tongsim

TongSIM is a high-fidelity platform for training and testing embodied agents using Unreal Engine and Python SDK. It benefits operations teams by enabling realistic simulations for agent development. It connects to workflows involving agent training, testing, and deployment.

1. **Install Dependencies:** Set up TongSIM (Unreal Engine 5.3+ and Python 3.10) and clone the official GitHub repo. Install required packages: `pip install tongsim-sdk unreal-engine-python`. 2. **Configure Environment:** Load your custom environment (e.g., warehouse.blend) or use TongSIM's pre-built assets. Adjust parameters via the Python SDK or Unreal Editor. 3. **Define Agent:** Specify agent type (e.g., wheeled robot, humanoid) and capabilities (sensors, actuators) in the config file. Use the SDK to define custom behaviors. 4. **Run Simulation:** Execute the simulation script with your parameters: `python run_simulation.py --task "pallet_transport" --env "warehouse" --duration 300`. Monitor progress in real-time via the TongSIM dashboard. 5. **Analyze Results:** Use the built-in analytics tools to generate reports. Export data for further analysis in tools like MATLAB or Tableau. Iterate by tweaking parameters and re-running simulations. **Tips for Better Results:** - Start with TongSIM's "Quick Start" templates to validate your setup before customizing. - Use the Python SDK to log custom metrics (e.g., energy consumption, path efficiency) for deeper insights. - For complex tasks, break them into subtasks (e.g., navigation → manipulation → transport) and test each independently. - Leverage TongSIM's "Scenario Editor" to create edge cases (e.g., power outages, sensor failures) for robustness testing.