Omniverse Isaac Gym Reinforcement Learning Environments for Isaac Sim

Installation

Follow the Isaac Sim documentation to install the latest Isaac Sim release.

Once installed, this repository can be used as a python module, omniisaacgymenvs, with the python executable provided in Isaac Sim.

To install omniisaacgymenvs, first clone this repository:

git clone https://github.com/NVIDIA-Omniverse/OmniIsaacGymEnvs.git

Once cloned, locate the python executable in Isaac Sim. By default, this should be python.sh. We will refer to this path as PYTHON_PATH.

To set a PYTHON_PATH variable in the terminal that links to the python executable, we can run a command that resembles the following. Make sure to update the paths to your local path.

For Linux: alias PYTHON_PATH=~/.local/share/ov/pkg/isaac_sim-*/python.sh
For Windows: doskey PYTHON_PATH=C:\Users\user\AppData\Local\ov\pkg\isaac_sim-*\python.bat $*

Install omniisaacgymenvs as a python module for PYTHON_PATH:

PYTHON_PATH -m pip install -e .

Running the testing task

PYTHON_PATH scripts/random_policy.py task=TestModule num_envs=1

Process of the task

The task is used to test if the closed chain robot will be simulated normally in Omniverse Isaac Gym. The total episode length is 1000. At the first episode, the robot will be reset to its initial pose with 0 velocity for every DoF. For the first 100 timsteps, no joint position targets are set, so ideally the robot should stay still for a while. For the rest of the timesteps, a random DoF position target (directly from the actor network output, inside the range of [-1, 1]) will be set, and ideally the robot will move the joints to the target.