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.
Silly question maybe, but didn’t Boston Dynamics have videos of bipedal robots doing acrobatics / running ~7/8 years ago? Kinda looked like they “solved” locomotion then
Their approach required pre-computation and simulation before execution. If you watch their videos carefully, you can see the advance planning work on some of the screens.
I can understand pre-computation making the “software” problem of locomotion easier, but how does it help with the hardware problems laid out in the article, ie repeated very high load over a very short amount of time?
BD used hydraulics for a long time. Works, but inefficient. You have to carry the actuators, the tank, probably a hydraulic accumulator, the pump, valves, and the power source for the pump. That's why BD's machines were so big. Someone at Google said "We need to have a conversation about hydraulics", and the dog robot in 2019 was the first all-electric machine.
Presumably for outdoors or home deployment. The world is designed for bipedal locomotion, and human bipedal locomotion is designed for the world.
But yes, for a factory or commercial environment it doesn't make too much sense. It would be cheaper to adapt the environment, and many commercial environments are already designed to be accessible for wheelchair users anyway.
> Besides that, our entire technology is based on the human form. An automobile, for instance, has its controls so made as to be grasped and manipulated most easily by human hands and feet of a certain size and shape, attached to the body by limbs of a certain length and joints of a certain type. Even such simple objects as chairs and tables or knives and forks are designed to meet the requirements of human measurements and manner of working. It is easier to have robots imitate the human shape than to redesign radically the very philosophy of our tools.
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.
The power of money.
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.
Silly question maybe, but didn’t Boston Dynamics have videos of bipedal robots doing acrobatics / running ~7/8 years ago? Kinda looked like they “solved” locomotion then
Their approach required pre-computation and simulation before execution. If you watch their videos carefully, you can see the advance planning work on some of the screens.
I can understand pre-computation making the “software” problem of locomotion easier, but how does it help with the hardware problems laid out in the article, ie repeated very high load over a very short amount of time?
BD used hydraulics for a long time. Works, but inefficient. You have to carry the actuators, the tank, probably a hydraulic accumulator, the pump, valves, and the power source for the pump. That's why BD's machines were so big. Someone at Google said "We need to have a conversation about hydraulics", and the dog robot in 2019 was the first all-electric machine.
I feel like the loads would suit electrostatic motors quite well if those could be made appropriately compact.
I simply do not understand why you would ever prefer a fully humanoid robot as opposed to a humanoid torso on some other locomotion system.
Presumably for outdoors or home deployment. The world is designed for bipedal locomotion, and human bipedal locomotion is designed for the world.
But yes, for a factory or commercial environment it doesn't make too much sense. It would be cheaper to adapt the environment, and many commercial environments are already designed to be accessible for wheelchair users anyway.
Isaac Asimov already explained that better than I could (https://www.reddit.com/r/asimov/comments/pm84ud/why_robots_a...):
> Besides that, our entire technology is based on the human form. An automobile, for instance, has its controls so made as to be grasped and manipulated most easily by human hands and feet of a certain size and shape, attached to the body by limbs of a certain length and joints of a certain type. Even such simple objects as chairs and tables or knives and forks are designed to meet the requirements of human measurements and manner of working. It is easier to have robots imitate the human shape than to redesign radically the very philosophy of our tools.
Why the AI "engineering expert"? Seems to take some credibility away from what otherwise could be an interesting and informative read.
Yeah I couldn't get past so many issues in the AI generated illustrations. Not useful at all when they are completely wrong.
Check out opensource actuator for robots.
Opentorque actuator
https://www.gabrael.io/new-page
https://github.com/G-Levine/OpenTorque-Actuator
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.
Except we don't need 100% bipedal robots. Wheels are perfectly ok for majority of city work and factory floor.
Put the robot on rollerskates break the wheels for the occasional stair.