A language-directed virtual human motion generation approach based on musculoskeletal models

The development of the systems capable of synthesizing natural and life-like motions for virtual characters has long been a central focus in computer animation. It needs to generate high-quality motions for characters and provide users with a convenient and flexible interface for guiding character motions. In this work, we propose a language-directed virtual human motion generation approach based on musculoskeletal models to achieve interactive and higher-fidelity virtual human motion, which lays the foundation for the development of language-directed controllers in physics-based character animation. First, we construct a simplified model of musculoskeletal dynamics for the virtual character. Subsequently, we propose a hierarchical control framework consisting of a trajectory tracking layer and a muscle control layer, obtaining the optimal control policy for imitating the reference motions through the training. We design a multi-policy aggregation controller based on large language models, which selects the motion policy with the highest similarity to user text commands from the action-caption data pool, facilitating natural language-based control of virtual character motions. Experimental results demonstrate that the proposed approach not only generates high-quality motions highly resembling reference motions but also enables users to effectively guide virtual characters to perform various motions via natural language instructions.