Isaac Sim Automator
Contents
Isaac Sim Automator
The Isaac Sim Automator tool automates the deployment of Isaac Sim to public clouds, enabling efficient and scalable simulations.
Installation
Installing Docker
Ensure Docker is installed on your system for container management. For installation guidance, see Docker Installation.
Obtaining NGC API Key
Obtain an NGC API Key to download Docker images from NVIDIA NGC. This can be done at NGC API Key Setup.
Building the Container
To build the Automator container, use the following command in your project root directory:
./build
This builds and tags the Isaac Sim Automator container as 'isa'.
Usage
Running Automator Commands
You can run the Automator commands in two ways:
- Enter the automator container and run commands inside:
./run
./somecommand
- Or, prepend the command with ./run:
./run ./somecommand <parameters>
Examples include:
./run ./deploy-aws
./run ./destroy my-deployment
Deploying Isaac Sim
Choose the appropriate cloud provider (AWS, GCP, Azure, Alibaba Cloud) and follow the provided steps to deploy Isaac Sim using the automator container.
K-Scale Sim Library
The K-Scale Sim Library is built atop Isaac Gym for simulating Stompy, providing interfaces for defined tasks like walking and getting up.
Getting Started with K-Scale Sim Library
Initial Setup
First, clone the K-Scale Sim Library repository and set up the environment:
git clone https://github.com/kscalelabs/sim.git
cd sim
conda create --name kscale-sim-library python=3.8.19
conda activate kscale-sim-library
make install-dev
Installing Dependencies
After setting up the base environment, download and install necessary third-party packages:
wget https://developer.nvidia.com/isaac-gym/IsaacGym_Preview_4_Package.tar.gz
tar -xvf IsaacGym_Preview_4_Package.tar.gz
conda env config vars set ISAACGYM_PATH=`pwd`/isaacgym
conda deactivate
conda activate kscale-sim-library
make install-third-party-external
Running Experiments
Setting Up Experiments
Download and prepare the Stompy model for experiments:
wget https://media.kscale.dev/stompy.tar.gz
tar -xzvf stompy.tar.gz
python sim/scripts/create_fixed_torso.py
export MODEL_DIR=stompy
Training and Evaluation
- For leg-specific tasks:
python sim/humanoid_gym/train.py --task=legs_ppo --num_envs=4096 --headless
- For full-body tasks:
python sim/humanoid_gym/train.py --task=stompy_ppo --num_envs=4096 --headless
Evaluate the models on CPU:
python sim/humanoid_gym/play.py --task=legs_ppo --sim_device=cpu
Troubleshooting
Common issues and solutions for setting up and running Isaac Gym and K-Scale simulations.
git submodule update --init --recursive
export LD_LIBRARY_PATH=PATH_TO_YOUR_ENV/lib:$LD_LIBRARY_PATH
sudo apt-get install vulkan1