There and back again

1. Labview can make a quadcopter fly(http://labviewrobotics.wordpress.com/2009/10/06/how-to-build-a-quad-rotor-uav/). This person uses a powerPC 400 MHz processor with a SingleBoardRIO. It requires there to be a compactRIO, hardware that was made by N.I., that costs Rs. 2,35,700. Again, it does work for the ARDUINO as presented at this link http://www.youtube.com/watch?v=RGRhIQneO6w. This is just for the switching of an LED. LIFA(Labview interface for ARDUINO) is a free download that helps you do just that. You need to download the VI package manager and then the LIFA interface. That's just it.
2. French company 'Parrot' has developed an interface between its own on board computer based on an RTOS(which I don't know about yet), and Labview. This means that there is no general case like for the ARDUINO.
3. A real time operating system is used to process real time requests without buffering delays. A RTOS is focused on a narrow set of applications. Therefore, we want to classify it as 'hard' or 'soft' depending on the variabliity in jitter. Jitter is the variability in time taken to accept and complete an application's task. There is something called the R.O.S. the robot operating system developed at Stanford. Have to follow up on what it is.
4. To simulate control of the pentacopter I need to develop an X plane plane simulator version of the pentacopter, that will give linear velocities and positions of the penta in the X plane environment.  This will be supplied as input to the VI file in Labview using the SIL(Standard Interchange Language that is based on SQL and allows for transfer of data between software programs)http://www.sbai2013.ufc.br/pdfs/8127.pdf
Again, you do require to mathematically model the motion equations, to even get the thing onto
5. Something that really gives me hope alot of hope

"The system was simple. Each propeller created a thrust, and the four thrusts combined to counteract gravity. We put together our model using text-based code in an NI LabVIEW MathScriptNode, checked it against the literature, and moved forward to the control code.

We wanted to combine a linear-quadratic regulator (LQR) with a Kalman filter to build a Linear-Quadratic Gaussian (LQG) control algorithm. LabVIEW software provided the tools to make the model linear, create the gain matrices for the LQR controller, help tune the Kalman filter, and implement the LQR and Kalman filter. We wrapped the closed-loop system in a LabVIEW Control Design and Simulation Module Loop, tuned a few parameters, and assembled a full simulation of the system.

Here was the exciting part: By using the LabVIEW toolchain, we had the opportunity to reuse the work we did modeling and developing the control algorithm to create the deployed system. We moved the simulation code to the real-time processor of the NI Single-Board RIO and replaced the model of the quadcopter with real I/O. And, with a little tuning, we had a flying robot."http://zone.ni.com/devzone/cda/pub/p/id/1012

6.http://www.sbai2013.ufc.br/pdfs/7920.pdf describes in a relatively simpler method, the idea of motion of a quadcopter, it's simpler because the author does not just put a couple of results and graphs and actually goes through with solving the equations.

7. I spoke to my good friend Vidya, who promised to teach me something about Kalman filters so that I can understand how and when to use it in the project. This is a long term thing. 

Current goals==

1. Finish the motion equations.

2. Finish the simulation using SIL  SIMULINK/X-Plane or SIL NI LABVIEW/X- Plane

Finish the above by January's end. 

Okay even if I do get the control  loops ready, will there be enough memory on board the ARDUINO ATMEGA2560 board to do those computations for attitude, the extended kalman filter etc.!!!!