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https://github.com/iamlab-cmu/isaacgym-utils

Wrappers and utilities for Nvidia IsaacGym
https://github.com/iamlab-cmu/isaacgym-utils

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Wrappers and utilities for Nvidia IsaacGym

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# isaacgym-utils

This repo contains wrappers and utilities for `isaacgym`



Supported version of Isaac Gym: 1.0rc2



Supported `up_axis` mode: `z` (`UP_AXIS_Z` in the Isaac Gym documentation)



## Installation



### Install IsaacGym



Install IsaacGym from [Nvidia](https://developer.nvidia.com/isaac-gym)



This library supports the latest IsaacGym version - `1.0.preview2`.

It will not work with older versions.



### Install isaacgym-utils



Install `isaacgym-utils`:



```bash

git clone [email protected]:iamlab-cmu/isaacgym-utils.git

pip install -e isaacgym-utils

```



By default, only "core" dependencies are installed. To install dependencies needed for optional `isaagym-utils` capabilities, modify the above `pip install` command to indicate the desired optional capability. The following commands will also install the core dependencies.



Reinforcement learning (RL):

```

pip install -e isaacgym-utils[rl]

```



Parallel IsaacGym instances via Ray:

```

pip install -e isaacgym-utils[ray]

```



Multiple capabilities can be specified:

```

pip install -e isaacgym-utils[ray,rl]

```



Or, install all capabilities:

```

pip install -e isaacgym-utils[all]

```



## Running examples



Examples scripts can be found in `isaacgym-utils/examples/`.

These scripts need to be run at the root level of `isaacgym-utils`:



```bash

cd isaacgym-utils

python examples/run_franka.py

```



Each example script has a corresponding config file in `cfg/` that can be used to change object properties like friction.



### Running with Ray



[Ray](https://github.com/ray-project/ray) is a fast and simple framework for building and running distributed applications.



Requires the `[ray]` or `[all]` installation of `isaacgym-utils`.



See `isaacgym_utils/examples/franka_pick_block_ray.py` for an example of running multiple `isaacgym` instances in parallel using Ray.



### RL environment



Requires the `[rl]` or `[all]` installation of `isaacgym-utils`.



See `isaacgym_utils/rl/vec_env.py` for the abstract Vec Env base class that is used for RL.

It contains definitions of methods that are expected to be overwritten by a child class for a specific RL environment.



See `isaacgym_utils/rl/franka_vec_env.py` for an example of an RL env with a Franka robot using joint control, variable impedance control, and hybrid force-position control.



See `examples/run_franka_rl_vec_env.py` for an example of running the RL environment, and refer to the corresponding config for changing various aspects of the environment (e.g. in the YAML config, the fields under `franka.action` determine what type of action space is used).



For new tasks and control schemes, you can make a new class that inherits `GymVecEnv` (or `GymFrankaVecEnv` if using the Franka) and overwrite the appropriate methods.



## Loading external objects

To load external meshes, the meshes need to be wrapped in an URDF file.

See `assets/ycb` for some examples.

The script `scripts/mesh_to_urdf.py` can help make these URDFs, but using it is not necessary.

Then, they can be loaded via `GymURDFAsset`.

See `GymFrankaBlockVecEnv._setup_single_env_gen` in `isaacgym_utils/rl/franka_vec_env.py` for an example.



## Tensor API



To use IsaacGym's Tensor API, set `scene->gym->use_gpu_pipeline: True` in the yaml configs.



This switches `isaacgym-utils`' API to use the Tensor API backend, and you can access the tensors directly using `scene.tensors`.



To directly write values into writable tensors (see IsaacGym docs for more details), instead of relying on `isaacgym-utils`' internal implementations, you should:

1. Write to a tensor in `scene.tensors`

2. Call `scene.register_actor_tensor_to_update` to ensure that the writes are committed during the next simulation step.



## Things to Note



* Attractors can't be used if `use_gpu_pipeline: True`

* If using `physx` and not controlling the an actor with joint PD control, you must set `dof_props->stiffness` to have all `0`'s, otherwise IsaacGym's internal PD control is still in effect, even if you're sending torque commands or using attractors. This is not a problem when using the `flex` backend.

* We only support `scene->gym->up_axis: z` - setting the `up_axis` to `x` or `y` will give unexpected behaviors for camera rendering. This is a bug internal to IsaacGym.

* `flex` w/ backend supports getting point-wise contacts. `physx` backend w/ `use_gpu_pipeline: True` and `use_gpu: True` only supports getting body-wise contacts (summing up all point-wise contacts). Other `physx` configurations do not support getting any contact forces.

* `flex` does not support `use_gpu_pipeline: True`



## Citation



If you use `isaacgym-utils` in a publication, please consider citing the repo:



```

@misc{isaacgym-utils,

title = {IsaacGym Utilities},

year = {2021},

note = {Developed by the CMU Intelligent Autonomous Manipulation Lab},

url={https://github.com/iamlab-cmu/isaacgym-utils},

author = {Liang, Jacky},

}

```