaborate and share their work, as they’ve done on many projects to date.

If one country does take the lead, it will certainly see some major advantages as a result. Brookings Institute fellow Indermit Gill goes so far as to say that whoever leads in AI in 2030 will “rule the world” until 2100. But Gill points out that in addition to considering each country’s strengths, we should consider how willing they are to improve upon their weaknesses.

While China leads in investment and the US in innovation, both nations are grappling with huge economic inequalities that could negatively impact technological uptake. “Attitudes toward the social change that accompanies new technologies matter as much as the technologies, pointing to the need for complementary policies that shape the economy and society,” Gill writes.

Will China’s leadership be willing to relax its grip to foster innovation? Will the US business environment be enough to compete with China’s data, investment, and education advantages? And can both countries find a way to distribute technology’s economic benefits more equitably?

Time will tell, but it seems we’ve got our work cut out for us—and China does too.

Image Credit: Adam Birkett on Unsplash Continue reading

Posted in Human Robots

#437924 How a Software Map of the Entire Planet ...

i
“3D map data is the scaffolding of the 21st century.”

–Edward Miller, Founder, Scape Technologies, UK

Covered in cameras, sensors, and a distinctly spaceship looking laser system, Google’s autonomous vehicles were easy to spot when they first hit public roads in 2015. The key hardware ingredient is a spinning laser fixed to the roof, called lidar, which provides the car with a pair of eyes to see the world. Lidar works by sending out beams of light and measuring the time it takes to bounce off objects back to the source. By timing the light’s journey, these depth-sensing systems construct fully 3D maps of their surroundings.

3D maps like these are essentially software copies of the real world. They will be crucial to the development of a wide range of emerging technologies including autonomous driving, drone delivery, robotics, and a fast-approaching future filled with augmented reality.

Like other rapidly improving technologies, lidar is moving quickly through its development cycle. What was an expensive technology on the roof of a well-funded research project is now becoming cheaper, more capable, and readily available to consumers. At some point, lidar will come standard on most mobile devices and is now available to early-adopting owners of the iPhone 12 Pro.

Consumer lidar represents the inevitable shift from wealthy tech companies generating our world’s map data, to a more scalable crowd-sourced approach. To develop the repository for their Street View Maps product, Google reportedly spent $1-2 billion sending cars across continents photographing every street. Compare that to a live-mapping service like Waze, which uses crowd-sourced user data from its millions of users to generate accurate and real-time traffic conditions. Though these maps serve different functions, one is a static, expensive, unchanging map of the world while the other is dynamic, real-time, and constructed by users themselves.

Soon millions of people may be scanning everything from bedrooms to neighborhoods, resulting in 3D maps of significant quality. An online search for lidar room scans demonstrates just how richly textured these three-dimensional maps are compared to anything we’ve had before. With lidar and other depth-sensing systems, we now have the tools to create exact software copies of everywhere and everything on earth.

At some point, likely aided by crowdsourcing initiatives, these maps will become living breathing, real-time representations of the world. Some refer to this idea as a “digital twin” of the planet. In a feature cover story, Kevin Kelly, the cofounder of Wired magazine, calls this concept the “mirrorworld,” a one-to-one software map of everything.

So why is that such a big deal? Take augmented reality as an example.

Of all the emerging industries dependent on such a map, none are more invested in seeing this concept emerge than those within the AR landscape. Apple, for example, is not-so-secretly developing a pair of AR glasses, which they hope will deliver a mainstream turning point for the technology.

For Apple’s AR devices to work as anticipated, they will require virtual maps of the world, a concept AR insiders call the “AR cloud,” which is synonymous with the “mirrorworld” concept. These maps will be two things. First, they will be a tool that creators use to place AR content in very specific locations; like a world canvas to paint on. Second, they will help AR devices both locate and understand the world around them so they can render content in a believable way.

Imagine walking down a street wanting to check the trading hours of a local business. Instead of pulling out your phone to do a tedious search online, you conduct the equivalent of a visual google search simply by gazing at the store. Albeit a trivial example, the AR cloud represents an entirely non-trivial new way of managing how we organize the world’s information. Access to knowledge can be shifted away from the faraway monitors in our pocket, to its relevant real-world location.

Ultimately this describes a blurring of physical and digital infrastructure. Our public and private spaces will thus be comprised equally of both.

No example demonstrates this idea better than Pokémon Go. The game is straightforward enough; users capture virtual characters scattered around the real world. Today, the game relies on traditional GPS technology to place its characters, but GPS is accurate only to within a few meters of a location. For a car navigating on a highway or locating Pikachus in the world, that level of precision is sufficient. For drone deliveries, driverless cars, or placing a Pikachu in a specific location, say on a tree branch in a park, GPS isn’t accurate enough. As astonishing as it may seem, many experimental AR cloud concepts, even entirely mapped cities, are location specific down to the centimeter.

Niantic, the $4 billion publisher behind Pokémon Go, is aggressively working on developing a crowd-sourced approach to building better AR Cloud maps by encouraging their users to scan the world for them. Their recent acquisition of 6D.ai, a mapping software company developed by the University of Oxford’s Victor Prisacariu through his work at Oxford’s Active Vision Lab, indicates Niantic’s ambition to compete with the tech giants in this space.

With 6D.ai’s technology, Niantic is developing the in-house ability to generate their own 3D maps while gaining better semantic understanding of the world. By going beyond just knowing there’s a temporary collection of orange cones in a certain location, for example, the game may one day understand the meaning behind this; that a temporary construction zone means no Pokémon should spawn here to avoid drawing players to this location.

Niantic is not the only company working on this. Many of the big tech firms you would expect have entire teams focused on map data. Facebook, for example, recently acquired the UK-based Scape technologies, a computer vision startup mapping entire cities with centimeter precision.

As our digital maps of the world improve, expect a relentless and justified discussion of privacy concerns as well. How will society react to the idea of a real-time 3D map of their bedroom living on a Facebook or Amazon server? Those horrified by the use of facial recognition AI being used in public spaces are unlikely to find comfort in the idea of a machine-readable world subject to infinite monitoring.

The ability to build high-precision maps of the world could reshape the way we engage with our planet and promises to be one of the biggest technology developments of the next decade. While these maps may stay hidden as behind-the-scenes infrastructure powering much flashier technologies that capture the world’s attention, they will soon prop up large portions of our technological future.

Keep that in mind when a car with no driver is sharing your road.

Image credit: sergio souza / Pexels Continue reading

Posted in Human Robots

#437892 This Week’s Awesome Tech Stories From ...

ENVIRONMENT
Human-Made Stuff Now Outweighs All Life on Earth
Stephanie Pappas | Scientific American
“Humanity has reached a new milestone in its dominance of the planet: human-made objects may now outweigh all of the living beings on Earth. Roads, houses, shopping malls, fishing vessels, printer paper, coffee mugs, smartphones and all the other infrastructure of daily life now weigh in at approximately 1.1 trillion metric tons—equal to the combined dry weight of all plants, animals, fungi, bacteria, archaea and protists on the planet.”

SPACE
So, It Turns Out SpaceX Is Pretty Good at Rocketing
Eric Berger | Ars Technica
“As the Sun sank toward the South Texas horizon, a fantastical-looking spaceship rose into the reddening sky. It was, in a word, epic. …This was one heck of a test-flight that addressed a number of unknowns about Starship, which is the upper stage of SpaceX’s new launch system and may one day land humans on the Moon, Mars, and beyond.”

ARTIFICIAL INTELLIGENCE
Tiny Four-Bit Computers Are All You Need to Train AI
Karen Hao | MIT Technology Review
“The work…could increase the speed and cut the energy costs needed to train deep learning by more than sevenfold. It could also make training powerful AI models possible on smartphones and other small devices, which would improve privacy by helping to keep personal data on a local device. And it would make the process more accessible to researchers outside big, resource-rich tech companies.”

ENERGY
Did Quantum Scape Just Solve a 40-Year-Old Battery Problem?
Daniel Oberhaus | Wired
“[The properties of solid state batteries] would send…energy density through the roof, enable ultra-fast charging, and would eliminate the risk of battery fires. But for the past 40 years, no one has been able to make a solid-state battery that delivers on this promise—until earlier this year, when a secretive startup called QuantumScape claimed to have solved the problem. Now it has the data to prove it.”

ROBOTICS
Hyundai Buys Boston Dynamics for Nearly $1 Billion. Now What?
Evan Ackerman | IEEE Spectrum
“I hope that Boston Dynamics is unique enough that the kinds of rules that normally apply to robotics companies (or companies in general) can be set aside, at least somewhat, but I also worry that what made Boston Dynamics great was the explicit funding for the kinds of radical ideas that eventually resulted in robots like Atlas and Spot. Can Hyundai continue giving Boston Dynamics the support and freedom that they need to keep doing the kinds of things that have made them legendary? I certainly hope so.”

BIOTECH
CRISPR and Another Genetic Strategy Fix Cell Defects in Two Common Blood Disorders
Jocelyn Kaiser | Science
“It is a double milestone: new evidence that cures are possible for many people born with sickle cell disease and another serious blood disorder, beta-thalassemia, and a first for the genome editor CRISPR. Today, in The New England Journal of Medicine (NEJM) and tomorrow at the American Society of Hematology (ASH) meeting, teams report that two strategies for directly fixing malfunctioning blood cells have dramatically improved the health of a handful of people with these genetic diseases.”

ETHICS
The Dark Side of Big Tech’s Funding for AI Research
Tom Simonite | Wired
“Timnit Gebru’s exit from Google is a powerful reminder of how thoroughly companies dominate the field, with the biggest computers and the most resources. …[Meredith] Whittaker of AI Now says properly probing the societal effects of AI is fundamentally incompatible with corporate labs. ‘That kind of research that looks at the power and politics of AI is and must be inherently adversarial to the firms that are profiting from this technology.’i”

Image credit: Karsten Winegeart / Unsplash Continue reading

Posted in Human Robots

#437884 Hyundai Buys Boston Dynamics for Nearly ...

This morning just after 3 a.m. ET, Boston Dynamics sent out a media release confirming that Hyundai Motor Group has acquired a controlling interest in the company that values Boston Dynamics at US $1.1 billion:

Under the agreement, Hyundai Motor Group will hold an approximately 80 percent stake in Boston Dynamics and SoftBank, through one of its affiliates, will retain an approximately 20 percent stake in Boston Dynamics after the closing of the transaction.

The release is very long, but does have some interesting bits—we’ll go through them, and talk about what this might mean for both Boston Dynamics and Hyundai.

We’ve asked Boston Dynamics for comment, but they’ve been unusually quiet for the last few days (I wonder why!). So at this point just keep in mind that the only things we know for sure are the ones in the release. If (when?) we hear anything from either Boston Dynamics or Hyundai, we’ll update this post.

The first thing to be clear on is that the acquisition is split between Hyundai Motor Group’s affiliates, including Hyundai Motor, Hyundai Mobis, and Hyundai Glovis. Hyundai Motor makes cars, Hyundai Mobis makes car parts and seems to be doing some autonomous stuff as well, and Hyundai Glovis does logistics. There are many other groups that share the Hyundai name, but they’re separate entities, at least on paper. For example, there’s a Hyundai Robotics, but that’s part of Hyundai Heavy Industries, a different company than Hyundai Motor Group. But for this article, when we say “Hyundai,” we’re talking about Hyundai Motor Group.

What’s in it for Hyundai?
Let’s get into the press release, which is filled with press release-y terms like “synergies” and “working together”—you can view the whole thing here—but still has some parts that convey useful info.

By establishing a leading presence in the field of robotics, the acquisition will mark another major step for Hyundai Motor Group toward its strategic transformation into a Smart Mobility Solution Provider. To propel this transformation, Hyundai Motor Group has invested substantially in development of future technologies, including in fields such as autonomous driving technology, connectivity, eco-friendly vehicles, smart factories, advanced materials, artificial intelligence (AI), and robots.

If Hyundai wants to be a “Smart Mobility Solution Provider” with a focus on vehicles, it really seems like there’s a whole bunch of other ways they could have spent most of a billion dollars that would get them there quicker. Will Boston Dynamics’ expertise help them develop autonomous driving technology? Sure, I guess, but why not just buy an autonomous car startup instead? Boston Dynamics is more about “robots,” which happens to be dead last on the list above.

There was some speculation a couple of weeks ago that Hyundai was going to try and leverage Boston Dynamics to make a real version of this hybrid wheeled/legged concept car, so if that’s what Hyundai means by “Smart Mobility Solution Provider,” then I suppose the Boston Dynamics acquisition makes more sense. Still, I think that’s unlikely, because it’s just a concept car, after all.

In addition to “smart mobility,” which seems like a longer-term goal for Hyundai, the company also mentions other, more immediate benefits from the acquisition:

Advanced robotics offer opportunities for rapid growth with the potential to positively impact society in multiple ways. Boston Dynamics is the established leader in developing agile, mobile robots that have been successfully integrated into various business operations. The deal is also expected to allow Hyundai Motor Group and Boston Dynamics to leverage each other’s respective strengths in manufacturing, logistics, construction and automation.

“Successfully integrated” might be a little optimistic here. They’re talking about Spot, of course, but I think the best you could say at this point is that Spot is in the middle of some promising pilot projects. Whether it’ll be successfully integrated in the sense that it’ll have long-term commercial usefulness and value remains to be seen. I’m optimistic about this as well, but Spot is definitely not there yet.

What does probably hold a lot of value for Hyundai is getting Spot, Pick, and perhaps even Handle into that “manufacturing, logistics, construction” stuff. This is the bread and butter for robots right now, and Boston Dynamics has plenty of valuable technology to offer in those spaces.

Photo: Bob O’Connor

Boston Dynamics is selling Spot for $74,500, shipping included.

Betting on Spot and Pick
With Boston Dynamics founder Marc Raibert’s transition to Chairman of the company, the CEO position is now occupied by Robert Playter, the long-time VP of engineering and more recently COO at Boston Dynamics. Here’s his statement from the release:

“Boston Dynamics’ commercial business has grown rapidly as we’ve brought to market the first robot that can automate repetitive and dangerous tasks in workplaces designed for human-level mobility. We and Hyundai share a view of the transformational power of mobility and look forward to working together to accelerate our plans to enable the world with cutting edge automation, and to continue to solve the world’s hardest robotics challenges for our customers.”

Whether Spot is in fact “the first robot that can automate repetitive and dangerous tasks in workplaces designed for human-level mobility” on the market is perhaps something that could be argued against, although I won’t. Whether or not it was the first robot that can do these kinds of things, it’s definitely not the only robot that do these kinds of things, and going forward, it’s going to be increasingly challenging for Spot to maintain its uniqueness.

For a long time, Boston Dynamics totally owned the quadruped space. Now, they’re one company among many—ANYbotics and Unitree are just two examples of other quadrupeds that are being successfully commercialized. Spot is certainly very capable and easy to use, and we shouldn’t underestimate the effort required to create a robot as complex as Spot that can be commercially used and supported. But it’s not clear how long they’ll maintain that advantage, with much more affordable platforms coming out of Asia, and other companies offering some unique new capabilities.

Photo: Boston Dynamics

Boston Dynamics’ Handle is an all-electric robot featuring a leg-wheel hybrid mobility system, a manipulator arm with a vacuum gripper, and a counterbalancing tail.

Boston Dynamics’ picking system, which stemmed from their 2019 acquisition of Kinema Systems, faces the same kinds of challenges—it’s very good, but it’s not totally unique.

Boston Dynamics produces highly capable mobile robots with advanced mobility, dexterity and intelligence, enabling automation in difficult, dangerous, or unstructured environments. The company launched sales of its first commercial robot, Spot in June of 2020 and has since sold hundreds of robots in a variety of industries, such as power utilities, construction, manufacturing, oil and gas, and mining. Boston Dynamics plans to expand the Spot product line early next year with an enterprise version of the robot with greater levels of autonomy and remote inspection capabilities, and the release of a robotic arm, which will be a breakthrough in mobile manipulation.

Boston Dynamics is also entering the logistics automation market with the industry leading Pick, a computer vision-based depalletizing solution, and will introduce a mobile robot for warehouses in 2021.

Huh. We’ll be trying to figure out what “greater levels of autonomy” means, as well as whether the “mobile robot for warehouses” is Handle, or something more like an autonomous mobile robot (AMR) platform. I’d honestly be surprised if Handle was ready for work outside of Boston Dynamics next year, and it’s hard to imagine how Boston Dynamics could leverage their expertise into the AMR space with something that wouldn’t just seem… Dull, compared to what they usually do. I hope to be surprised, though!

A new deep-pocketed benefactor

Hyundai Motor Group’s decision to acquire Boston Dynamics is based on its growth potential and wide range of capabilities.

“Wide range of capabilities” we get, but that other phrase, “growth potential,” has a heck of a lot wrapped up in it. At the moment, Boston Dynamics is nowhere near profitable, as far as we know. SoftBank acquired Boston Dynamics in 2017 for between one hundred and two hundred million, and over the last three years they’ve poured hundreds of millions more into Boston Dynamics.

Hyundai’s 80 percent stake just means that they’ll need to take over the majority of that support, and perhaps even increase it if Boston Dynamics’ growth is one of their primary goals. Hyundai can’t have a reasonable expectation that Boston Dynamics will be profitable any time soon; they’re selling Spots now, but it’s an open question whether Spot will manage to find a scalable niche in which it’ll be useful in the sort of volume that will make it a sustainable commercial success. And even if it does become a success, it seems unlikely that Spot by itself will make a significant dent in Boston Dynamics’ burn rate anytime soon. Boston Dynamics will have more products of course, but it’s going to take a while, and Hyundai will need to support them in the interim.

Depending on whether Hyundai views Boston Dynamics as a company that does research or a company that makes robots that are useful and profitable, it may be difficult for Boston Dynamics to justify the cost to develop the
next Atlas, when the
current one still seems so far from commercialization

It’s become clear that to sustain itself, Boston Dynamics needs a benefactor with very deep pockets and a long time horizon. Initially, Boston Dynamics’ business model (or whatever you want to call it) was to do bespoke projects for defense-ish folks like DARPA, but from what we understand Boston Dynamics stopped that sort of work after Google acquired them back in 2013. From one perspective, that government funding did exactly what it was supposed to do, which was to fund the development of legged robots through low TRLs (technology readiness levels) to the point where they could start to explore commercialization.

The question now, though, is whether Hyundai is willing to let Boston Dynamics undertake the kinds of low-TRL, high-risk projects that led from BigDog to LS3 to Spot, and from PETMAN to DRC Atlas to the current Atlas. So will Hyundai be cool about the whole thing and be the sort of benefactor that’s willing to give Boston Dynamics the resources that they need to keep doing what they’re doing, without having to answer too many awkward questions about things like practicality and profitability? Hyundai can certainly afford to do this, but so could SoftBank, and Google—the question is whether Hyundai will want to, over the length of time that’s required for the development of the kind of ultra-sophisticated robotics hardware that Boston Dynamics specializes in.

To put it another way: Depending whether Hyundai’s perspective on Boston Dynamics is as a company that does research or a company that makes robots that are useful and profitable, it may be difficult for Boston Dynamics to justify the cost to develop the next Atlas, when the current one still seems so far from commercialization.

Google, SoftBank, now Hyundai

Boston Dynamics possesses multiple key technologies for high-performance robots equipped with perception, navigation, and intelligence.

Hyundai Motor Group’s AI and Human Robot Interaction (HRI) expertise is highly synergistic with Boston Dynamics’s 3D vision, manipulation, and bipedal/quadruped expertise.

As it turns out, Hyundai Motors does have its own robotics lab, called Hyundai Motors Robotics Lab. Their website is not all that great, but here’s a video from last year:

I’m not entirely clear on what Hyundai means when they use the word “synergistic” when they talk about their robotics lab and Boston Dynamics, but it’s a little bit concerning. Usually, when a big company buys a little company that specializes in something that the big company is interested in, the idea is that the little company, to some extent, will be absorbed into the big company to give them some expertise in that area. Historically, however, Boston Dynamics has been highly resistant to this, maintaining its post-acquisition independence and appearing to be very reluctant to do anything besides what it wants to do, at whatever pace it wants to do it, and as by itself as possible.

From what we understand, Boston Dynamics didn’t integrate particularly well with Google’s robotics push in 2013, and we haven’t seen much evidence that SoftBank’s experience was much different. The most direct benefit to SoftBank (or at least the most visible one) was the addition of a fleet of Spot robots to the SoftBank Hawks baseball team cheerleading squad, along with a single (that we know about) choreographed gymnastics routine from an Atlas robot that was only shown on video.

And honestly, if you were a big manufacturing company with a bunch of money and you wanted to build up your own robotics program quickly, you’d probably have much better luck picking up some smaller robotics companies who were a bit less individualistic and would probably be more amenable to integration and would cost way less than a billion dollars-ish. And if integration is ultimately Hyundai’s goal, we’ll be very sad, because it’ll likely signal the end of Boston Dynamics doing the unfettered crazy stuff that we’ve grown to love.

Photo: Bob O’Connor

Possibly the most agile humanoid robot ever built, Atlas can run, climb, jump over obstacles, and even get up after a fall.

Boston Dynamics contemplates its future

The release ends by saying that the transaction is “subject to regulatory approvals and other customary closing conditions” and “is expected to close by June of 2021.” Again, you can read the whole thing here.

My initial reaction is that, despite the “synergies” described by Hyundai, it’s certainly not immediately obvious why the company wants to own 80 percent of Boston Dynamics. I’d also like a better understanding of how they arrived at the $1.1 billion valuation. I’m not saying this because I don’t believe in what Boston Dynamics is doing or in the inherent value of the company, because I absolutely do, albeit perhaps in a slightly less tangible sense. But when you start tossing around numbers like these, a big pile of expectations inevitably comes along with them. I hope that Boston Dynamics is unique enough that the kinds of rules that normally apply to robotics companies (or companies in general) can be set aside, at least somewhat, but I also worry that what made Boston Dynamics great was the explicit funding for the kinds of radical ideas that eventually resulted in robots like Atlas and Spot.

Can Hyundai continue giving Boston Dynamics the support and freedom that they need to keep doing the kinds of things that have made them legendary? I certainly hope so. Continue reading

Posted in Human Robots