Tuesday, December 16, 2014

OpenCV essentials Review

OpenCV essentials provides a good overview of what sort of applications can be built with 2.4.9 release of OpenCV. There are a few references to what's coming in 3.0 release. According to the official website of OpenCV, 3.0 is to be released at the end of 2014. I like the way that the author has provided a fair description and code for detecting different 2-D feature descriptors in OpenCV. Cascade classification is also covered. The author goes on to describe what can be used as cascade classifiers. Latent SVM has also been included in this description. Tracking, background subtraction using OpenCV is also covered along with code samples.

Machine Learning is also provided in this book along with code samples. Code samples for classifiers such as KNN, Random Forest, SVM are provided.

Interestingly, steps to configure GPU (CUDA), a couple of GPU optimized OpenCV programs using NVIDIA CUDA is also provided.

If you are looking for a decent book for OpenCV with most recent stable release (2.4.9) covered, this is a good buy.

You can purchase it here.

Sunday, December 14, 2014

Programming a simple self driving robot

I had a lot of fun doing CpE 493M: Mobile Robotics this semester. We explored on how to use various sensors and program them to build an autonomous robot that drives straight.

The hardware was pre-built and all we had to do was to program the robot using a MATLAB toolbox. More details on the hardware platform are provided here.

The robot has a bunch of ultra-sonic sensors, IMU sensor, kinect sensor, magnetometer and all the sensors(wheel encoders, bump sensors) in a programmable roomba. The processing power is provided by an 11-inch asus X202e laptop on a Intel i-3 processor.

We were a group of 5 students who were given the task of navigating the hallway of our building at WVU. We wrote a program to drive across the hallway. The hallway wasn't exactly straight. So, even if we did dead-reckoning, the robot would steer into a wall or go out of the path. This is due to uneven friction on the wheels and other factors (such as cracks on the floor tiles).

My primary task was to design the module that would take images from the Kinect Sensor and give the right heading direction (to steer left or right). This data would be provided to a PID controller that controls the heading direction of the robot. The robot has a differential drive mechanism. This way we are able to control the heading direction by changing speeds of the wheels.

This is what the kinect cameras sees:



Then, we filter the red color from the rest of the image:



Then, we apply blob detection on the image, we then filter the blobs and identify the locations of the blobs. The following blob labels, along with their location are obtained:



Then, we obtain a path by drawing 2 lines from the 2 cups from bottom-left and bottom-right and find an intersection point. Its a naive technique, but works well most of the time.





So, we do path correction after every few frames (5 frames). The data is collected at 20-30 frames per second.

We then are able to correct the path of the robot every few seconds. I'm sorry for the shaky video. Here is a video of our robot driving






Monday, September 8, 2014

Getting data from camera in Robot Operating System

I have used webcams in OpenCV before.

However, I came across a situation where I had to stream the webcam data to a ROS (Robot Operating System) topic.

There are bunch of ROS packages on ros.org website. However, when I did a

it gave me errors saying there was no such package found.

All I want to do is grab the data from a webcam and post it to a topic (so that other ROS nodes can read from that topic). I knew it had to be simple

So, I came across this deb package in Ubuntu

Once, I did the above installation all I had to do was


Then, it started publishing data onto /image_raw topic.

Then I could do a


To read the data from the camera published on the topic.

To get a list of topics published to, do a

If you ran the above command, you could infer that the published image stream is of type /sensor_msgs/Image