USE CASE
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01
Equipment & Robot Simulation
- Provide real-time feedback from simulation results to AI training
- Improve control performance through reinforcement learning–based iterative optimization
- Continuously enhance performance by incorporating real operational data
02
Virtual Control & Validation Simulation
- Pre-validate robot control algorithms in a virtual environment
- Support Virtual Commissioning and Hardware-in-the-Loop (HIL) testing
- Recreate collaborative scenarios involving heterogeneous robots such as cobots and AMRs
03
World Foundation Model
- Precisely replicate the physical characteristics of equipment and robots within a 3D environment
- Enable realistic physical interactions using multi-physics engines
- Generate AI training data leveraging multimodal inputs
04
Automated Synthetic Data Generation Engine
- Automatically generate AI training data based on robot and equipment operations
- Secure diverse environment and condition scenarios through domain randomization
- Support high-precision labeling and automatic Ground Truth generation
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