Skip to content

The IAAC GitHub Organization unifies robotics and design with templates, hardware drivers (cameras, LiDAR, ROS), and support for robotic arms, mobile robots, and drones. It includes tools for 3D reconstruction, navigation, and Python libraries for vision and machine learning, plus tutorials on Linux, Docker, and ROS.

Notifications You must be signed in to change notification settings

MRAC-IAAC/IAAC-libraries-tools

Repository files navigation

IAAC-libraries-tools

Author: Shu Xiao

The IAAC GitHub Organization is a unified repository ecosystem for interdisciplinary collaboration in robotics, computer vision, and design. It includes standardized repository templates, drivers for cameras (ZED Mini, Kinect Azure, etc.), LiDARs (RPLIDAR, Livox), and ROS integration. Resources support robotic platforms like ARM robots (offline, online, and real-time control), TurtleBots, Husky A100, and drones. Key applications include 3D reconstruction, navigation, and Python libraries for computer vision, machine learning, and point cloud processing. Comprehensive tutorials cover Linux, Docker, ROS, and virtual environments. This platform fosters innovation and efficiency, advancing IAAC’s cutting-edge research and development initiatives.

🧑‍🎓 What are you looking for?

This page outlines six essential modules developed at IAAC that form the backbone of our robotics ecosystem:

  • IAAC-templates
  • IAAC-robots
  • IAAC-hardware-drivers
  • IAAC-applications
  • IAAC-codebase
  • IAAC-tutorials

These six modules together provide a comprehensive framework for building, deploying, and managing robotic systems. They encompass all aspects of robotics development, from hardware integration to advanced software tools, helping users design and implement cutting-edge robotics applications efficiently and effectively.

🌱 Getting Started

Before diving into the resources, take a moment to familiarize yourself with the structure of this page. Understanding the layout will help you quickly find the materials and tools you need to get started with your project.

The page is organized into clearly defined sections, each designed to guide you through different stages of the learning process, from initial setup to advanced topics. Once you're familiar with the structure, navigating to the relevant resources will be faster and more efficient, ensuring you make the most of the available content.

📂 Each Module includes:

  • What is this about?
  • Where it can be used?
  • Why to use it?
  • How to use it?

Further Reading: Each module provides in-depth information about its purpose, applications, and step-by-step instructions on how to use it. For even more detailed guidance, you can explore the links to relevant resources provided on each module's page.

🗃️ Lessons

Module About What's in this module Linked Module
00 IAAC-templates Introduction of how to the template. Templates Link
01 IAAC-robots This module focuses on various robotic platforms available for use. Includes different control mechanisms and configurations. - Robotic Arm
- Mobile Robot
- Drone
Link
02 IAAC-hardware-drivers This module covers the integration of sensors and hardware necessary for robotic systems to perceive and interact with their environments. - Camera
- Lidar
Link
03 IAAC-applications This module focuses on the various robotic applications that can be developed using the IAAC framework. - 3D Reconstruction
- Navigation
Link
04 IAAC-codebase The IAAC_Codebase module provides a collection of software tools, libraries, and frameworks essential for developing robotic applications. - Computer Vision-Python
- Machine Learning
Link
05 IAAC-tutorials This module offers comprehensive educational resources for getting started and mastering the robotics ecosystem. - Linux
- Docker
- Virtual Environment
- Ros
Link

🎒 Most recent updated Curricula

Our team updated our curricula! Check out:

About

The IAAC GitHub Organization unifies robotics and design with templates, hardware drivers (cameras, LiDAR, ROS), and support for robotic arms, mobile robots, and drones. It includes tools for 3D reconstruction, navigation, and Python libraries for vision and machine learning, plus tutorials on Linux, Docker, and ROS.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 2

  •  
  •