Processing the LiDAR Point Cloud with PCL

Result

Data 1	Data 2

Pipe Line

Visualization step by step

1. Raw Data

   Data 1	Data 2

2. Filtering

   Data 1	Data 2

3. Segment

   Data 1	Data 2

4. Clustering

   Data 1	Data 2

5. Rendering

   Data 1	Data 2

Workspace

• Ubuntu 16.04
• PCL - v1.7.2
• C++ v14

1. Install and Run docker desktop

   • Install Docker
   • Run docker destkop

2. Pull the image and make the container from kimjw7981/SFND_lidar

   • Check out this page kimjw7981/SFND_lidar Docker Hub
   • Run this command for pull the image and make the container

     docker run -p 6080:80 -v /dev/shm:/dev/shm kimjw7981/sfnd

   • Connect the linux GUI environment with localhost:6080 on your browser

3. Run LX Terminal

4. Execute the following commands in LX Terminal

   sudo apt update -y && sudo apt upgrade -y
   cd ~/SFND_Lidar_Obstacle_Detection
   mkdir build && cd build
   cmake ..
   make
   ./environment

5. Done

   • Take your time to learn the Sensor Fusion Nanodegree Program

Build from Source

PCL Source Github

PCL Mac Compilation Docs