Simplified Physical Model‐based Balance‐preserving Motion Re‐targeting for Physical Simulation

Abstract

In this study, we propose a novel motion re‐targeting framework that provides natural motions of target robot character models similar to the given source motions of a different skeletal structure. The natural target motion requires satisfying kinematic constraints to show a similar motion to the source motion although the kinematical structure between the source and the target character models differ from each other. Simultaneously, the target motion should maintain physically plausible features such as keeping the balance of the target character model. To handle the issue, we utilize a simple physics model (an inverted‐pendulum‐on‐a‐cart model) during the motion re‐targeting process. By interpreting the source motion's balancing property via the pendulum model, the target motion inherits the balancing property of the source motion. The inheritance is derived by performing the motion analysis to extract the necessary parameters for re‐targeting the pendulum model's motion pattern and parameter learning to estimate the suitable parameters for the target character model. Based on the simple physics inheritance, the proposed framework provides balance‐preserving target motions, even applicable to the full‐body physics simulation or a real robot control. We validate the framework by experimenting with motion re‐targeting from animal character and human character source models to the quadruped‐ and humanoid‐type target models with Muaythai punching, kicking and walking motions. We also implement comparisons with the existing methods to clarify the enhancement.