Updated README with usage instructions

README.md

@@ -9,3 +9,16 @@ PCL based ROS package to Detect/Cluster --> Track --> Classify static and dynami
 - Unsupervised k-means clustering based on detected features and refinement using RANSAC
 - Stable tracking (object ID & data association) with an ensemble of Kalman Filters 
 - Robust compared to k-means clustering with mean-flow tracking
+
+### Usage:
+
+Follow the steps below to use this (`multi_object_tracking_lidar`) package:
+
+1. [Create a catkin workspace](http://wiki.ros.org/catkin/Tutorials/create_a_workspace) (if you do not have one setup already). 
+1. Navigate to the `src` folder in your catkin workspace: `cd ~/catkin_ws/src`
+1. Clone this repository: `git clone https://github.com/praveen-palanisamy/multiple-object-tracking-lidar.git`
+1. Compile and build the package: `cd ~/catkin_ws && catkin_make`
+1. Add the catkin workspace to your ROS environment: `source ~/catkin_ws/devel/setup.bash`
+1. Run the `kf_tracker` ROS node in this package: `rosrun multi_object_tracking_lidar kf_tracker`
+
+If all went well, the ROS node should be up and running! As long as you have the point clouds (from LIDAR or other pointcloud generator) published on to the `filtered_cloud` rostopic, you should see outputs from this node published onto the `obj_id`, `cluster_0`, `cluster_1`, …, `cluster_5` topics along with the markers on `viz` topic which you can visualize using RViz.