Lidar obstacle detection project

This repo contains code to process Point Cloud Data from LIDAR sensing.

From input pcd, the code:

• Filters down the input pointcloud by reducing resolution and field of view (using pcl library).
• Segments obstacles points from other points (floor/road) using RANSAC algorithm (Random Sample Consensus).
• Clusters obstacles based on points distance, efficient neighbours research with KD-TREE algorithm (balanced tree is guaranteed by ordering points by axis).
• Draws Boxes around each detected clusters.

Dependencies

• PCL
• Eigen
• Boost

Compile and run

Retrieve the source code:

git clone https://github.com/sando92/lidar_obstacle_detection.git

Create the build directory at root and enter it:

cd lidar_obstacle_detection
mkdir build
cd build

Compile the project:

cmake .. && make

And finally run it:

./environment