Abstract: In various embodiments, an inverse kinematic (IK) modeling application generates models that are used to solve IK problems for object animations. The IK modeling application generates configuration vectors based on a set of joint parameters associated with a joint chain. The IK modeling application executes forward kinematic operation(s) on the joint chain based on the configuration vectors to generate target vectors. Each target vector includes data associated with at least one of a position or an orientation for an end-effector associated with the joint chain. The IK modeling application performs one or more machine learning (ML) operations on an ML model based on the configuration vectors and the target vectors to generate a trained ML model that computes a predicted joint vector associated with the joint chain based on at least one of a target position or a target orientation for the end-effector.

Abstract: In various embodiments, a computer animation application automatically solves inverse kinematic problems when generating object animations. The computer animation application determines a target vector based on a target value for a joint parameter associated with a joint chain and at least one of a target position or a target orientation for an end-effector associated with the joint chain. The computer animation application executes a trained machine learning model on the target vector to generate a predicted vector that includes data associated with multiple joint parameters associated with the joint chain.