arxiv_ml 95% Match Software/Framework Paper Robotics researchers,Computer graphics researchers,AI researchers,Game developers,Animators 3 weeks ago

MimicKit: A Reinforcement Learning Framework for Motion Imitation and Control

robotics › robotics-rl

📄 Abstract

Abstract: MimicKit is an open-source framework for training motion controllers using motion imitation and reinforcement learning. The codebase provides implementations of commonly-used motion-imitation techniques and RL algorithms. This framework is intended to support research and applications in computer graphics and robotics by providing a unified training framework, along with standardized environment, agent, and data structures. The codebase is designed to be modular and easily configurable, enabling convenient modification and extension to new characters and tasks. The open-source codebase is available at: https://github.com/xbpeng/MimicKit.

Authors (1)

Xue Bin Peng

Submitted

October 15, 2025

arXiv Category

cs.GR

arXiv PDF Code

Key Contributions

MimicKit provides an open-source, modular framework for training motion controllers using both motion imitation and reinforcement learning. It offers implementations of common techniques and algorithms, standardized structures, and is designed for easy extension, supporting research and applications in computer graphics and robotics.

Business Value

Accelerates research and development in robotics and computer graphics by providing a standardized, reusable, and extensible framework for training complex motion controllers, reducing development time and fostering collaboration.

Paper Metadata

Innovation Type

Framework/Tooling

Deployment Feasibility

High, as it's a software framework designed for research and development.

Limitations Addressed

Lack of a unified framework for motion imitation and RL,Inconsistent environment/agent/data structures across research,Difficulty in extending existing methods to new characters/tasks

View Code on GitHub

Technical Tags

motion imitationreinforcement learningrobotics controlcomputer graphicsopen-source frameworkmodular designcharacter animationmotion synthesispolicy learningRL algorithms

Research Topics

Robotics ControlMotion ImitationReinforcement LearningComputer GraphicsAI Frameworks

Methods & Architectures

Motion Imitation techniquesReinforcement Learning algorithms

Applications & Tasks

Robotics Computer Graphics Animation Virtual Reality Training motion controllersUnified training frameworkStandardized environment/agent/data structures Motion imitationRobotics controlCharacter animationMotion synthesis

Related Fields

RoboticsComputer GraphicsMachine LearningReinforcement LearningAnimation

Keywords

motion imitationreinforcement learningroboticscomputer graphicsanimationcontrol frameworkopen-sourcemodularmotion synthesischaracter controlpolicy learningRL algorithms

Academic Context

#Robotics Control#Motion Imitation#Reinforcement Learning#Computer Graphics#AI Frameworks

Technology Stack

Frameworks & Libraries

MimicKit

Commercial Potential

Potential Products

Robotics control softwareAnimation toolsVirtual character animation systems

Target Industries

RoboticsGamingFilm and AnimationVirtual Reality

Use Case Examples

Training robots to perform complex manipulation tasks through imitationCreating realistic character animations for games and filmsDeveloping virtual agents for simulations

Competitive Edge

Provides a unified and extensible platform for motion imitation and RL, simplifying the development process compared to using disparate libraries.

Market Opportunity

Significant interest in advanced robotics and animation tools.

Revenue Models

Support servicescustom developmentintegration.

Resource Requirements

Compute Needs

Varies depending on the complexity of the tasks and RL algorithms used.

Data Requirements

Motion capture data for imitation, simulation environments for RL.

Deployment Constraints

Requires expertise in RL and robotics for effective application.

Scalability

Designed to be modular and extensible for new characters and tasks.

Production Readiness

Maturity Level

Released Framework

Time to Market

Short (for research use)

Licensing

Open Source

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