ROS Programming: Building Powerful Robots

Implementing an SVM-ROS application

Following shows the aim of this project.

In this application we are going to classify a sensor data in three ways. The sensor values are assumed to be in between 0 to 30,000 and we are having a dataset which is having the sensor value mapping. For example, for a sensor value, you can assign the value belongs to 1, 2, or 3. To test the SVM, we are making another ROS node called virtual sensor node, which can publish value in between 0 to 30000. The trained SVM model can able to classify the virtual sensor value. This method can be adopted for any kind of sensors for classifying its data.

Before embedding SVM in ROS, here's some basic code in Python using sklearn to implement SVM.

The first thing is importing ...