Lightwheel-Platform Enterprise
Make Simulation Successful
Lightwheel Lab Enterprise delivers an end-to-end sim2real pipeline
and comprehensive data factory for building Physical AI models.
LW-BenchHub Training
Framework
LW-BenchHub Training Framework is designed for robotics research and development teams looking to accelerate their
work with comprehensive simulation capabilities built on IsaacLab, with upcoming Newton solver integration.
Who It’s For
Smaller Engineering Team
Larger Engineering Team
Feature Comparison
See What's Next
Full Newton-IsaacLab integration is currently in development by NVIDIA, with a small update expected in December 2024 and the comprehensive integration planned for March 2025.
Once these updates are released, LW-BenchHub will incorporate Newton's advanced physics solving capabilities.
Whether you're prototyping your first reinforcement learning policy or scaling to thousands of parallel simulations, LW-BenchHub provides the comprehensive toolkit to get started quickly and grow with your needs.
End-2-End
Data Collection Pipeline
End-to-end data collection and generation capabilities
Simulation environments
Ego-centric data collection
Data generation and augmentation
What you need
Our solution
Collect comprehensive, physics-accurate trajectories from Isaac Sim and MuJoCo that capture the full state of robot interactions:
Rich sensory data
RGB/depth visuals, proprioceptive feedback, and tactile information
Physical parameters
Kinematic states (positions, velocities, accelerations) and contact dynamics (forces, torques, collision geometry)
Multiple data collection modalities
Data Collection using Teleoperation in simulation: Human-guided demonstrations with full physics fidelity
Data Collection using Reinforcement learning in Simulation: Autonomous policy exploration and optimization
Simulation environments
What you need
Our solution
Collect comprehensive, physics-accurate trajectories from Isaac Sim and MuJoCo that capture the full state of robot interactions:
Rich sensory data
RGB/depth visuals, proprioceptive feedback, and tactile information
Physical parameters
Kinematic states (positions, velocities, accelerations) and contact dynamics (forces, torques, collision geometry)
Multiple data collection modalities
Data Collection using Teleoperation in simulation: Human-guided demonstrations with full physics fidelity
Data Collection using Reinforcement learning in Simulation: Autonomous policy exploration and optimization
Ego-centric data collection
What you need
Our solution
Gather data using physical robots and objects to capture real-world dynamics, edge cases, and environmental variations.
Bridge the sim-to-real gap with teleoperation demonstrations and sensor recordings from actual deployment scenarios.
Our system is hardware-agnostic and supports a wide range of commercial and specialized devices:
This flexibility allows us to optimize for your specific use case—whether prioritizing portability, sensor density, image quality, field of view, or real-time on-device processing capabilities.
Our data is delivered synchronized, calibrated, and formatted for immediate integration into training workflows:
Beyond visual data, our system integrates comprehensive sensor configurations tailored to your requirements:
This flexibility allows us to optimize for your specific use case—whether prioritizing portability, sensor density, image quality, field of view, or real-time on-device processing capabilities.
We deploy both tracking paradigms to provide comprehensive spatial understanding:
This dual approach delivers the visual grounding, contact dynamics, and kinematic ground truth that modern VLA architectures and world models require. Our hybrid tracking solutions enable simultaneous markerless and marker-based capture, streaming both motion data and video in real time.
Ego-centric data naturally aligns with how robots perceive and interact with their environment. Our collection methodology captures:
Our collection infrastructure leverages the same technology powering breakthrough research in egocentric AI and robotics, including datasets like Ego-Exo4D that have become foundational tools across computer vision and robotics communities.
Data generation and augmentation
data quality, quantity, and physical accuracy—customizable based on your requirements
What you need
Our solution
Leverage advanced generative models and world models (Cosmos, MimicGen, and others) to enhance data quality, quantity, and physical accuracy—customizable based on your requirements.
Augment existing datasets with procedurally generated variations, synthetic scenarios, and domain randomization to improve model robustness and generalization.
SimReady Asset Library
Production-ready assets validated for robotics simulation
Objects
Environments
Supported Tasks
Rigid objects
Articulated objects
Deformable objects
Rigid objects
Articulated objects
Deformable objects
Optimized Robot Models
Access our curated library of the most commonly used robot platforms
Commonly used robot hands in the market and robot models
Dexterous robotic hands, fine-tuned for minimal sim-to-real gap
Production-tested configurations ready for immediate use
Benchmarking &
RL Policy Evaluation API
Know exactly where you stand. Whether you're publishing research, optimizing for production deployment, or
validating a new learning algorithm, our benchmarking infrastructure gives you the credibility and insights you need.
How Does Your Approach Compare to State-of-the-Art?
Training robots for specific behaviors is just the first step — you need to know how your RL policies stack up against established benchmarks and competing approaches. Are you meeting industry standards? Outperforming baseline methods? Our automated evaluation framework gives you the answers.
Compare Against State-of-the-Art Benchmarks
Measure your policy's performance against established standards across manipulation, locomotion, and multi-robot tasks. Validate your approach against published results from leading research labs and production systems.
Automated RL Policy Evaluation API
Stop manually running evaluations — our API automatically benchmarks your trained policies across standardized test suites. Receive comprehensive performance metrics, success rates, and video recordings for detailed analysis. Track improvements across training iterations and identify performance bottlenecks.
What You Get
Objective performance metrics against recognized benchmarks
Video recordings for qualitative analysis and debugging
Automated evaluation workflows that integrate into your training pipeline
Model
Zero-shot VLM Model Evaluation
Pull the blue cable
Success rate: 0%
Unplug the blue cable
Success rate: 0%
Ready to Get Started?
The Lightwheel Enterprise Package brings together all the tools, assets, and services
you need to accelerate your robotics development from simulation to reality.