ShadowEngine

End-to-End Embodied AI Infrastructure

ShadowEngine is an embodied AI infrastructure platform built on high-precision motion capture data, enabling a complete data–training–validation loop from human skill acquisition to robotic deployment.

Core Capability

It solves critical bottlenecks in embodied AI development.

fragmented data collection and utilization
inefficient data format transformation
disconnected training, simulation, and deployment workflows

Standardized Data Asset Library

NKV-SE Source

A large-scale repository of high-quality motion datasets designed for robot learning and embodied AI applications.

Key Features

1,000+ hours of cleaned human motion data captured with NOKOV motion capture systems 100,000+ high-quality motion samples
1,000+ hours of retargeted datasets for Unitree G1 robots
Fundamental action libraries including walking, running, jumping, grasping, and manipulation
Standardized formats supporting multiple robot platforms

Multi-Modal Data Hub

NKV-SE Fusion

A unified platform for synchronizing, managing, and organizing large-scale multimodal robot learning data

Key Features

Real-time synchronization of motion capture, IMU, force plate, EMG, EEG, robot joint states, cameras, LiDAR, and audio.

Data collection task management
Dataset permission and access control
Annotation, tagging, inheritance, and sharing
Dataset version tree management
Import, export, cleaning, and user administration tools

Motion Retargeting Platform

NKV-SE ReTarget

A high-precision motion retargeting platform for embodied robots. Powered by dynamics-aware optimization, it accurately transfers human motion capture data to robot models while supporting large-scale simulation to accelerate robot training.

Key Features

Real-time and offline retargeting
Expert data export for model training
Open APIs for URDF/MJCF robot integration
Interactive parameter tuning and customization

Robot Teleoperation Platform

NKV-SE TeleOp

NKV-SE TeleOp delivers immersive, low-latency robot teleoperation powered by high-precision motion capture data.

Key Features

Supports Unitree G1 and other robot platforms
Rapid adaptation to different robots through
Enables intuitive full-body teleoperation with smooth, responsive motion replication for walking, running, squatting, and other complex movements.

Sim-to-Real Validation Platform

NKV-SE Valid

A Sim-to-Real closed-loop validation system that addresses the performance differences between real robots and simulation environments. It feeds validation results back to the training platform for further model optimization.

It also solves the motion consistency issues in mass production of robots and serves as a universal motion consistency evaluation platform for general-purpose robots.

Key Features

Compare position, velocity, and acceleration
Configure custom evaluation metrics and benchmarks
Analyze performance data and identify abnormal frames
Save evaluation results and build robot performance profiles

AI Model Training Platform

NKV-SE Train

Key Features

Integrates high-fidelity physics simulation and mainstream reinforcement learning frameworks
Proprietary training platform optimized for motion capture–driven robot learning.Fills the gap in public training solutions for motion capture–based robot learning