MotionAnimator: Semantic-to-Motion Reasoning for Animating Part-Structured 3D Assets in XR

Abstract

3D digital assets are increasingly used in education, simulation, design, and immersive content creation, yet most remain behaviorally inert: they provide geometry and component structure but lack the semantic annotations, motion constraints, and executable behaviors needed to function as dynamic objects in Extended Reality (XR). Animating such assets therefore still requires manual rigging, object-specific templates, or substantial programming expertise. We introduce MotionAnimator, an intent-driven, part-aware XR animation authoring system that transforms semantically unlabeled, part-structured 3D assets into executable animations from natural-language instructions. Rather than generating code directly from text, MotionAnimator externalizes object understanding and motion reasoning into explicit semantic and motion representations. It grounds object identity, semantic parts, and functional directions, constructs a structured plan that coordinates object- and part-level motion, and translates the plan into executable Unity behavior. On a benchmark of 90 prompts across 30 objects, MotionAnimator demonstrated reliable semantic grounding and coordinated animation generation across diverse objects and animation intents. An exploratory user study further provided insights into users' experiences with MotionAnimator and highlighted its potential for part-aware XR animation authoring. These findings demonstrate how explicit semantic and motion representations can bridge high-level user intent and executable behavior, enabling existing part-structured assets to support coordinated XR animations beyond object-level transformations and predefined behaviors.