Basically in PGA2D, rotations, angular velocity/acceleration, torque etc automatically get handled by geometric product of multivectors. The additional dimension makes all rotations centered at origin, which makes them compose much more nicely.
Basically in PGA2D, rotations, angular velocity/acceleration, torque etc automatically get handled by geometric product of multivectors. The additional dimension makes all rotations centered at origin, which makes them compose much more nicely.
So you think would PGA aid in understanding the weird properties of SO(3) and SE(3) (and its tangent spaces), as well as writing simulation code with it? I know that people use various representations for rigid transformations (screws vs. dual quaternions vs. exponential maps vs. motors), but I am interested which method would work the best in both a theoretical sense (in understanding the kinematics and dynamics more abstractly) and in a pragmatic sense (difficulty of writing and reading actual simulation code, amount of operations used, SIMD-friendliness, etc.)
You might find Professor Lasenby's 2020 talk (among others at Bivector Youtube channel) useful: https://www.youtube.com/watch?v=m7v2IUJtC3g
I didn’t even notice at first. I just thought “oh that’s cool: they’ve primed the physics so it bounces through neat patterns before settling”. But my brain was gently tapping my shoulder... When I listened to it I noticed it was a hypercube, saw “n-dimensional“, and WOW