A marker of progress will be when Amazon converts to automated picking. They've been trying hard for almost a decade now. They had an annual competition for years. They have a decent picking robot developed in house.[1] It's not being deployed in quantity yet.
Nor does it have anything like a humanoid hand. Just a two-surface gripper.
Amazon's production robots are mostly automatic guided vehicles, not manipulators.
I'm impressed with how far legged locomotion has come. But as yet, nobody seems to be using legged robots for any commercial purpose beyond the demo level.
Is Tesla still going to produce vast numbers of humanoid robots by the end of 2026?
There's been a lot of progress on the hardware side. Motor technology from drones has produced much better robot motors. The sweet spot on gear reduction seems to have been found. (Too much reduction, and you can't back drive. Too little, and the motors have to be too big.) The volumes are now large enough to justify making robot-specific components. Robot arms are much better than a decade ago. So are robot legs. Control is better, too. It looks like a humanoid robot will cost about as much as a car.
But they're still not quite good enough to be useful.
We'll know they are real when an Amazon Prime truck drives up and a robot does the last 100 meters of the delivery.
That would only be a minor marker. A major marker would be whatever the Chinese equivalent(s) of Amazon are (Alibaba? etc.) going that route successfully. From academic / industrial conference presentations it appears Chinese services are banking on automation far more than an entity like Amazon does.
That being said, I don't know what exact state the industrial automation technology is there and I can only extrapolate (or do websearch, which didn't lead to enough details; I only found things like https://www.youtube.com/watch?v=JnUGgc8R3ng).
When something like https://www.allegrohand.com is mass produced and used industrially, I bet the last mile (meter?) would change a bit, and full automation would be easier and less finicky.
Not sure about that. Labor costs are lower in China and the CCP is strongly incentivized to keep enough jobs around for humans to maintain their own hold on power.
Labor costs are lower, but rising, and already high enough that automation can be appealing.
The Chinese government is also pretty good at finding things for people to do, so I doubt that's a factor. Go to any big park in a city and see how many people are sweeping up leaves, or guarding a building/area that isn't particularly secure.
Yes, picking is one, and package delivery is another. I wonder how many people currently get package deliveries by robot? It might be a good metric to track?
Roboticist here. All of this, and he didn’t mention compliance or online adaptation to otherwise un-sensable dynamics. Or massively complex miniature mechanisms.
Current generation tactile sensors cost a couple thousand $ PER FINGER, and have a real world MTBF of hours. The cost can be solved with economy of scale. The fragility is harder.
> Current generation tactile sensors cost a couple thousand $ PER FINGER, and have a real world MTBF of hours. The cost can be solved with economy of scale. The fragility is harder.
Are we talking about experimental laboratory ones here? What happens when the Alibaba players start getting into the game? They have plenty of humanoid robots.
Capacitive touchscreens are not tactile in any way whatsoever. They are purely electrical, and there are plenty of things (actually, most things, I'd say) which are not sufficiently capacitive to be detected by such approaches. You usually need to measure physical deformation instead, which is much more difficult to do precisely. (There are capacitive approaches to that, but they don't work like a touchscreen)
Yes the problem is very hard. Mainly because high DOF generalization is very difficult.
We have self driving cars because what are the control inputs? Pedal, brake, steering wheel. This already took many many years.
Now for a humanoid robot: An action space that is metaphorically Hilbert. (Physically, yes, obviously)
Also, IMO, LLM's can aid the development of robots, but do little beyond a planning, human control interface. Below that it's the domain of control and the solution will be the correct combination of classical, neural, and real time optimization based control.
All the bad-ass biped robots that actually look natural? It's PID controls wrapped with control barrier functions constraining the QPs that are being solved in real time.
But that's annoying to derive per-application. So we'll need neural methods which can be learned (while being constrained by a priori knowledge of dynamics). My hunch is that the Yann LeCunn type of jepa models will be how tasks can be learned.
> All the bad-ass biped robots that actually look natural? It's PID controls wrapped with control barrier functions constraining the QPs that are being solved in real time.
That's not entirely true. Locomotion is well addressed by RL in sim. It's true that there is still a PD layer, and the RL policy produces setpoints for it.
> So we'll need neural methods which can be learned
Data is a problem. LLMs had the advantage of the whole internet to train on. Robots don’t have that corpus of information. And real time learning seems to be something that everyone in AI is studiously ignoring.
The hope is that RL in simulation can fill the gap.
Also there’s imitating humans, via a suitable mapping from the human sensor, control and configuration space to the robot’s. Some groups have gathered video and other data from humans doing tasks, for example with a VR headset.
I don’t think the complexity scales with every additional degree of freedom like you are painting here. I think it’s just a matter of getting the right training data in sufficient quantities for an LLM to output across all degrees of freedom simultaneously without it being some exponential leap.
I mean, functional robotics isn't that hard, robotic vacuums have been in homes for a decade now, and industrial robotic arms. However, humanoid robots IS hard mainly because of the form factor constraints. You can't really get a lot of power out of servo motors and other actuator if it all has to be self-contained in a humanoid form instead of using hydraulics or pneumonic or even big stepper motors as for stationary industrial robots.
The videos I've seen of humanoid robot applications are basically that it can do dishes and fold laundry, but I think if household chore robots ever come to market, they would probably not look humanoid at all and probably look like semi dishwashers/washing machines with wheels and a gripper arm.
people very soon as going to look back at all of us and just think "they didn't even have robots yet! how did they even eat?" Well, future readers, it isn't easy! We either go to the store and bring back groceries ourselves or pay a helper to do it. No robot in the loop there. Then when it comes time to cook something we either have to cut it up and otherwise prepare it and then cook it ourselves, or another human can do it, or we can buy fully prepared foods that don't require cooking. And then when we're done we have to put our own dishes away into a dishwasher. We can't just say a few words and have a robot do it for us!
The physical world is basically an infinite amount of global state that must be perceived indirectly through imperfect sensors and acted on using imperfect motors and manipulators.
I can say many things, but most people here will not believe me. I'd say just watch China do the 'impossible'. Then some self reflection should be in order.
A marker of progress will be when Amazon converts to automated picking. They've been trying hard for almost a decade now. They had an annual competition for years. They have a decent picking robot developed in house.[1] It's not being deployed in quantity yet. Nor does it have anything like a humanoid hand. Just a two-surface gripper. Amazon's production robots are mostly automatic guided vehicles, not manipulators.
I'm impressed with how far legged locomotion has come. But as yet, nobody seems to be using legged robots for any commercial purpose beyond the demo level.
Is Tesla still going to produce vast numbers of humanoid robots by the end of 2026?
There's been a lot of progress on the hardware side. Motor technology from drones has produced much better robot motors. The sweet spot on gear reduction seems to have been found. (Too much reduction, and you can't back drive. Too little, and the motors have to be too big.) The volumes are now large enough to justify making robot-specific components. Robot arms are much better than a decade ago. So are robot legs. Control is better, too. It looks like a humanoid robot will cost about as much as a car.
But they're still not quite good enough to be useful.
We'll know they are real when an Amazon Prime truck drives up and a robot does the last 100 meters of the delivery.
[1] https://www.youtube.com/watch?v=WStK9HNn8c8&
That would only be a minor marker. A major marker would be whatever the Chinese equivalent(s) of Amazon are (Alibaba? etc.) going that route successfully. From academic / industrial conference presentations it appears Chinese services are banking on automation far more than an entity like Amazon does.
That being said, I don't know what exact state the industrial automation technology is there and I can only extrapolate (or do websearch, which didn't lead to enough details; I only found things like https://www.youtube.com/watch?v=JnUGgc8R3ng).
When something like https://www.allegrohand.com is mass produced and used industrially, I bet the last mile (meter?) would change a bit, and full automation would be easier and less finicky.
Not sure about that. Labor costs are lower in China and the CCP is strongly incentivized to keep enough jobs around for humans to maintain their own hold on power.
Labor costs are lower, but rising, and already high enough that automation can be appealing.
The Chinese government is also pretty good at finding things for people to do, so I doubt that's a factor. Go to any big park in a city and see how many people are sweeping up leaves, or guarding a building/area that isn't particularly secure.
Yes, picking is one, and package delivery is another. I wonder how many people currently get package deliveries by robot? It might be a good metric to track?
Roboticist here. All of this, and he didn’t mention compliance or online adaptation to otherwise un-sensable dynamics. Or massively complex miniature mechanisms.
Current generation tactile sensors cost a couple thousand $ PER FINGER, and have a real world MTBF of hours. The cost can be solved with economy of scale. The fragility is harder.
yep. and with the western funding model, how many hardware iterations can you do before you run out of runway?
> Current generation tactile sensors cost a couple thousand $ PER FINGER, and have a real world MTBF of hours. The cost can be solved with economy of scale. The fragility is harder.
Are we talking about experimental laboratory ones here? What happens when the Alibaba players start getting into the game? They have plenty of humanoid robots.
i think you can get some good surface for a few hundred $$ / few fingers here
https://xelarobotics.com/
How much more sensitive do you need to be compared to say a standard mobile capacitive screen and those are essentially dirt cheap at this point.
Capacitive touchscreens are not tactile in any way whatsoever. They are purely electrical, and there are plenty of things (actually, most things, I'd say) which are not sufficiently capacitive to be detected by such approaches. You usually need to measure physical deformation instead, which is much more difficult to do precisely. (There are capacitive approaches to that, but they don't work like a touchscreen)
I'm picturing humanoid robots having to operate in pairs so they can constantly fix each other.
i like this
Yes the problem is very hard. Mainly because high DOF generalization is very difficult.
We have self driving cars because what are the control inputs? Pedal, brake, steering wheel. This already took many many years.
Now for a humanoid robot: An action space that is metaphorically Hilbert. (Physically, yes, obviously)
Also, IMO, LLM's can aid the development of robots, but do little beyond a planning, human control interface. Below that it's the domain of control and the solution will be the correct combination of classical, neural, and real time optimization based control.
All the bad-ass biped robots that actually look natural? It's PID controls wrapped with control barrier functions constraining the QPs that are being solved in real time.
But that's annoying to derive per-application. So we'll need neural methods which can be learned (while being constrained by a priori knowledge of dynamics). My hunch is that the Yann LeCunn type of jepa models will be how tasks can be learned.
> All the bad-ass biped robots that actually look natural? It's PID controls wrapped with control barrier functions constraining the QPs that are being solved in real time.
That's not entirely true. Locomotion is well addressed by RL in sim. It's true that there is still a PD layer, and the RL policy produces setpoints for it.
> So we'll need neural methods which can be learned
Data is a problem. LLMs had the advantage of the whole internet to train on. Robots don’t have that corpus of information. And real time learning seems to be something that everyone in AI is studiously ignoring.
The hope is that RL in simulation can fill the gap.
Also there’s imitating humans, via a suitable mapping from the human sensor, control and configuration space to the robot’s. Some groups have gathered video and other data from humans doing tasks, for example with a VR headset.
I don’t think the complexity scales with every additional degree of freedom like you are painting here. I think it’s just a matter of getting the right training data in sufficient quantities for an LLM to output across all degrees of freedom simultaneously without it being some exponential leap.
I mean, functional robotics isn't that hard, robotic vacuums have been in homes for a decade now, and industrial robotic arms. However, humanoid robots IS hard mainly because of the form factor constraints. You can't really get a lot of power out of servo motors and other actuator if it all has to be self-contained in a humanoid form instead of using hydraulics or pneumonic or even big stepper motors as for stationary industrial robots.
The videos I've seen of humanoid robot applications are basically that it can do dishes and fold laundry, but I think if household chore robots ever come to market, they would probably not look humanoid at all and probably look like semi dishwashers/washing machines with wheels and a gripper arm.
Couple of related reads/watches to this I found useful recently, with a similar conclusion:
https://www.youtube.com/watch?v=FUUzmRH5Yi4
https://www.construction-physics.com/p/robot-dexterity-still...
people very soon as going to look back at all of us and just think "they didn't even have robots yet! how did they even eat?" Well, future readers, it isn't easy! We either go to the store and bring back groceries ourselves or pay a helper to do it. No robot in the loop there. Then when it comes time to cook something we either have to cut it up and otherwise prepare it and then cook it ourselves, or another human can do it, or we can buy fully prepared foods that don't require cooking. And then when we're done we have to put our own dishes away into a dishwasher. We can't just say a few words and have a robot do it for us!
Eat? You must be living under a rock. We've been evaporating our sustenance and storing it in the cloud for years.
Perhaps nanobots will be able to carry the chemical makeup of a cheeseburger and rebuild a bite directly in our mouths, no cooking necessary!
Remember though, there is no food cloud really, just other people's fridges.
> We either go to the store and bring back groceries ourselves or pay a helper to do it.
Or order it from Amazon, in which case there was likely a robot in the pipeline.
Robots are very widely deployed, but almost entirely invisibly to the customer yet.
Roomba is the main exception.
As if people of the future will be able to read. Maybe some future AI anthropologists will read it though.
hairstylists are safe. and manicurists. and outcall masseurs.
really anything that involves a bade near your body or where body contact is the point.
They've already got a kind of masseur. You put on a spandex outfit to reduce friction and lay under 2 arms apparently.
> https://www.aescape.com/
that's neither sexy nor sensual. pass.
The physical world is basically an infinite amount of global state that must be perceived indirectly through imperfect sensors and acted on using imperfect motors and manipulators.
I can say many things, but most people here will not believe me. I'd say just watch China do the 'impossible'. Then some self reflection should be in order.