Exploring NVIDIA Carter Robot in ROS2 Navigation with Isaac Sim and Action Graph
NVIDIA Carter Robot
Introduction:
In the realm of robotics, navigation plays a pivotal role in enabling machines to traverse environments effectively. NVIDIA, a pioneer in AI and robotics technology, offers a powerful solution through their Carter robot platform, integrated with ROS2 (Robot Operating System 2) and Isaac Sim. In this blog post, we’ll delve into the intricacies of ROS2 navigation with NVIDIA Carter, leveraging the capabilities of Isaac Sim’s Action Graph for enhanced performance and efficiency.
Understanding ROS2 Navigation:
ROS2, the successor to ROS, is a flexible framework for building robotic systems. It provides a wealth of tools and libraries for various robotics tasks, including navigation. Navigation in ROS2 involves mapping the environment, localization of the robot within that map, and path planning to navigate from one point to another while avoiding obstacles.
Introducing NVIDIA Carter:
NVIDIA Carter is a versatile robot platform designed for research and development in robotics. It comes equipped with powerful hardware and software components, making it an ideal platform for experimenting with advanced navigation algorithms and techniques.
The Role of Isaac Sim:
Isaac Sim, NVIDIA’s simulation platform, provides a realistic virtual environment for testing and validating robotic algorithms. It offers high-fidelity physics simulation and realistic sensor models, allowing developers to train and deploy algorithms in simulation before deploying them on physical robots.
Getting Started:
To get started with ROS2 navigation in NVIDIA Carter using Isaac Sim and Action Graph, follow these steps:
- Launch Isaac Sim and create a simulation environment that resembles your target deployment environment.
- Connect the action graph for sensor and other information.
- Design and implement navigation behaviors using the Action Graph editor in Isaac Sim.
- Launch ros2 navigation node.
- Monitoring and analyzing the ROS2 node and Isaac Sim action graph using rqt graph.
Launch Isaac Sim and create a simulation environment that resembles your target deployment environment.
Carter robot setup
Action graph for navigation stack 2
Navigation action graph
- Differential Controller
- ros2 sub twist
- Articulation controller
- ros2 publish transform tree
- ros2 publish raw transform tree
- Isaac read lidar beam node
- ros2 publisher laser scan
- ros2 publish odometry
- Isaac compute odometry node
The action graph required for the ROS2 navigation stack in Isaac Sim is crucial for orchestrating robot movement, obstacle avoidance, and path planning within simulated environments.
After connecting the action graph in Isaac Sim, open the terminal and execute the command ‘ros2 topic list’ to observe the available ROS2 topics and their respective interactions within the simulation environment.
The output in terminal
Action graph topics in terminal
Design and implement navigation behaviors using the Action Graph editor in Isaac Sim.
Navigation
Install ros2 navigation stack
sudo apt install ros-humble-nav2-bringup
After installing the ROS2 navigation bringup package, launch the navigation system from the terminal using the appropriate launch command to initiate the navigation functionalities within the ROS2 framework.
ros2 launch bringup_launch.py use_sim_time:=True autostart:=True map:=//Home/maps/carter_warehouse_navigation.yaml
To launch the navigation system in ROS2, you typically use a launch file. The exact command can vary depending on your setup and launch file configurations. However, a common approach is to use the ros2 launch command followed by the package name and launch file.
Isaac sim and navigation
rqt graph
Utilize the ‘rqt graph’ tool for visualization, allowing for clear and insightful representation of the ROS (Robot Operating System) graph structure and message flow within the robotic system.
rqt
Conclusion: In conclusion, NVIDIA Carter combined with ROS2 and Isaac Sim offers a powerful platform for developing and testing navigation algorithms for robotic systems. By leveraging the capabilities of Isaac Sim’s Action Graph, developers can design sophisticated navigation behaviors that enable robots to navigate complex environments autonomously. Whether you’re a researcher, student, or robotics enthusiast, exploring ROS2 navigation with NVIDIA Carter opens up a world of possibilities for building intelligent and autonomous robotic systems.