ril-env is an environment management package designed for robotic control, perception and simulation. It provides an API and programmatic interface to manage state-action flow for both real hardware robots and sensors and their simulation counterparts.
Currently, ril-env supports record-replay of the xArm 7 robotic arm on a single machine, with the option of camera perception running in a seperate thread.
More features will be added soon; see the issues tab under the repository.
Run the following
sudo ip addr add 192.168.1.100/24 dev enp2s0
sudo ip link set enp2s0 up
sudo ip route add 192.168.1.223 dev enp2s0
ril-env is tested on Ubuntu Linux with Python 3.
To get started, first clone the repository.
git clone https://github.com/UCLA-Robot-Intelligence-Lab/ril-env.git
This repository uses the xarm folder from the xArm-Python-Sdk
package. If there are any issues, it is recommended that you do the
following:
First remove the xarm folder. Using the
xArm-Python-Sdk
package, follow the instructions on that repo and install the package
at the root of this repository. Then after installing, move the xarm folder into the
root repository and remove xArm-Python-Sdk.
Create the conda (recommended) environment. Replace rilenv your preferred name for the environment. Run this at the root of your repository:
conda env create -n rilenv -f environment.yml
Finally, set up the package:
pip install -e .
Ensure that the arm is enabled on the machine you will run the relevant script on.
To run both the perception and xArm 7 robotic arm, you can use the joint_script.py script.
To run perception and the robotic arm seperately, you can either run xarm_script.py and camera_script.py seperately.
You can access nearly all of the parameters for the APIs through their respective config dataclasses. Then, when writing or using a script, you simply need to specify what parameters to change and what to change them to when the config() object is being created.