This project performs 3D segmentation on data obtained from a RGB-D camera.
To run this project, copy "sensor_stick" directory to "src" directory of your catkin workspace (typically "catkin_ws"), then run catkin_make, source devel/setup.bash, then execute "roslaunch sensor_stick robot_spawn.launch".
The original project dataset looks like this:
In the first step, RGB-D point cloud is downsampled using Voxel grid filter.
Then a passthrough filter is used to focus only on area above table (table desk included)
RANSAC is used to perform segmentation around table desktop plane.
The table is extracted as positive segments:
The objects are extracted as negative segments:
In the end, Euclidean clustering utilizing Kd-tree is used to partition object mesh into individual 3D objects and visualized in RViz:
