ROS2 Point Clouds For Autonomous Self Driving Car using PCL. This repository helps you understand and learn usage of point clouds in autonomous vehicles.
It covers the basics of point clouds, including what they are, how they are created, and how they can be represented. The Point Cloud Library (PCL), a popular open-source library for processing point clouds. I learned how to create and run ROS2 nodes, use the PCL (Point Cloud Library) library, perform RTAB mapping (Real-Time Appearance-Based Mapping), and apply segmentation and clustering techniques.
The next few sections focuses on using PCL to process point clouds for autonomous vehicles. We will learn how to filter point clouds, segment point clouds, and cluster point clouds. We will also learn how to use PCL to create 3D maps and to track objects in the environment.
The final section covers the Kitti dataset, a large dataset of 3D lidar data. We will learn how to use the Kitti dataset to train and evaluate object detection algorithms.
Table of Contents
This is repository for the course ROS2 Point Clouds For Autonomous Self Driving Car using PCL availble at Udemy . Complete source code is open sourced.
- Move into your workspace/src folder
cd path/to/ros2_ws/src/
##e.g cd ~/ros2_ws/src/
- Clone the repository in your workspace
git clone https://github.com/roniepatil/ROS2-Point-Cloud-Clustering-and-Segmentation-for-Autonomous-Vehicles.git
- Perform make and build through colcon
cd /path/to/workspace_root/
##e.g ~/ros2_ws/
colcon build
- Source your Workspace in any terminal you open to Run files from this workspace ( which is a basic thing of ROS )
source /path/to/ros2_ws/install/setup.bash
- Make sure kitti data is in ~/ros2_ws/data
- Build Kitti Data Processing and run it
colcon build && ros2 launch point_cloud_processing process_kitti.launch.py
- Run Rviz with config file
ros2 launch point_cloud_processing bring_rviz.launch.py
- Building Point Cloud Maps with RTAB-Map
- Processing Kitti Dataset
Software Based
- Ubuntu 22.04 (LTS)
- ROS2 - Humble
export AMENT_PREFIX_PATH=''
sudo apt install libpcl-dev
sudo apt-get install ros-humble-pcl-ros
sudo apt-get install ros-humble-pcl-conversions
sudo apt install pcl-tools
Extras:
sudo apt install python3-colcon-clean
colcon clean workspace
colcon build
ros2 pkg create --build-type ament_cmake point_cloud_processing
colcon build --packages-select point_cloud_processing
pcl_viewer table_scene.pcd
ros2 run point_cloud_processing pcd_import
ros2 run point_cloud_processing plane_cloud
pcl_viewer -multiview 2 plane.pcd plane_.pcd
EXTRA
sudo apt remove libgazebo11
sudo apt remove libgazebo-dev
sudo apt remove
sudo apt install ros-humble-gazebo-ros-pkgs
sudo apt install ros-humble-rtabmap-ros
sudo apt install python3-opencv
sudo apt install libopencv-dev
ros2 launch turtlebot3_gazebo turtlebot3_world.launch.py
ros2 launch point_cloud_processing rtab_mapping.launch.py
ros2 run teleop_twist_keyboard teleop_twist_keyboard
https://github.com/umtclskn/ros2_kitti_publishers
https://github.com/Deepak3994/Kitti-Dataset/blob/master/raw_data_downloader.sh
https://github.com/introlab/rtabmap_ros/tree/humble-devel/rtabmap_demos/launch
https://github.com/introlab/rtabmap/wiki/Installation#rtab-map-desktop-ubuntu-1804-2004-2204