Line Follower using Neural Nets : Part 1 (Generating Data Set)

Neural Networks are convenient when mapping a function which behaves non-linearly. However, for Training and Testing purpose , Data is the most important piece of the puzzle.

The Neural Network Line Follower to be designed uses 8 Line sensing elements where each will return
 1 : Line Detected
 0 : Line Not Detected

So the possible dataset is the combination of 8 binary units arranged in different pattern leading to a total of
            2⁸ =  256 Samples of data.

I wrote the following MATLAB script to create the data for training the Neural Network.

 function [bin,out]=DataGen(m)  

 % Function to Generate Training Data set for training neural network of a  
 % line follower  
 %    
 %     [bin,out]=DataGen(number of inputs)  
 %       
 % It is a good practice to have an even number of input units for the  
 % NN Network to be trained  
 n=(2^m)-1;              
 bin=decimalToBinaryVector(0:n);   
 [p,q]=size(bin);             
 out=zeros(p,1);   
 bLeft=bin(:,1:(q/2));  
 bRight=bin(:,((q/2)+1):end);  
 wL=bi2de(bLeft,'left-msb');  
 wR=bi2de(bRight,'right-msb');  
  for i=1:p  
    if wL(i)>wR(i)  
      out(i)=-1;  
    end   
    if wL(i)<wR(i)  
      out(i)=1;  
    end  
    if wL(i)==wR(i)  
      out(i)=0;  
    end    
  end  
 end  

Here:
         bin holds the binary input sequence of 8 bits    
         out holds the output corresponding to the input bin

Such that:
          if bin=[1 0 0 0 0 0 0 0]  then out = -1      (Line Sensed on far left : Move Left)

          if bin=[0 0 0 0 0 0 1 0]  then out =  1      (Line sensed on right : Move Right)

          if bin=[0 0 1 0 0 1 0 0]  then out =  0      (Line sensed symetrically : Keep Moving Forward)

For a Neural Network,  0 is pretty much a perfection so it allocates a really small value (~0) such that it can be considered as zero.

From the script above with 8 as a parameter via the following syntax:

           [bin,out]=DataGen(8);

we get:

           bin = 256 X 8 Input Data Matrix

           out = 256 X 1 Output Data Matrix

In the screenshot of the varibles, Left Segment shows the input from the sensors while we have the expected output in the blue bounded box on right:

These Data elements are ready to be used as Training Parameters for our Neural Network.
Further Development to be covered by subsequent posts.

Update 7/Sep/16 : Read Part II: Designing Neural Network

Peace Out.

Used:
Matlab 2016a