Rover Autonomous Land Vehicle in a Neural Network

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                    Machine Perception and Cognitive Robotics Laboratory
                        Center for Complex Systems and Brain Sciences
                                Florida Atlantic University

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##Info

    This is the second version of the RALVINN code. It uses OpenCV to read the images from
    the BrookStone Rover instead of PyGame. 

##Current Status

    This is a work in progress by the members of the FAU Machine Perception Club. You may 
    encounter bugs and other issues when running this code. 

##Getting Started with RALVINN.

    Before running the code you will need to make sure that the following python packages 
    have been installed

    1)OpenCV 3.0
    2)PyPNG
    3)PyQrCode and QRTools
    4)PyGame
    5)cStringIO

##How to connect to BrookStone Rover.

    1)Open your WIFI settings. 
    2)Finds the Rover SSID, it usually starts with Rover_ROVERID.
    3)Connect the SSID ID. The green LED light on the Rover will stop flashing once 
    a connection has been established.

##How to create a QR Code. To create a QR code you will need to run CreateQRCode. This python script creates a qr code with whatever command you give it.

##How does the BrookStone Rover Read QR Codes? Withing the RoverPylot script there is method called refresh_video_feed. That scripts saves the image array into a file named "qr.ong". Then when the rover sees the QR in the feed the function qr_tools uses the built in function decoder to decode the meaning of the QR code. ##Getting started with the BrookStone Rover 2.0. Run MPCR_RALVINN.py. If everything has been installed correctly a window will pop up showing the Rover video feed. Use the keyboard commands below to move the BrookStone Rover 2.0

##How to control the BrookStone Rover 2.0: W - Forward S - Back D - Right A - LEFT U - Toggle Infrared Night Vision. J - Camera Up K - Camera Down I - Toggle Lights Space bar - Take a pic.

##To Do List 1)Give the BrookStone Rover 2.0 the ability to read QR codes. 2)Apply Reinforcement Learning using the QR codes to create positive and negative feedback.
3)Add more helper functions. 4)Fix Bugs! * Corrupt JPEG DATA - Only seen on Linux system. Will need to investigate. Does not affect Rover.