Well as you can see on the title of the post, I decided to talk a bit more about what I do 3/4 of my day: JAVA, hopefully to share the problems I have everyday will help somebody else and also I'm pretty sure they will also help me.
My whole Java career started 3 years ago just by coincidence, I was in charge of the development of the "brain" of a mobile robot and the best way to have an OS independent software is using Java, so I ended up buying a Java book and started messing around with my computer and Netbeans.
Anyway, to make a long story short I developed two softwares to create the robot's brain, the requirement was that the robot could be able to move from position A to position B making all the decisions by himself in order to avoid obstacles and reach its destination.
To accomplish this goal I decided to use Self Organizing Maps also called Kohonen Networks, a self-organizing artificial neural network that selects the winner neuron by using the euclidean distance.
The learning process for the SOM is to make that different areas of the network can be activated by similar input patterns, and this resembles a lot to the way our brains work when we receive auditory or visual information and different areas of our brain generate the response.
JKam is the name of the software I developed for this task, its goal is to make easier the training process for Kohonen Networks and it has the following features:
My whole Java career started 3 years ago just by coincidence, I was in charge of the development of the "brain" of a mobile robot and the best way to have an OS independent software is using Java, so I ended up buying a Java book and started messing around with my computer and Netbeans.
Anyway, to make a long story short I developed two softwares to create the robot's brain, the requirement was that the robot could be able to move from position A to position B making all the decisions by himself in order to avoid obstacles and reach its destination.
To accomplish this goal I decided to use Self Organizing Maps also called Kohonen Networks, a self-organizing artificial neural network that selects the winner neuron by using the euclidean distance.
The learning process for the SOM is to make that different areas of the network can be activated by similar input patterns, and this resembles a lot to the way our brains work when we receive auditory or visual information and different areas of our brain generate the response.
JKam is the name of the software I developed for this task, its goal is to make easier the training process for Kohonen Networks and it has the following features:
- It allows you to define the structure of the map (Input Neurons, X Neurons and Y Neurons)
- Bubble and Gaussian neighborhood functions
- Exponential, Linear or Inverse Time learning factor functions
- Training variables such as amount of steps, radius, training sets and initial learning factor rate.
- It also allows you to save and re-use training sets and neural networks on an XML format.
I stopped working with this software a couple of years ago but I think it can be pretty useful on different fields so if anyone is interested on using it, just send me an email and I will gladly send you the files.
Well that's it, on the next post I'll talk about the software using a SOM trained with JKam, the brain of the robot: Ferbar.
