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https://github.com/methyldragon/ros-tutorials

Tutorials and starter code for the Robot Operating System (ROS) framework (Featuring ROS 1 and 2!) 🤖🔥🐲
https://github.com/methyldragon/ros-tutorials

cpp python3 references robot-operating-system robotics ros ros1 ros2 syntax tutorial tutorials

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Tutorials and starter code for the Robot Operating System (ROS) framework (Featuring ROS 1 and 2!) 🤖🔥🐲

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README

          

# ROS Tutorials

I've compiled a whole bunch of comprehensive tutorials and starter code templates for the **Robot Operating System** (ROS), for both **ROS 1** and **ROS 2**!

Most of these can be read through in under an hour, and they're pitched at the beginner to intermediate level. But most importantly, they're **designed to be CTRL-F-able!**

## Pre-Requisites

It will definitely help to brush up on [Python](https://github.com/methylDragon/coding-notes/tree/master/Python%203) and [C++]().

As well as [Linux]() to be able to follow along with the tutorial.

## Support my efforts!

[![Yeah! Buy the DRAGON a COFFEE!](./assets/COFFEE%20BUTTON%20%E3%83%BE(%C2%B0%E2%88%87%C2%B0%5E).png)](https://www.buymeacoffee.com/methylDragon)

[Or leave a tip! ヾ(°∇°*)](https://www.paypal.me/methylDragon)

## Further Reading

After reading up on the ROS tutorials, you can do some further reading!

### Robotic Manipulator Planning with MoveIt!

![1563793456590](assets/1563793456590.png)

> The MoveIt! project is a ROS package that helps with motion planning for robotic manipulators. As such, it is especially useful for working with and planning for arms!

### Point Cloud Library Integration with ROS

![CylinderSegmentation.gif](assets/CylinderSegmentationFast.gif)

> The **Point Cloud Library** (or **PCL**) is a **large scale, open project [1]** for 2D/3D image and point cloud processing. The PCL framework contains numerous state-of-the art algorithms including filtering, feature estimation, surface reconstruction, registration, model fitting and segmentation. These algorithms can be used, for example, to filter outliers from noisy data, stitch 3D point clouds together, segment relevant parts of a scene, extract keypoints and compute descriptors to recognize objects in the world based on their geometric appearance, and create surfaces from point clouds and visualize them -- to name a few.

### Sensor Fusion with ROS

[![Click to watch video!](assets/youtube_thumbnail.png)](https://youtu.be/5vZOvISwT94)

> The robot_localisation package in ROS is a very useful package for fusing any number of sensors using various flavours of Kalman Filters!

## Credits

All credits and sources are listed inside the tutorials and references themselves.

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