--- title: Generate Synthetic Data of Dynamic Environments With a Custom Isaac Sim-Based Framework [S51570] tags: GTC2023 description: Nvidia 2023 GTC session --- # Generate Synthetic Data of Dynamic Environments With a Custom Isaac Sim-Based Framework [S51570] # Nvidia issac sim ## Grade GRADE is a system I developed to seamlessly manage the Isaac Sim simulation software to Generate Realistic Animated Dynamic Environments for Robotics Research. ![image](https://github.com/shaung08/GTC2023/raw/main/Generate%20Synthetic%20Data%20of%20Dynamic%20Environments%20With%20a%20Custom%20Isaac%20Sim-Based%20Framework%20%5BS51570%5D/img/img01.png) ### grade main componets 1. Readlistic Environmnets 2. Animaton Assets 3. Custom robots 4. A Customizable pipeline 5. Additional processing tools ### grade software pipeline 1. create environment * Blender * Unreal Engine * Digital twin 2. Convert to USD format 3. Load it into Isaac Sim 4. Using sdk to set environment and camera to generate dataset #### Verify yolo people detection: 1. Train on synthetic data -> fine tune on S-coco dataset and full coco dataset 2. Train on S-coco dataset and full coco dataset **Result: 1. is more accurate than 2.** --- ## 參考 * [https://github.com/eliabntt/GRADE-RR](https://github.com/eliabntt/GRADE-RR) ## Thank you! :dash: You can find me on - GitHub: https://github.com/shaung08 - Email: a2369875@gmail.com