Ian R. Manchester

LOInK: Learned Optimal Inverse Kinematics via Structured Neural Surrogate Models

We introduce Learned Optimal Inverse Kinematics (LOInK), a method to generate approximately optimal solutions to an inverse kinematics problem. When trained on data consisting of sampled configurations and associated task variables and a given cost function, LOInK learns a bi-Lipschitz invertible mapping from configura...