AI was clearly heavily used in the making of this article, and I almost dismissed it as slop. But after reading it I think there's enough correct information here for it to be useful as a general overview of the problems in the space.
I spent some time on legged locomotion back in the 1990s. It was clear then that you wanted torque control, and I did some work on the theory for that, trying to solve it from first principles, not machine learning. Got some nice theory and a patent out. But the parts just weren't there to build such things. As the article points out, the key to this is motor back-drivability. The final drive has to survive shock loads, and it has to dump forces into the motor, where the magnetic fields can take it. As I've quoted before, "you cannot strip the teeth of a magnetic field", a comment from early General Electric locomotive sales. (Locomotives are Diesel-electric, not Diesel with a clutch and shifting gearbox, because the clutch required is huge. Yes, it's been tried.)
That's something few areas of engineering cared about, with the exception of aircraft flight control systems with mechanical backup.
Pneumatic actuators looked promising, but proportional dynamic valves were big, heavy, and about $1000 each. Linear motors (not ball screws) looked like the coming thing back then, as 10:1 power/weight ratio had been achieved.
But that technology never got much further, and Aura, the biggest player, collapsed in a financial scandal. Series elastic actuators were (and still are) a race between the spring compressing and the ball screw motor starting up. Hydraulics were too clunky; Boston Dynamics built a 400 pound mule, but the Diesel power pack never worked.
Direct drive pancake motors were used by some SCARA industrial robots, but those were too big for leg joints.
I thought someone would crack the direct drive problem eventually, but nobody ever did. We're still stuck with some gear reduction.
Some of the exotic ideas for muscles mentioned in this article go back that far. The McKinney muscle is old, and not too useful. There was some interest in electrorheological fluids, fluids whose mechanical properties change when an electric field is applied. That didn't become useful either. Shape-memory alloys were a dead end; liquid cooling can overcome the slowness problem, but not the inefficiency problem. Everybody went back to good old electric motors, although they became 3-phase AC instead of DC. It helped that the drone industry made 3-phase motors and their controllers small, cheap, and powerful.
Academic robotics groups were tiny. MIT and Stanford had less than a dozen people each.
Progress required hundreds of millions of dollars for all that custom engineering and R&D. The level of effort just wasn't there. Nor would throwing money at the problem prior to machine learning have led to useful products.
It's impressive what's been accomplished in the last five years. It took a lot of money.
This is AI slop and the article contains some of the worst illustrations I have ever seen. Most do not make any sense mechanically. Here are the worst ones:
- The "orbiting threaded rollers" in figure 6 are not meshing with anything (not that they could, since they are orientated in the wrong direction).
- The ball of the ball screw in figure 7 deforms the screw and the roller screw "meshes" with a flat surface.
- The guy on the pogo stick in figure 14 is jumping himself rather than putting his feet on the stands of the pogo stick.
- In figure 16, a key penetrates the elastomer skin of the optical tactile sensor, destroying it.
Nobody has a problem with companies using AI to edit articles, create images.
But when even the writer is an AI persona, the trust factor gets destroyed.
Asking: As gpugreg remarked[0], this is AI slop to the point that it is impossible to trust anything from this article/blog post. As such, I flagged the submission.
- I wonder, is it possible to give a reason to the flag?
- Is flagging the submission without comments the right way to go?
For me, it is important that slowly but surely it goes through that AI slop is not what is accepted here on HN. Yes to have whatever LLM helping with grammar, spelling, etc. but the content should not be the output of a one shot "write me a blog post about humanoid robot actuators" prompt.
Probably a dumb question, because I know nothing about robotics, but:
> The "Zero RPM" Problem
> When a robot bends its knees to stand, the motor must constantly fight gravity. There is no skeletal structure to lock against. To an electric motor, holding a static load—known as stall torque—is the most punishing state possible.
Why not just add some kind of brake that can fully or partially lock the joint?
TLDR: we don't have the actuators required to make humanoid locomotion work reliably.
Also: something every human actually kind of knows. You need to take impacts on muscles, not on mechanical connections. Even if we had the actuators required, you also need perfect control. The only way actuators can work this well is if they properly predict the impacts so that the power of the motor ("the magnetic field") can absorb nearly all the impact. If you try to take the impacts even on human bones (that are very solid and self-repairing) they will break surprisingly quickly.
My opinion is that the need for high reduction is only because we can't have high voltage on the motors. If we either had very small distances between the magnets and electrical wires (think micrometers), or we have voltages in the 100s to 1000s of volts, we don't have to make this poisoned choice. (in a way, VERY small distances between magnets and wires is how human and animal muscles do it. But they go all the way down to sub-10 nanometers)
Its completely impossible to trust an article when half the diagrams have serious issues and headlines are worst slop indicators. I am sure the author is knowledgeable and spend some time on this. But please please, with butter, please, either spend the last 10% to get rid of these issues or just don't publish it! Keep it in your ai research gallery or if you want to publish that gallery as ai research?
I really like the idea of using two series elastic actuators in parallel on the same joint. This way motors acting in opposite direction can pre-tension the springs making the leg stiffer or softer. And if a lot of strength is needed they can act in the same direction summing their forces.
It should be fairly straightforward to control dynamically so you can use pretty much any motor and gearbox.
That's an idea that predates series elastic actuators. It's been used in tendon robots, where there are two winding drums pulling on two cables, with a spring between the end of each cable and the load. The cables oppose each other. Tighten up both, and the joint becomes stiff. Loosen up both, and the joint becomes flexible. Like muscles.
CWRU robotics liked this idea. Lightweight robot arms and painting robots have used it. Snake robots often work that way. Robot hands are often tendon driven.
Tendon robots are not popular for industrial use. The tendon cables wear out. Robots which do the same thing over and over wear their tendons at the same points. Not good in factory settings.
A useful model of a muscle is a spring and damper in parallel, like an auto suspension. The spring's neutral point, the spring's spring constant, and the damper's damping constant are all controllable. An actuator built that way can provide both force and position control, and can absorb shock loads. This is roughly how biological muscles behave.
The most practical actuator like that is a double-ended air cylinder. Each end has two proportional valves, to let air in from the air supply and to let air out to exhaust.
Such devices can be tuned from stiff to rigid, held at any position, and can absorb shock loads, which just compress the air trapped in the cylinder. Festo, the German automation equipment manufacturer, is a leading promoter of that approach.[1] They've popularized precision pneumatic control with a computer managing the valves. Works great in factories where you can plug into a compressed air line. Festo has lots of videos online, if you like looking at pneumatic actuators.
A series elastic actuator is a different concept. It's a stiff spring on the end of a stiff screw-type linear actuator. Shock loads compress the spring, a sensor at the spring detects this, and the linear actuator is commanded to quickly spin up the motor and unload the spring. Force can be measured from the length of the spring. It's a way to fake a real force actuator with a cheap positional one.
This was a popular idea in research robotics, because it's something that can be put together from off the shelf components. It's a useful research tool. But it's not a very good actuator for large loads. There's a race between the applied load squeezing the spring and the motor spinning up to take off the load before the spring bottoms out. It's only useful for a limited load range. If the spring is too stiff, you still take a high shock load at the gear train. If the spring is too soft, the spring bottoms out before the motor can catch up. You can buy series elastic actuators from academic and hobbyist suppliers [2], but they're rarely seen in factories.
There's been much robot actuator progress in the last decade. Not miracles, just money and good specialized mechanical engineering.
Why these screws are used instead of just threads? Because rolling friction is lower than sliding friction. You can use less or more of them trading friction for shock resistance.
Through the first 10 figures I looked at, there was literally A SINGLE ONE that didn't have obvious functional errors. This was not written by someone who read or understood the material. This is slop
23 comments
[ 3.1 ms ] story [ 36.5 ms ] threadOpentorque actuator
https://www.gabrael.io/new-page
https://github.com/G-Levine/OpenTorque-Actuator
I spent some time on legged locomotion back in the 1990s. It was clear then that you wanted torque control, and I did some work on the theory for that, trying to solve it from first principles, not machine learning. Got some nice theory and a patent out. But the parts just weren't there to build such things. As the article points out, the key to this is motor back-drivability. The final drive has to survive shock loads, and it has to dump forces into the motor, where the magnetic fields can take it. As I've quoted before, "you cannot strip the teeth of a magnetic field", a comment from early General Electric locomotive sales. (Locomotives are Diesel-electric, not Diesel with a clutch and shifting gearbox, because the clutch required is huge. Yes, it's been tried.) That's something few areas of engineering cared about, with the exception of aircraft flight control systems with mechanical backup.
Pneumatic actuators looked promising, but proportional dynamic valves were big, heavy, and about $1000 each. Linear motors (not ball screws) looked like the coming thing back then, as 10:1 power/weight ratio had been achieved. But that technology never got much further, and Aura, the biggest player, collapsed in a financial scandal. Series elastic actuators were (and still are) a race between the spring compressing and the ball screw motor starting up. Hydraulics were too clunky; Boston Dynamics built a 400 pound mule, but the Diesel power pack never worked. Direct drive pancake motors were used by some SCARA industrial robots, but those were too big for leg joints. I thought someone would crack the direct drive problem eventually, but nobody ever did. We're still stuck with some gear reduction.
Some of the exotic ideas for muscles mentioned in this article go back that far. The McKinney muscle is old, and not too useful. There was some interest in electrorheological fluids, fluids whose mechanical properties change when an electric field is applied. That didn't become useful either. Shape-memory alloys were a dead end; liquid cooling can overcome the slowness problem, but not the inefficiency problem. Everybody went back to good old electric motors, although they became 3-phase AC instead of DC. It helped that the drone industry made 3-phase motors and their controllers small, cheap, and powerful.
Academic robotics groups were tiny. MIT and Stanford had less than a dozen people each. Progress required hundreds of millions of dollars for all that custom engineering and R&D. The level of effort just wasn't there. Nor would throwing money at the problem prior to machine learning have led to useful products.
It's impressive what's been accomplished in the last five years. It took a lot of money.
Put the robot on rollerskates break the wheels for the occasional stair.
- The "orbiting threaded rollers" in figure 6 are not meshing with anything (not that they could, since they are orientated in the wrong direction).
- The ball of the ball screw in figure 7 deforms the screw and the roller screw "meshes" with a flat surface.
- The guy on the pogo stick in figure 14 is jumping himself rather than putting his feet on the stands of the pogo stick.
- In figure 16, a key penetrates the elastomer skin of the optical tactile sensor, destroying it.
- The gears in figure 20 touch perpendicularly.
From what I can understand this is the Robbie Dickson in question: https://www.huffpost.com/entry/lessons-from-a-serial-ent_b_9...
Nobody has a problem with companies using AI to edit articles, create images. But when even the writer is an AI persona, the trust factor gets destroyed.
- I wonder, is it possible to give a reason to the flag?
- Is flagging the submission without comments the right way to go?
For me, it is important that slowly but surely it goes through that AI slop is not what is accepted here on HN. Yes to have whatever LLM helping with grammar, spelling, etc. but the content should not be the output of a one shot "write me a blog post about humanoid robot actuators" prompt.
[0]: https://news.ycombinator.com/item?id=48005917
> The "Zero RPM" Problem
> When a robot bends its knees to stand, the motor must constantly fight gravity. There is no skeletal structure to lock against. To an electric motor, holding a static load—known as stall torque—is the most punishing state possible.
Why not just add some kind of brake that can fully or partially lock the joint?
Also: something every human actually kind of knows. You need to take impacts on muscles, not on mechanical connections. Even if we had the actuators required, you also need perfect control. The only way actuators can work this well is if they properly predict the impacts so that the power of the motor ("the magnetic field") can absorb nearly all the impact. If you try to take the impacts even on human bones (that are very solid and self-repairing) they will break surprisingly quickly.
My opinion is that the need for high reduction is only because we can't have high voltage on the motors. If we either had very small distances between the magnets and electrical wires (think micrometers), or we have voltages in the 100s to 1000s of volts, we don't have to make this poisoned choice. (in a way, VERY small distances between magnets and wires is how human and animal muscles do it. But they go all the way down to sub-10 nanometers)
It should be fairly straightforward to control dynamically so you can use pretty much any motor and gearbox.
Tendon robots are not popular for industrial use. The tendon cables wear out. Robots which do the same thing over and over wear their tendons at the same points. Not good in factory settings.
A useful model of a muscle is a spring and damper in parallel, like an auto suspension. The spring's neutral point, the spring's spring constant, and the damper's damping constant are all controllable. An actuator built that way can provide both force and position control, and can absorb shock loads. This is roughly how biological muscles behave.
The most practical actuator like that is a double-ended air cylinder. Each end has two proportional valves, to let air in from the air supply and to let air out to exhaust. Such devices can be tuned from stiff to rigid, held at any position, and can absorb shock loads, which just compress the air trapped in the cylinder. Festo, the German automation equipment manufacturer, is a leading promoter of that approach.[1] They've popularized precision pneumatic control with a computer managing the valves. Works great in factories where you can plug into a compressed air line. Festo has lots of videos online, if you like looking at pneumatic actuators.
A series elastic actuator is a different concept. It's a stiff spring on the end of a stiff screw-type linear actuator. Shock loads compress the spring, a sensor at the spring detects this, and the linear actuator is commanded to quickly spin up the motor and unload the spring. Force can be measured from the length of the spring. It's a way to fake a real force actuator with a cheap positional one.
This was a popular idea in research robotics, because it's something that can be put together from off the shelf components. It's a useful research tool. But it's not a very good actuator for large loads. There's a race between the applied load squeezing the spring and the motor spinning up to take off the load before the spring bottoms out. It's only useful for a limited load range. If the spring is too stiff, you still take a high shock load at the gear train. If the spring is too soft, the spring bottoms out before the motor can catch up. You can buy series elastic actuators from academic and hobbyist suppliers [2], but they're rarely seen in factories.
There's been much robot actuator progress in the last decade. Not miracles, just money and good specialized mechanical engineering.
[1] https://www.youtube.com/watch?v=GedJiaz_E1I
[2] https://www.hebirobotics.com/actuators
Here's an actual schematic: https://ae-pic-a1.aliexpress-media.com/kf/Sd3fe9841e4ed4871b...
Why these screws are used instead of just threads? Because rolling friction is lower than sliding friction. You can use less or more of them trading friction for shock resistance.
I see a lot of videos lately, mostly from China, and I'm curious what everybody is using.