🚀 AstroViz 🚀

AstroViz is the ultimate real-time data visualization suite for ROS 2 robotic missions. Built from the ground up for flexibility, clarity, and performance, AstroViz empowers roboticists, engineers, and field operators with a unified interface to monitor, control, and debug complex systems in real-time.

• 🌍 All-in-one visualization: From GPS and LiDAR to camera feeds, robot state, and motor health, AstroViz integrates multiple views into a cohesive and modern GUI.
• ⚡ High-performance: Docker-based deployment with GPU support ensures smooth operation even in data-intensive environments.
• 🛰️ Field-proven: Whether you’re launching autonomous vehicles, drones, or ground robots, AstroViz is your visual command center.

💡 Looking for a ROS 2 tool that goes beyond raw data and helps you make real-time decisions in the field? AstroViz is built for that.

Visual Overview

DASHBOARD VIEWER

For a detailed view of all implemented windows, see: windows implemented

Table of Contents

1. Get Started
   • Prerequisites
   • Installation
     • Clone the Repository
     • Build Using Docker
     • Run the Docker Container
2. Usage
   • Node Overview
   • Running Nodes
3. Maintainer
4. License

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Get Started

Prerequisites

To run this package, ensure the following dependencies are installed:

• Git: For version control and repository management.
• Docker: To streamline the environment setup and execution.
• NVIDIA Container Toolkit (if using an NVIDIA GPU): For hardware acceleration.

Installation

Clone the Repository

Start by cloning the repository:

git clone [email protected]:hucebot/astroviz.git

Build Using Docker

This repository includes a pre-configured Docker setup for easy deployment. To build the Docker image:

1. Navigate to the docker directory:

   cd astroviz/docker

2. Run the build script:

   sh build.sh

   This will create a Docker image named astroviz.

Run the Docker Container

Once built, launch the container using:

sh run.sh

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Usage

Node Overview

This package nodes that are designed to facilitate teleoperation and visualization of data. Each node serves a specific purpose in the teleoperation workflow:

• gpsmap_viewer: Visualizes GPS data on a map.
• camera_viewer: Displays camera feed from the robot.
• imu_viewer: Visualizes IMU data.
• lidar_viewer: Visualizes LiDAR data.
• teleoperation_viewer: Provides a GUI for teleoperation control.
• dashboard_viewer: A comprehensive dashboard that integrates various data streams and provides a unified interface for monitoring and control.
• plot_viewer: Displays real-time plots of various data streams.
• grid_map_viewer: Visualizes grid map data for navigation and planning.
• robot_state_viewer: Displays the current state of the robot related to the joint positions and transformations.
• motor_state_viewer: Monitors and visualizes the state of the robot's motors, including temperature and voltage readings.
• fpv_viewer: First-person view from the robot's perspective using 3d camera data and processing the point cloud as an image.
• record_manager_viewer: Manages and visualizes recording sessions, allowing users to start, stop, and review recordings.

Running Nodes

To run the nodes, you can use the following command:

ros2 run astroviz <node_name>

Replace <node_name> with the name of the node you wish to run, such as gps_map_viewer, camera_viewer, etc.

Or if you prefer to run the dashboard viewer, which integrates all functionalities:

ros2 launch astroviz dashboard_launcher.launch.py

For the fpv viewer, use:

ros2 run astroviz fpv_viewer --config /ros2_ws/src/astroviz/config/config.yaml 

Maintainer

This package is maintained by:

Clemente Donoso
Email: [email protected] GitHub: CDonosoK

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License

This project is licensed under the MIT. See the LICENSE file for details.

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Contributions and feedback are welcome! If you encounter any issues or have suggestions for improvements, feel free to open an issue or submit a pull request.