Boston Dynamics’s new Atlas robotic is kicking soccer balls like a World Cup athlete. But it surely’s additionally a lot less complicated — and cheaper — to make than earlier than.
Hyundai Motor Firm
Boston Dynamics’ new Atlas humanoid robotic has been wowing the world for months now, even earlier than the corporate unveiled it performing unprecedented soccer acrobatics in celebration of the present World Cup. The corporate unveiled the fifth generation of Atlas at CES early this 12 months, and it’d simply be the strongest and most succesful humanoid on the planet. Atlas has all the time been innovative, however the draw back has been price: traditionally upwards of $200,000. Perhaps not anymore. In an unique interview with Forbes, Director of Robotic Conduct for Atlas Alberto Rodriguez advised me that the brand new Atlas is way less complicated.
It’s, actually, “virtually an order of magnitude discount in complexity in comparison with the earlier era,” Rodriguez advised me. “It has method, method much less components, and method much less distinctive components. And the method of producing it’s a lot sooner and less complicated, which results in increased reliability and decrease price.”
That may be a large assertion, and he is aware of it. Rodriguez was cautious to say “virtually” an order of magnitude, not a full 10x less complicated.
However even a fraction of that could be a key sign of a maturing product: elevated functionality with decreased complexity. And the ensuing decrease price ought to make Atlas much more fascinating for potential prospects. Hyundai, which lately purchased the remaining 20% of Boston Dynamics that it didn’t already personal, is planning to maintain most or all of this 12 months’s manufacturing run for its personal makes use of. However quickly the corporate plans to build at least 30,000 Atlas humanoids a year, and others will be capable of buy it.
Why simplicity is the entire recreation
Proper now, apart from a couple of robotic makers who’re already scaling like Agibot and Unitree, humanoid robots are costly, hand-built, and finicky. Each distinctive half is a provide chain to handle, a failure level to engineer round, a line merchandise that retains the worth excessive.
The businesses that win the humanoid race might want to have a fantastic product, for positive. However they’ll additionally must be able to constructing tens of 1000’s of dependable items at a worth that makes prospects attain for his or her checkbooks.
Boston Dynamics seems to be optimizing for precisely that.
By stripping out components and, crucially, lowering the variety of distinctive components, the corporate shortens manufacturing time, raises reliability, and drives down price, suddenly. Fewer distinctive parts means less complicated meeting, fewer issues to interrupt, and a cleaner path to quantity manufacturing.
“We’re blissful that we have been capable of display the identical degree of efficiency, or increased, with a robotic that’s basically method, method less complicated,” Rodriguez mentioned. “Which we predict places us in a very good place for the subsequent step of mass manufacturing.”
That final phrase — mass manufacturing — is the place this will get fascinating. A humanoid that matches or beats the earlier era’s functionality whereas being far cheaper and extra dependable to supply is not only a higher robotic. It is a greater enterprise.
That’s one of many advantages of getting Hyundai as a company mother or father: this firm is aware of easy methods to manufacture. Hyundai Motor Group, which additionally owns Kia and Genesis, sells round seven million autos a 12 months mixed, making it one of many world’s three largest automakers. When you’re making thousands and thousands of something, likelihood is you’ve gotten fairly good at it.
That’s a truth that ought to put a touch of worry into each humanoid robotic competitor.
Functionality is {hardware} plus software program, and software program is now the bottleneck
However functionality isn’t nearly {hardware}.
“It’s actually the mix of {hardware} and software program,” Rodriguez advised me. When engineers design a brand new robotic, they construct in potential, however that potential stays theoretical till the management software program grows extra able to unlocking it. I’ve heard this from different humanoid robotic makers like 1X in California and Humanoid.ai within the UK as effectively.
“The issues we are able to present with present {hardware} are nonetheless restricted by our skill to know easy methods to management it,” he mentioned. “Atlas — however I am positive it is the identical for a lot of different robots — is able to rather more than we have been capable of squeeze efficiency out of it right this moment.”
In different phrases, the AI and management algorithms stay the primary bottleneck on getting worth out of robotic {hardware}. And humanoid robots aren’t any totally different than different fashionable merchandise like software-heavy automobiles and client electronics: they’ll ship with a default set of capabilities, however over-the-air software program updates will unlock extra.
Rodriguez frames the Boston Dynamics AI stack as two techniques working collectively.
The primary is bodily intelligence, the core management loop that handles steadiness, agility, and bodily ability: leaping, grabbing, shifting objects with velocity and generality. The second is reasoning intelligence, the layer that appears at a job, breaks it into steps and figures out easy methods to do it, together with issues like making a judgement name on whether or not an object shall be heavy or mild.
Bodily intelligence is Boston Dynamics’ dwelling turf.
For years the corporate has pushed the frontier of what legged robots can do, taking inspiration from dancing, parkour, and gymnastics. “That is clearly a aggressive power we’ve,” Rodriguez mentioned.
However over the past couple of years, the workforce has invested closely within the reasoning facet as a result of that’s what unlocks generality. If a robotic is deployed on a manufacturing facility line and the workflow adjustments two weeks later, you don’t need to spend one other few months reprogramming and revalidating it. “You need the robotic to study via expertise or via demonstration, in a method that’s extra pure,” Rodriguez mentioned. Right here’s the human corollary: you get employed on the manufacturing facility and a coworker or boss reveals you what to do. You study it, and as issues change, you adapt on the fly slightly than ranging from scratch.
That’s sort of a holy grail for humanoid robots proper now.
Talking ‘manufacturing facility language’
However there’s a a lot much less glamorous layer that’s simply as necessary: getting robots to speak to the techniques that run a manufacturing facility. Integration is without doubt one of the greatest hidden prices of deploying new expertise, and a humanoid that may’t talk with a warehouse administration system depends on being advised what to do in particular person, over and over.
Right here, Boston Dynamics leans on expertise most of its humanoid rivals don’t have. Stretch, its wheeled-base warehouse robotic, already ships with a fleet administration system deployed throughout tons of of consumers. That administration system assigns inspection routes and coordinates which robotic does what, slightly than requiring every unit to be programmed individually.
“That is one thing we have been doing for some time now,” Rodriguez mentioned.
Bringing that orchestration muscle to Atlas is a significant head begin.
The legs-versus-wheels query
I requested Rodriguez the place he lands on the trade’s favourite debate: legs or wheels. Most robotic patrons I speak to are greater than effective with legs, which saves battery, permits for excellent stability and – crucially – can match into present security rules.
However Rodriguez shared some new insights that undercut the frequent assumption within the manufacturing facility/warehouse/logistics areas that legs are an costly indulgence.
First, the complexity math is nearer than I’d have guessed. A wheeled omnidirectional base usually makes use of 4 wheels with two actuators every — one to drive, one to steer — for eight actuators complete. That’s roughly what you want for 2 legs, Rodriguez says.
“The mechanical complexity that goes into constructing legs right this moment isn’t that totally different,” he mentioned.
Second, legs go extra locations, and never simply up stairs. Factories look flat till you want to cross the hole between a loading dock and a trailer, or climb to a mezzanine. Third, legs allow a slimmer kind issue. A cell base must be vast in each path to remain steady when an arm extends, however a legged robotic can orient its stance to remain skinny the place area is tight.
In warehouses, the place each sq. foot is at a premium, that issues.
As for steadiness and locomotion, the issue that stumped roboticists for many years?
“It is truly not that tough anymore,” Rodriguez mentioned. “We have discovered the fitting recipes for easy methods to do it reliably.”
(After all, loads of rather more lately based humanoid startups are nonetheless engaged on precisely that.)
From parkour to the pitch: Atlas and the World Cup
As a part of its “Subsequent Begins Now” marketing campaign for the FIFA World Cup 2026, Hyundai Motor created Faculty of Soccer, a five-part social movie sequence following Atlas because it learns to play the sport.
The sequence builds to Atlas pulling off a “Ghost Rabona,” a sophisticated cross-leg kick that calls for exact timing, steadiness, and managed movement effectively past easy motion replication.
The kicker, so to talk: each motion was carried out by Atlas itself, with no CGI. It’s a advertising and marketing marketing campaign, positive, nevertheless it’s additionally a real demonstration of the agility Rodriguez says is the corporate’s core power: the bodily intelligence that can do way more prosaic work on dusty manufacturing facility flooring.
The underside line
Boston Dynamics’ pitch is coming into focus.
Match or beat the earlier Atlas on functionality, construct it with a fraction of the complexity, at increased reliability and decrease price. Layer on reasoning AI so it may be retasked with out months of reprogramming and hook into orchestration software program borrowed from a fleet already working at tons of of consumers.
Do all of it on legs, as a result of the complexity penalty is smaller than the trade assumes and the payoff — attain, and a slim footprint, and only a a lot cooler robotic — is actual.
The demos are all the time cool. (After all!)
However the order-of-magnitude simplification is the large story. That’s what makes the distinction between a pastime and a scalable, manufacturable, worthwhile product.
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