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I enjoyed this article and thought it gave a nice summary of techniques for rotation. It did leave me with a feeling of skepticism towards a few of its points.
by Agentlien 4y ago
I enjoyed this article and thought it gave a nice summary of techniques for rotation. It did leave me with a feeling of skepticism towards a few of its points.
Most of all I feel like I don't understand the usefulness of the defined map. The article does admit that computing and interpolating quaternions is very practical. The one use case given for this map over quaternions is averaging a set of rotations.
This isn't something I've regularly had to do. The closest I can think of is handling multiple competing orientation constraints in a physics solver. This is something we did at my first job and while I didn't look closely at the code I know it was neatly handled using quaternions.
- dimatura 4y agoI've worked a fair bit with 3D data in a robotics context, mostly from the perception side but also a tiny bit on the motion side (and grad coursework). In practice you have to deal with pretty much all the representations, they all have their pros/cons and in some cases more than one works fine, so different libraries will use different representations and you have to convert back and forth all the time (a fun source of bugs!). In an academic context, I feel like the community has converged on matrix exponential representation. One reason, I think, is that it's fairly good for optimization with gradient-based approaches, which is useful on its own but also meshes well with deep learning tools that are increasingly becoming more common for 3D perception (and motion planning) tasks.
- Agentlien 4y agoI work with game development and used to work in medical simulation. Most projects I've been on use primarily matrices for most transforms with quaternions used to handle pure rotations, transformed to matrices at the last possible stage.