MPL - Motion Programming Language

MPL is a domain-specific language that revolutionizes 3D motion and animation through human-readable, semantic syntax. Designed to bridge the gap between natural language and 3D movement, MPL transforms complex mathematical representations into intuitive, code-like commands that both humans and AI systems can easily understand and generate.

Current Implementation: MMD (MikuMikuDance) format support with plans for broader 3D animation ecosystems.

Gallery and playground

Why MPL?

MPL democratizes 3D motion creation and unlocks powerful AI capabilities:

🎯 Human-Centric Design

Semantic commands: Express complex 3D movements through intuitive, readable syntax
Natural language alignment: Bridge the gap between human intent and 3D mathematics
Built-in safety: Anatomically-aware constraints prevent impossible poses automatically

🤖 AI & Machine Learning Ready

LLM-friendly syntax: Structured, predictable grammar enables language models to understand and generate motion
Training-optimized: Semantic tokens create rich datasets for AI motion synthesis
Compositional intelligence: Modular pose components allow AI to learn and recombine movement patterns
Cross-modal potential: Text-to-motion, motion-to-text, and motion-to-motion transformations

🔧 Developer Benefits

Composable architecture: Reuse and combine animation building blocks
Version control friendly: Text-based format integrates seamlessly with development workflows
Extensible framework: Domain-agnostic design supports future 3D animation formats

Syntax

Pose Definitions

@pose kick_left {
    leg_l bend forward 30;
    knee_l bend backward 0;
    leg_r bend backward 20;
    knee_r bend backward 15;
}

@pose kick_right {
    leg_r bend forward 30;
    knee_r bend backward 0;
    leg_l bend backward 20;
    knee_l bend backward 15;
}

Animation Sequences

@animation walk {
    0: kick_left;
    0.3: kick_right;
    0.6: kick_left;
    0.9: kick_right;
}

Main Execution

main {
    walk;
}

Bone Commands

Format: bone action direction amount

Actions: bend, turn, sway, move
Directions: forward, backward, left, right, up, down

Supported Bones

Body Core: base, center, upper_body, waist, neck, head
Arms: shoulder_l/r, arm_l/r, arm_twist_l/r, elbow_l/r, wrist_l/r, wrist_twist_l/r
Legs: leg_l/r, knee_l/r, ankle_l/r, toe_l/r
Fingers: thumb_0/1/2_l/r, index_0/1/2_l/r, middle_0/1/2_l/r, ring_0/1/2_l/r, pinky_0/1/2_l/r

Use Cases

🎬 Creative Applications

Natural language to motion: Transform descriptions like "wave hello" or "sit down" into 3D animations
Procedural animation: Generate variations and combinations of existing movement patterns
Interactive storytelling: Create dynamic character animations through conversational interfaces

🤖 AI & Research Applications

Motion synthesis training: Use MPL's semantic structure to train generative models for 3D animation
Cross-modal learning: Enable AI systems to understand relationships between language, motion, and visual content
Behavioral modeling: Research human movement patterns through structured, analyzable motion data
Animation assistance: AI-powered tools for pose correction, completion, and stylistic adaptation

🛠️ Development & Production

Rapid prototyping: Quickly iterate on character animations without complex 3D software
Automated content creation: Generate animation assets programmatically for games and applications
Motion capture enhancement: Post-process and refine motion capture data using semantic editing
Cross-platform compatibility: Bridge different 3D animation formats through MPL's universal syntax

📚 Education & Accessibility

Animation learning: Teach 3D animation concepts through intuitive, code-like syntax
Accessibility tools: Enable motion creation for users without traditional 3D animation expertise
Documentation: Create readable, maintainable animation specifications

🚀 Future Vision

MPL is designed as a foundational language for the next generation of AI-powered motion synthesis:

Universal Motion Representation: Expand beyond MMD to support industry-standard formats (FBX, BVH, USD, etc.)
Large Motion Models (LMMs): Enable training of specialized AI models that understand human movement semantics
Multimodal AI Integration: Seamless integration with vision, language, and audio AI systems
Real-time Motion Generation: Live animation synthesis for gaming, VR/AR, and interactive media
Collaborative AI Tools: Human-AI partnerships in creative motion design and animation production

📄 License

GPL-3.0 License - see LICENSE for details.

mmd-mpl 0.2.16