CLAW: Composable Language-Annotated Whole-body Motion Generation

• URL: http://arxiv.org/abs/2604.11251v3
• Date: Fri, 17 Apr 2026 08:04:02 GMT
• Title: CLAW: Composable Language-Annotated Whole-body Motion Generation
• Abstract summary: We present CLAW, a pipeline for scalable generation of language-annotated whole-body motion data.<n>CLAW composes motion primitives from a kinematic planner, parameterized by movement, heading, speed, pelvis height, and duration.<n>A low-level controller tracks these references in MuJoCo simulation, yielding physically grounded trajectories.
• Score: 55.99805728566105
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Training language-conditioned whole-body controllers for humanoid robots demands large-scale motion-language datasets. Existing approaches based on motion capture are costly and limited in diversity, while text-to-motion generative models produce purely kinematic outputs that are not guaranteed to be physically feasible. We present CLAW, a pipeline for scalable generation of language-annotated whole-body motion data for the Unitree G1 humanoid robot. CLAW composes motion primitives from a kinematic planner, parameterized by movement, heading, speed, pelvis height, and duration, and provides two browser-based interfaces--a real-time keyboard mode and a timeline-based sequence editor--for exploratory and batch data collection. A low-level controller tracks these references in MuJoCo simulation, yielding physically grounded trajectories. In parallel, a template-based engine generates diverse natural-language annotations at both segment and trajectory levels. To support scalable generation of motion-language paired data for humanoid robot learning, we make our system publicly available at: https://github.com/JianuoCao/CLAW

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