IKDP

Inverse kinematics through a diffusion process

Solving inverse kinematics with a conditional DDPM instead of a regression network.

  • Proposed and implemented conditional-DDPM inverse kinematics.
  • Engineered the training and inference pipeline for stable, constraint-aware IK generation.
  • Outperformed IKNet by 14% and an MLP baseline by 84% in accuracy.