This repository is based on the original one by MacAllister Higgins (https://github.com/mjshiggins/ros-examples) ,but provides HSR colorization of the PointCloud or code the encoding with height, density and intensity (Colour visualisation corresponds to the LiDAR values)

This is a standard ROS catkin-ized workspace. Don't know what that means? Check out a great intro on ROS here or head on over to Udacity to sign up for the Robotics or Self-Driving Car Engineer Nanodegree.

There's currently only one node for processing LIDAR data. Use "catkin_make" in the root of this repo to build the lidar node, and run with rosrun lidar lidar_node after installing PCL and ROS (Indigo, preferably).

If you've downloaded any of the datasets for the challenge, you can start using the data with these nodes immediately by running rosbag play -l name-of-file.bag. The "-l" keeps the bag file playing on repeat so that you can keep working on your algorithm without having to mess with the data playback.