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VDTraining: One-Stop Robot Reinforcement & Imitation Learning Platform

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USD$8,000.00 USD$5,000.00 (% off)

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VDTraining: One-Stop Robot Reinforcement & Imitation Learning Platform

VDTraining is an all-in-one Web-based training workbench and sim2sim simulation validation toolkit designed for modern robotics. It seamlessly integrates motion capture data conversion, imitation learning, policy simulation validation, model exporting, and real-robot deployment. VDTraining delivers a complete, closed-loop pipeline from raw motion capture data collection directly to physical robot action deployment.

Key Capabilities & Features

All-in-One Web-Based Workbench:
Features an intuitive, visual web interface that simplifies complex workflows into a user-friendly “select parameters, click, and view results” R&D experience. No complex command-line operations required.
Multi-GPU Parallel Scheduling:
Built for high-performance computing, supporting multi-GPU parallel acceleration to drastically reduce policy training times.
Real-Time Visualization & Tuning:
Monitor training curves in real-time and dynamically adjust reward parameters and action sampling strategies directly through the web interface.
Sim2Sim Validation & Frame Capture:
Validate trained policy models in high-fidelity sim2sim environments, with support for policy model frame-capturing to analyze robot behaviors in detail.
100% Open Source & Easy Deployment:
Offers full source code access with comprehensive installation guides and one-click environment setup, allowing researchers and developers to get started instantly.

Ideal Application Scenarios

Robot Reinforcement Learning & Imitation Learning
Academic Research & Algorithm Verification
Robotics Product Demonstrations & Prototyping
Humanoid Robot Motion Control Development

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Why Choose Our Robotics RL Solution?

Bridging the gap between human motion capture and robotic execution is complex. Our solution eliminates the guesswork by providing a unified robot motion training pipeline.

Seamless Sim-to-Real Deployment: Transition confidently from physics simulators to physical hardware with proven deployment scripts.
Unitree G1 Ready: Includes pre-configured parameters and case studies specifically optimized for the Unitree G1 humanoid robot.
Open Source Architecture: Gain full control with accessible Python source code for data processing, training, inference, and deployment.
Zero-to-One Guidance: Whether you are setting up your first robot learning environment or deploying complex AI models, our step-by-step documentation ensures your success.

What’s Included in the Training Package?

Our Robotics AI training package is divided into five core modules, providing everything you need to build, train, and deploy.

1. Comprehensive RL Documentation

Get up to speed quickly with our detailed manuals covering the entire reinforcement learning for robotics workflow:

Environment Setup Guide: Step-by-step dependency lists and version requirements for Linux.
Data Format Specifications: Clear guidelines for pre-RL human motion data and post-RL robot model formats.
Model Architecture & Training Manuals: Deep dives into RL model parameters, source code explanations, and training startup guides.
Simulation & Hardware Manuals: Detailed instructions for robot simulation validation and real-world execution.

2. Complete RL Resource Package

Access the core engine of your robot motion training pipeline. This package includes the complete source code and standard robot parameter files:

Robot Project Files: Source code for common humanoid robots.
Data Processing Scripts: Modules for input/output data preprocessing and robot motion data retargeting.
Training & Inference Architecture: End-to-end scripts to turn raw motion data into deployable RL models.
Sim-to-Real Scripts: Dedicated code for both simulation testing and physical robot execution.

3. Engineering Deployment Services

Skip the setup headaches. Our engineering team provides robust support for environment installation across multiple OS and GPU versions. We help you configure directory trees, set up single-script rapid training, and establish a complete engineering pipeline for model training and visualization.

4. Step-by-Step Case Study Documentation

Learn by doing with our fully illustrated, practical tutorials based on real-world applications:

RL Model Training Guide: Learn how to ingest data, tune parameters, and export deployable models.
Simulation Reproduction Guide: Instructions on loading models and visualizing training results in a simulated environment.
Hardware Reproduction Guide: A foolproof guide to deploying your RL model onto a physical robot and executing inference scripts.