3 ms·

Related: https://eater.net/quaternions https://eater.net/quaternions

by incognito124 2y ago

t55 2y ago
wow love the fact that you can interact with the videos
- incognito124 2y ago
  That's what's most valuable to me too. If I remember correctly, Ben Eater (8bit CPU from scratch guy) and Grant Sanderson (3b1b guy) tried to do a little experiment on education with this guided-yet-interactive learning material back in 2018 (!!). As someone working in EDU sector of tech, I'm constantly amazed by what people come up with in order to explain things to other people (or even themselves). Whatever the experiment was, I'd say it was a success, and I hope we get to see more such material on other topics in future.
FpUser 2y ago
What a beautiful and high quality presentations. All the praises to the author.
dang 2y ago
Related: Visualizing quaternions (2018) - https://news.ycombinator.com/item?id=38043644 https://news.ycombinator.com/item?id=38043644 - Oct 2023 (42 comments) Visualizing quaternions: an explorable video series (2018) - https://news.ycombinator.com/item?id=31083042 https://news.ycombinator.com/item?id=31083042 - April 2022 (15 comments) Visualizing quaternions: An explorable video series - https://news.ycombinator.com/item?id=18310788 https://news.ycombinator.com/item?id=18310788 - Oct 2018 (32 comments)
ge96 2y ago
I still gotta grasp this for IMUs
- Joel_Mckay 2y ago
  In general, the better sensor fusion algorithms incorporate kalman filtering. https://www.olliw.eu/2013/imu-data-fusing/#chapter23 https://www.olliw.eu/2013/imu-data-fusing/#chapter23 Best of luck =3
  - ge96 2y ago
    Yeah something else I need to do. lazy question, if I have an IMU that is swaying around as I try to move in a linear direction (e.g. Forward) is that something this kind of filtering would be used for? Regarding displacement estimation. Edit: I get fusion is regarding multiple sensors
    - Joel_Mckay 2y ago
      Normally, there are several types of sensors available, but most use 9DOF packages (3-axis gyroscope, accelerometer, and magnetometer) gyroscope: fast over-sampled low-pass filter, but slowly drifts compounding heading errors accelerometer: relatively stable, but dead-reckoning errors compound quickly magnetometer: best stability, but low-sample rate and vulnerable to metal/magnets fooling/blinding the sensors The fusion algorithms usually weights which data is consistent with the motion path, and attenuates the estimated pose errors. Notably, not all sensors are equal quality, but there are probably better options now. =3
jdranczewski 2y ago
This was an invaluable resource 5 years ago when I was working on a summer research project making a ray tracing-based optical levitation simulator - initially it felt a bit insane to try to deeply understand this obscure bit of maths to implement rotations, but once it clicked it clicked. Quaternions ended up being a super neat formalism for writing and computing rotational equations of motion. https://github.com/jdranczewski/optical-levitation-raytracing-experiments https://github.com/jdranczewski/optical-levitation-raytracin... for my repo, and https://onlinelibrary.wiley.com/doi/abs/10.1002/nme.5165 https://onlinelibrary.wiley.com/doi/abs/10.1002/nme.5165 for the rotational dynamics with quaternions.
deleted 2y ago
[deleted]
ks2048 2y ago
FYI - if you're like me, you just looked at the page thinking it had some links to 3blue1brown videos. Not obvious that those are thumbnails link to interactive video apps. Very cool.

Related: https://eater.net/quaternions https://eater.net/quaternions

t55 2y ago

wow love the fact that you can interact with the videos

incognito124 2y ago
That's what's most valuable to me too. If I remember correctly, Ben Eater (8bit CPU from scratch guy) and Grant Sanderson (3b1b guy) tried to do a little experiment on education with this guided-yet-interactive learning material back in 2018 (!!). As someone working in EDU sector of tech, I'm constantly amazed by what people come up with in order to explain things to other people (or even themselves). Whatever the experiment was, I'd say it was a success, and I hope we get to see more such material on other topics in future.

FpUser 2y ago

What a beautiful and high quality presentations. All the praises to the author.

dang 2y ago

Related: Visualizing quaternions (2018) - https://news.ycombinator.com/item?id=38043644 https://news.ycombinator.com/item?id=38043644 - Oct 2023 (42 comments) Visualizing quaternions: an explorable video series (2018) - https://news.ycombinator.com/item?id=31083042 https://news.ycombinator.com/item?id=31083042 - April 2022 (15 comments) Visualizing quaternions: An explorable video series - https://news.ycombinator.com/item?id=18310788 https://news.ycombinator.com/item?id=18310788 - Oct 2018 (32 comments)

ge96 2y ago

I still gotta grasp this for IMUs

Joel_Mckay 2y ago
In general, the better sensor fusion algorithms incorporate kalman filtering. https://www.olliw.eu/2013/imu-data-fusing/#chapter23 https://www.olliw.eu/2013/imu-data-fusing/#chapter23 Best of luck =3
- ge96 2y ago
  Yeah something else I need to do. lazy question, if I have an IMU that is swaying around as I try to move in a linear direction (e.g. Forward) is that something this kind of filtering would be used for? Regarding displacement estimation. Edit: I get fusion is regarding multiple sensors
  - Joel_Mckay 2y ago
    Normally, there are several types of sensors available, but most use 9DOF packages (3-axis gyroscope, accelerometer, and magnetometer) gyroscope: fast over-sampled low-pass filter, but slowly drifts compounding heading errors accelerometer: relatively stable, but dead-reckoning errors compound quickly magnetometer: best stability, but low-sample rate and vulnerable to metal/magnets fooling/blinding the sensors The fusion algorithms usually weights which data is consistent with the motion path, and attenuates the estimated pose errors. Notably, not all sensors are equal quality, but there are probably better options now. =3

jdranczewski 2y ago

This was an invaluable resource 5 years ago when I was working on a summer research project making a ray tracing-based optical levitation simulator - initially it felt a bit insane to try to deeply understand this obscure bit of maths to implement rotations, but once it clicked it clicked. Quaternions ended up being a super neat formalism for writing and computing rotational equations of motion. https://github.com/jdranczewski/optical-levitation-raytracing-experiments https://github.com/jdranczewski/optical-levitation-raytracin... for my repo, and https://onlinelibrary.wiley.com/doi/abs/10.1002/nme.5165 https://onlinelibrary.wiley.com/doi/abs/10.1002/nme.5165 for the rotational dynamics with quaternions.

deleted 2y ago

[deleted]

ks2048 2y ago

FYI - if you're like me, you just looked at the page thinking it had some links to 3blue1brown videos. Not obvious that those are thumbnails link to interactive video apps. Very cool.