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Unitree Go2 simulation platform for testing navigation, decision-making and autonomous tasks. (NVIDIA Isaac/ROS2)

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Isaac Sim Unitree Go2 ROS2

Python ROS2 IsaacSim Linux platform

Welcome to the Isaac Sim Unitree Go2 repository! This repository provides a Unitree Go2 quadruped robot simulation, leveraging the Isaac Sim/Isaac Lab framework and integrating seamlessly with a ROS 2 interface. It offers a flexible platform for testing navigation, decision-making, and other autonomous tasks in various scenarios.

go2 navigation - gif warehouse demo - gif

Installation Guide

Step I: Please follow the latest Isaac Lab official documentation to install the Isaac Sim and Isaac Lab.

Step II: Please install ROS2 Humble with the official installation guide.

Step III: Install the prerequisite C extension in the conda environment. reference link

# default conda env for Isaac Lab
conda activate isaaclab      
conda install -c conda-forge libstdcxx-ng

Step IV: Clone this repo to your local directory.

git clone https://github.com/Zhefan-Xu/isaac-go2-ros2.git

Run Unitree Go2 Simulation

To run the simulation, please use the following command:

conda activate isaaclab
python isaac_go2_ros2.py

Once the simulation is loaded, the robot can be teleoperated by the keyboard:

W: Forward, A: Left, S: Backward, D: Right, Z: Left Turn, C: Right Turn.

sim.demo.mp4

ROS2 Topics and Visualization

After launching the simulation, the ROS2 data can be visualized in Rviz2:

rviz2 -d /path/to/isaac-go2-ros2/rviz/go2.rviz

rviz

Here is a categorized list of ROS 2 topics available for the Unitree Go2:

Command and Control

  • /unitree_go2/cmd_vel: Topic to send velocity commands to the robot for motion control.

Front Camera

  • /unitree_go2/front_cam/color_image: Publishes RGB color images captured by the front camera.
  • /unitree_go2/front_cam/depth_image: Publishes depth images from the front camera.
  • /unitree_go2/front_cam/info: Publishes camera information, including intrinsic parameters.

LIDAR

  • /unitree_go2/lidar/point_cloud: Publishes a point cloud generated by the robot's LIDAR sensor.

Odometry and Localization

  • /unitree_go2/odom: Publishes odometry data, including the robot's position, orientation, and velocity.
  • /unitree_go2/pose: Publishes the current pose of the robot in the world frame.

Simulation Environments & settings

The simulation environments and settings can be changed in isaac-go2-ros2/cfg/sim.yaml config file.

Launch different simulation environments

The current implementation contains a few environments which can be found on isaac-go2-ros2/env/sim_env.py, which follows standard Isaac Sim method for importing USD environments. To change the environment, please change the env_name in the config file isaac-go2-ros2/cfg/sim.yaml. Current available environments:

  • warehouse: A simple warehouse environment in Isaac Sim.
  • warehouse-forklifts: A warehouse environment with forklifts.
  • warehouse-shelves: A warehouse environment with shelves.
  • full-warehouse: A full warehouse environment containing everything.
  • obstacle-sparse: A sparse obstacle field environment.
  • obstacle-medium: A medium obstacle field environment.
  • obstacle-dense: A dense obstacle field environment.

Launch multiple robots in the environment

This repository supports running multiple Unitree Go2 robots and the number of robots can by changed by the num_envs parameter in the config file isaac-go2-ros2/cfg/sim.yaml. The following shows an example video.

multipe.robots.mp4

Example Usage

The video shows an example of using this repo with an RL agent to achieve navigation and collision avoidance:

go2.navigation.mp4

Acknowledgement

The Go2 controller is based on the RL controller implemented in go2_omniverse.

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Unitree Go2 simulation platform for testing navigation, decision-making and autonomous tasks. (NVIDIA Isaac/ROS2)

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