Sim-to-Real Transfer Skill
Techniques for minimizing simulation-to-reality gap and validating transfer
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技能内容
Sim-to-Real Transfer Skill
Overview
Expert skill for bridging the simulation-to-reality gap through domain randomization, system identification, and transfer validation techniques.
Capabilities
- Implement domain randomization (physics, appearance, dynamics)
- Configure system identification for simulation parameters
- Set up adaptive domain randomization
- Implement domain adaptation techniques
- Configure noise injection for robust policies
- Set up reality gap metrics and monitoring
- Implement progressive network transfer
- Configure latency simulation
- Set up sensor noise modeling
- Implement hardware-in-the-loop validation
Target Processes
- sim-to-real-validation.js
- digital-twin-development.js
- rl-robot-control.js
- field-testing-validation.js
Dependencies
- Simulation environments (Gazebo, Isaac Sim)
- Physical robot access
- System identification tools
Usage Context
This skill is invoked when processes require transferring simulation-trained models or behaviors to real robot hardware with minimal performance degradation.
Output Artifacts
- Domain randomization configurations
- System identification results
- Reality gap analysis reports
- Transfer validation metrics
- Sensor noise models
- Calibrated simulation parameters
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原文件路径
library/specializations/robotics-simulation/skills/sim-to-real/SKILL.md