Category Archives: ROS

RGBD PCL point cloud from Stereo vision with ROS and OpenCV

In my other tutorial, I showed you how to calibrate you stereo camera. After Calibration, we can get disparity map and  RGBD PCL point cloud from our stereo camera cool huh 🙂

1)Save the following text under “stereo_usb_cam_stream_publisher.launch

2) Then run the following node to publish both cameras and camera info (calibration matrix)

3) Run the following to rectify image and compute the disparity map:

Super important: If you have USB cam with some delays you should add the following “_approximate_sync:=true”

4) Let’s view everything:

Super important: If you have USB cam with some delays you should add the following “_approximate_sync:=True _queue_size:=10”

5) Running rqt graph should give you the following:

6) Run the to configure the matching algorithm parameter:

7) PCL pointcloud in RVIZ

Stereo Camera Calibration with ROS and OpenCV

In this tutorial, I’m gonna show you stereo camera calibration with ROS and OpenCV. So you need a pair of cameras, I bought a pair of this USB webcam which is okay for this task.

1)Save the following text under “stereo_usb_cam_stream_publisher.launch

2)Then run the following node to publish both cameras.

3)Now call the calibration node:

Super important:

If you have USB cam with some delays you should add the following “–no-service-check –approximate=0.1”

4)Pose the chess board in different position, and then click on the calibrate and save button.

5) The result gonna be store at /tmp/calibrationdata.tar.gz. Unzip the file and save it under “/home/<username>/.ros/stereo_camera_info

Connecting PS4 Controller dualshock via Bluetooth in Ubuntu

PS4 controllers work out of the box in Ubuntu with USB cable but I was looking for a way to get it work via Bluetooth as well. After installing a couple of packages I found “ds4drv”.
To install it:

Then you have to either add the user to the list of root user or simply run it with sudo:

Now hold ps button and share button on the controller and you should see the following in your terminal:

To check the button and see if everything is okay jut install jstest-gtk

A GUI ROS-package for cropping pcl pointcloud with dynamic reconfigure

This ROS package enables you to crop the scene from Kinect (input topic type: PCL pointcloud). You can even enable fitting a plane to remove the ground from the scene and by adjusting correct parameter you can get the desired object from the scene. code available on my Github.

White dots are original scene and rgb dots are from the cropped cloud. Values for the volume of cuboid are coming from sliders.

Car Detection Using Single Shot MultiBox Detector (SSD Convolutional Neural Network) in ROS Using Caffe

This work is similar to the previous work here, but this time I used Single Shot MultiBox Detector (SSD) for car detection. Installation is similar, clone the  SSD Caffe:

add the following lines to your Makefile.config

and build it:

used video_stream_opencv to stream your video:

download the trained model from here and put them in the model directory.

In my ssd.launch, I have changed my trained network into:

Now run the following to open rviz:

in the rviz, go to add a panel, and add integrated viewer>ImageViewrPlugin.

Now correct the topic in the added panel and you should see detected cars:

How to create octomap tree from mesh

I was looking for a way to create an octomap tree from arbitrary mesh file. Well at first I tried to convert my data into PCL pointcloud and then convert them into an octomap tree. But the problem was, for instance when you a cuboid mesh, you only have 8 vertex, which gives you 8 point and the walls between them won’t appear in the final octomap tree. So I found the following solution:

1) First, download the latest version of binvox from (more about binvox, source code available here or you can try this)
2) Convert you mesh file into binvox file i.e

3) grab the binvox2bt.cpp from octomap at GitHub and compile it, then

4) visualize the bt file install octovis:


mesh file (Dude.ply).

octomap bt file (

The sample file can be downloaded at Dude.ply,


Car Detection Using Fast Region-based Convolutional Networks (R-CNN) in ROS with Caffe

To run this, you need to install Fast-RCNN and Autoware. Just in case you got error regarding hd5f when making Fast-RCNN, add the following lines to your Makefile.config

Now run the following command to start:

if you got an error like :

That means your graphics card is not ready or accessible, in my everytime I suspend my notebook I get that error and I need a restart :/

now you should publish your video stream on the topic “image_raw”, for that purpose I used video_stream_opencv. Here is my launch file:

Now run the following to open rviz:

in the rviz, go to add a panel, and add integrated viewer>ImageViewrPlugin.

Now correct the topic in the added panel and you should see detected cars:

Octomap explanierend

In this tutorial, I explain the concept, probabilistic sensor fusion model and the sensor model used in Octomap library.

related publication: OctoMap: An Efficient Probabilistic 3D Mapping Framework Based on Octrees

1)Octamap Volumetric Model

octree storing free (shaded white) and occupied (black) cells. Image is taken from Ref [1]

2)Probabilistic Sensor Fusion Model

3)Sensor Model for Laser Range Data

Image is taken from Ref [1].


Finding roll, pitch yaw from 3X3 rotation matrix with Eigen


Roll, pitch, yaw using Eigen and KDL Frame


From Eigen documentation:

If you are working with OpenGL 4×4 matrices then Affine3f and Affine3d are what you want.
Since Eigen defaults to column-major storage, you can directly use the Transform::data()  method to pass your transformation matrix to OpenGL.

construct a Transform:

or like this:

But note that unfortunately, because of how C++ works, you can not do this:

and with KDL Frame: