4 ms·

Most tendons materials are elastic. That lead to create calibration problems and require proprioceptive sensors in the hand

fusslo 1y ago
Huh, never thought of that I wonder if companies are experimenting with materials like UHMWPE for non-elastic, high strength-to-diameter tendons. I dont know if you'd have to weld the dyneema to the anchor points, though
- imtringued 1y ago
  I think you're misunderstanding the essence of the problem. If you use tendons, you'll need a neural network in your control loop that can learn continuously so that it compensates rope stretch and changes in friction through wear and tear. A lot of problems in robotics reduce down to continual learning. Essentially all system identification tasks become obsolete the moment you have a self learning system and yet we have an AI industry preaching that AGI is around the corner without this "crutch".
  - stefanka 1y ago
    Not to mention that they easily break and are annoyingly tedious to be replaced (I had to assist often enough on such "surgeries" in our lab)
  - amelius 1y ago
    You could add encoder patterns to the tendons, like stripes. And then use something like a mouse-sensor to track them. This is still much lighter than servos. Another idea is to use an external camera or two and to track the fingers with a deep learning model. But this can become messy if other objects are in view. And it might also introduce more control delay in the feedback loop than a simple sensor.
    - stefanka 1y ago
      If space permits you should add absolute encoders in the joints. In a finger that’s likely a challenge. In an arm, that’s easy
  - stefanka 1y ago
    You don't necessarily need neural networks for that, there are more specialized function approximations that learn faster and enable life-long learning for kinematics/dynamics and extrapolate better than NN which are more general purpose.
  - spauldo 1y ago
    I would think pressure and angle sensors tied to a PID loop would suffice, but I'm not a roboticist.
    - stefanka 1y ago
      If you can get a feedback loop at the respective joint, then yes, this might be enough. In case of an arm (not this hand), you can often only observe the end of a chain, and then, that’s more complex
- stefanka 1y ago
  Roboy used dyneema tendons if I recall correctly. Fluidic actuators is another option. IMO, additional sensors and sensor fusion are necessary but this will raise the costs and demand to control software significantly. We are researching humanoid robots for quite some decades now and these problems are easily underestimated (similarly to autonomous driving). I doubt we'll see them in our houses very soon.
  - fusionadvocate 1y ago
    The issue is not that these problems are easily underestimated, but that the researchers are very proficient at repeating the same mistakes over and over again.
    - stefanka 1y ago
      Or both …
Symmetry 1y ago
In practice force sensing is more useful than proprioception in most cases, at least for grasping. Generally you won't the dimensions of an object you're attempting to grasp anywhere near as well as you would know the shape of the hand you're using so a certain amount of underactuated compliance makes the job a lot easier.
- stefanka 1y ago
  I agree. But even then elasticity had to be taken into account (and maybe even gravity), if the object is very delicate.

fusslo 1y ago

Huh, never thought of that I wonder if companies are experimenting with materials like UHMWPE for non-elastic, high strength-to-diameter tendons. I dont know if you'd have to weld the dyneema to the anchor points, though

imtringued 1y ago
I think you're misunderstanding the essence of the problem. If you use tendons, you'll need a neural network in your control loop that can learn continuously so that it compensates rope stretch and changes in friction through wear and tear. A lot of problems in robotics reduce down to continual learning. Essentially all system identification tasks become obsolete the moment you have a self learning system and yet we have an AI industry preaching that AGI is around the corner without this "crutch".
- stefanka 1y ago
  Not to mention that they easily break and are annoyingly tedious to be replaced (I had to assist often enough on such "surgeries" in our lab)
- amelius 1y ago
  You could add encoder patterns to the tendons, like stripes. And then use something like a mouse-sensor to track them. This is still much lighter than servos. Another idea is to use an external camera or two and to track the fingers with a deep learning model. But this can become messy if other objects are in view. And it might also introduce more control delay in the feedback loop than a simple sensor.
  - stefanka 1y ago
    If space permits you should add absolute encoders in the joints. In a finger that’s likely a challenge. In an arm, that’s easy
- stefanka 1y ago
  You don't necessarily need neural networks for that, there are more specialized function approximations that learn faster and enable life-long learning for kinematics/dynamics and extrapolate better than NN which are more general purpose.
- spauldo 1y ago
  I would think pressure and angle sensors tied to a PID loop would suffice, but I'm not a roboticist.
  - stefanka 1y ago
    If you can get a feedback loop at the respective joint, then yes, this might be enough. In case of an arm (not this hand), you can often only observe the end of a chain, and then, that’s more complex
stefanka 1y ago
Roboy used dyneema tendons if I recall correctly. Fluidic actuators is another option. IMO, additional sensors and sensor fusion are necessary but this will raise the costs and demand to control software significantly. We are researching humanoid robots for quite some decades now and these problems are easily underestimated (similarly to autonomous driving). I doubt we'll see them in our houses very soon.
- fusionadvocate 1y ago
  The issue is not that these problems are easily underestimated, but that the researchers are very proficient at repeating the same mistakes over and over again.
  - stefanka 1y ago
    Or both …

Symmetry 1y ago

In practice force sensing is more useful than proprioception in most cases, at least for grasping. Generally you won't the dimensions of an object you're attempting to grasp anywhere near as well as you would know the shape of the hand you're using so a certain amount of underactuated compliance makes the job a lot easier.

stefanka 1y ago
I agree. But even then elasticity had to be taken into account (and maybe even gravity), if the object is very delicate.