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This is what StuffMadeHere used in his latest video to simulate a mini-golf course! https://www.youtube.com/watch?v=2OfjZ3ORJfc&t=368s https://www.youtube.com/w

by cachius 6mo ago

This is what StuffMadeHere used in his latest video to simulate a mini-golf course! https://www.youtube.com/watch?v=2OfjZ3ORJfc&t=368s https://www.youtube.com/watch?v=2OfjZ3ORJfc&t=368s The physics engine I'm using is called MuJoCo. And if you're wondering why I didn't write my own physics engine, it's basically because I don't have 20 years.

prathje 6mo ago
That the calibration got the simulation so close to reality was quite impressive.
- cachius 6mo ago
  Though he had to resort to manual calibration. I always find he has interesting problems for domain experts and would like to see him team up with one. Also with programmers for faster programs than self taught python.
  - Izikiel43 6mo ago
    The guy has a masters in compsci and mechanical engineering, he has done both python and c++ afaik for his projects
    - liuliu 6mo ago
      I think the parent comment is specifically addressing why the black box (or stochastic?) optimizer he used not working.
    - ghusbands 6mo ago
      In the video in question, he doesn't seem able to choose a good scoring function for the stochastic solver (even over multiple weeks), seemingly choosing a linear sum of distances (see 8:50) between simulation and reality. That's a mistake that not even an undergraduate should make. He needs some domain experts.
      - Izikiel43 6mo ago
        I did comp sci, I sucked at this stuff, and I have a masters. Low level stuff? Os? Distributed systems? Multithreaded code? Now that’s more on my alley
nestorD 6mo ago
It's what put MuJoCo on my radar recently! But I was surprised to not see him do any kind of gradient descent to optimize his hyperparameters. MuJoCo has a JAX backend so it should be fairly straightforward.
- petters 6mo ago
  He is much better at building hardware than he is writing software.
  - KeplerBoy 6mo ago
    He seems pretty damn good at both.
- lpribis 6mo ago
  I'm pretty sure he has used gradient descent in previous videos to optimize systems, maybe this time it was just easier to hand tune rather than set up an optimization feedback harness around MuJoCo.

by cachius 6mo ago

prathje 6mo ago

That the calibration got the simulation so close to reality was quite impressive.

cachius 6mo ago
Though he had to resort to manual calibration. I always find he has interesting problems for domain experts and would like to see him team up with one. Also with programmers for faster programs than self taught python.
- Izikiel43 6mo ago
  The guy has a masters in compsci and mechanical engineering, he has done both python and c++ afaik for his projects
  - liuliu 6mo ago
    I think the parent comment is specifically addressing why the black box (or stochastic?) optimizer he used not working.
  - ghusbands 6mo ago
    In the video in question, he doesn't seem able to choose a good scoring function for the stochastic solver (even over multiple weeks), seemingly choosing a linear sum of distances (see 8:50) between simulation and reality. That's a mistake that not even an undergraduate should make. He needs some domain experts.
    - Izikiel43 6mo ago
      I did comp sci, I sucked at this stuff, and I have a masters. Low level stuff? Os? Distributed systems? Multithreaded code? Now that’s more on my alley

nestorD 6mo ago

It's what put MuJoCo on my radar recently! But I was surprised to not see him do any kind of gradient descent to optimize his hyperparameters. MuJoCo has a JAX backend so it should be fairly straightforward.

petters 6mo ago
He is much better at building hardware than he is writing software.
- KeplerBoy 6mo ago
  He seems pretty damn good at both.
lpribis 6mo ago
I'm pretty sure he has used gradient descent in previous videos to optimize systems, maybe this time it was just easier to hand tune rather than set up an optimization feedback harness around MuJoCo.