3d6b73753a
- Add pick_test_tube task: USDC asset repackaging, grasp generation, task config - Add tools: usdc_to_obj.py, repackage_test_tube.py, fix_test_tube_materials.py - Add custom_task_guide.md: full Chinese documentation for creating custom tasks - Add crawled InternDataEngine online docs (23 pages) - Add grasp generation script (gen_tube_grasp.py) and pipeline config
186 lines
5.8 KiB
Markdown
186 lines
5.8 KiB
Markdown
# Source: https://internrobotics.github.io/InternDataEngine-Docs/guides/installation.html
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# Installation [](#installation)
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This guide walks you through setting up InternDataEngine, including cloning the repository, preparing Isaac Sim, downloading assets, and installing dependencies. Follow the steps below to get your simulation environment ready for data generation.
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## Prerequisites [](#prerequisites)
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Before installing InternDataEngine, ensure the following requirements are met:
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| Dependency | Version | Description |
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| NVIDIA Isaac Sim | 4.1.0 (recommended) / 4.2.0 / 4.5.0 | Simulation engine |
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| Python | 3.10+ (recommended 3.10 or 3.11) | Runtime |
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| CUDA | 11.8+ | GPU-accelerated motion planning |
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## Step 1: Clone the Repository [](#step-1-clone-the-repository)
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bash
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```
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git clone https://github.com/InternRobotics/InternDataEngine.git
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cd InternDataEngine
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```
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## Step 2: Prepare Isaac Sim [](#step-2-prepare-isaac-sim)
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InternDataEngine relies on NVIDIA Isaac Sim for physics simulation. Please install it according to the version requirements above. Version **4.1.0 **is recommended.
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## Step 3: Download Assets [](#step-3-download-assets)
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All assets and dependency packages are hosted on HuggingFace: [InternDataAssets](https://huggingface.co/datasets/InternRobotics/InternData-A1/tree/main/InternDataAssets)
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Three components need to be downloaded:
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text
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```
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InternDataAssets/
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├── assets/ # Scene and task assets
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├── curobo/ # CuRobo motion planning library
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└── panda_drake/ # Drake kinematics library
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```
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### 3.1 Scene Assets [](#_3-1-scene-assets)
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**Required assets **(needed for all tasks):
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- `background_textures `, `envmap_lib `, `floor_textures `, `table_textures `— Domain Randomization materials
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- `table0 `, `table_info.json `— Table scene
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>
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The Randomization material directories contain many files. For quick testing, you can download just a few samples from each directory.
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**Robot models **(choose as needed):
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- `lift2 `, `franka `, `frankarobotiq `, `split_aloha_mid_360 `, `G1_120s `
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**Task assets **(choose as needed):
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- `basic `, `art `, `long_horizon `, `pick_and_place `
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We provide a download script at `scripts/download_assets.sh `for selective downloading:
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bash
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```
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bash scripts/download_assets.sh [OPTIONS]
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```
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| Option | Description |
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| `--min ` | Download only required scene assets (for quick testing) |
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| `--full ` | Download all scene assets including all robots and tasks (default) |
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| `--with-curobo ` | Also download the CuRobo package |
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| `--with-drake ` | Also download the panda_drake package |
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| `--local-dir DIR ` | Specify download directory (default: current directory) |
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bash
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```
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# Minimum assets + CuRobo + panda_drake
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bash scripts/download_assets.sh --min --with-curobo --with-drake
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# Full download (~200GB)
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bash scripts/download_assets.sh --full --with-curobo --with-drake
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```
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Hint
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The full asset collection is large, so download selectively based on your needs. Because the background, floor, and table textures contain many images for domain randomization, if your download speed is slow or disk space is limited, you can download only a small subset (e.g., 10+ images per directory) for debugging.
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### 3.2 CuRobo [](#_3-2-curobo)
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If you already have CuRobo installed and don't need to download it via the script above, simply merge the contents of ``[curobo/src/curobo/content](https://huggingface.co/datasets/InternRobotics/InternData-A1/tree/main/InternDataAssets/curobo/src/curobo/content)from HuggingFace into your local `YOUR_CUROBO_PATH/src/curobo/content `(contains robot URDFs and CuRobo configuration files).
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If CuRobo is not yet installed, you can also get the source from [NVlabs/curobo] ( [https://github.com/NVlabs/curobo](https://github.com/NVlabs/curobo)).
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## Step 4: Create Symlinks [](#step-4-create-symlinks)
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bash
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```
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cd InternDataEngine/workflows/simbox
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ln -s YOUR_PATH_TO_ASSETS assets
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ln -s YOUR_PATH_TO_CUROBO curobo
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ln -s YOUR_PATH_TO_PANDA_DRAKE panda_drake
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```
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## Step 5: Install Python Dependencies [](#step-5-install-python-dependencies)
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### Option A: Using Isaac Sim's Built-in Python [](#option-a-using-isaac-sim-s-built-in-python)
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bash
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```
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cd InternDataEngine
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YOUR_PATH_TO_ISAACSIM/python.sh -m pip install --upgrade pip
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YOUR_PATH_TO_ISAACSIM/python.sh -m pip install -r requirements.txt
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```
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### Option B: Using Conda [](#option-b-using-conda)
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bash
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```
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conda create -n banana python=3.10
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conda activate banana
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source YOUR_PATH_TO_ISAACSIM/setup_conda_env.sh
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cd InternDataEngine
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pip install --upgrade pip
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pip install -r requirements.txt
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```
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**Note **: The only difference between the two options is the Python launch command — Option A uses `YOUR_PATH_TO_ISAACSIM/python.sh `, while Option B uses `python `. This documentation uses `YOUR_PATH_TO_ISAACSIM/python.sh `throughout for consistency.
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## Step 6: Install CuRobo [](#step-6-install-curobo)
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Refer to the [CuRobo installation docs](https://curobo.org/get_started/1_install_instructions.html), specifically the **Install for use in Isaac Sim **section, then run:
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bash
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```
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cd InternDataEngine/workflows/simbox/curobo
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YOUR_PATH_TO_ISAACSIM/python.sh -m pip install -e .[isaacsim] --no-build-isolation
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```
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## Troubleshooting [](#troubleshooting)
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### Isaac Sim Not Found [](#isaac-sim-not-found)
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Ensure the `ISAAC_SIM_PATH `environment variable is set correctly:
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bash
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```
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export ISAAC_SIM_PATH=/path/to/isaac-sim
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```
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### CUDA Out of Memory [](#cuda-out-of-memory)
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Reduce the batch size in the configuration, or use a GPU with more VRAM. CuRobo motion planning benefits from larger GPU memory.
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### Import Errors [](#import-errors)
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Ensure all symlinks are set up correctly:
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bash
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```
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ls -la workflows/simbox/assets
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ls -la workflows/simbox/curobo
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ls -la workflows/simbox/panda_drake
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```
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