Frustrating by all the new single board computers boasting power, speed, RAM, awards, yet prove to be incomplete power hogs that run very slowly when real life sensors are included? Frustrated by poor documentation and myriad of scattered wiki links and forums? The usual response to this criticism is education - you'll learn. I think the main education has been how to sell and hype. Maybe they'll be knighted next year.
That said, one thing very enticing with new boards is the ability to program your project in Python. Even better, it would be nice to program in Octave! Octave is the GNU version of basic Matlab, arguably the best language for engineering and feedback control systems - absolutely perfect for robotics and maker projects. Clean concise programming and vector math! Every engineering student and professional knows what I'm talking about.
I'm not an adafruit representative by any means. I am a customer impressed by Adafruit's ability to pick the right component or sensor and integrate it with a simple to use breakout board at a very reasonable price, cheaper than sparkfun. Now adafruit claims to be engineer, but I've mostly seen selling and hacking. So here's an engineering challenge: design the Adaboard - a microcontroller or single board computer module using an off-the-shelf chip with at least 12 native ADCs!!! (at least 12bit), 12 or more PWM, 36 or more digital I/O, at least 2 SPI, two I2C, 4 hardware serial, ethernet, etc., programmable in Octave, Matlab, or at least Python, for $45 USD. So basically something similar to the Arduino Due, however programmable in a much more powerful and more popular language without boring low-level register instructions. So in other words, a basic line to read an ADC on pin 11 would read like this: volt = readadc(12);
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The point of this thread is to bring awareness to the possibility of a new 32bit microcontroller programmable in Octave or Python. Make yourself heard here if interested: http://forums.adafruit.com/viewtopic.php?f=4&t=35959
Latest exchanges reproduced here:
"westfw wrote": can you place a lower limit on the amount of RAM needed to do the sorts of calculations you had in mind? Just from a data array point of view. When you start talking about languages with built-in matrix and vector support, I think "large amounts of data."
Matrix/vector programming does not necessarily mean large data sets. Here, it means very clean, concise, highly legible programming. For example, the Kalman Gain Matrix shown below involves several matrix multiplications, inversion, and transpose (denoted with apostrophe).
K = Pp * H' * inv(H * Pp * H' + R);
Let's not worry about the definition of the Kalman Gain Matrix. The point here is this... imagine implementing the equation above in C or C++ language - it'd be very messy. Each term above could be a 2x2 matrix, 6x6, or more. In Matlab or Octave, the program expression is literally the above equation. I literally copied it from one my programs. No for-loops, no while-loops, no subroutine calls. The python version is not as elegant, but still better than C or C++ :
K = Pp * H.T * linalg.inv(H * Pp * H.T + R);
"westfw wrote:" It would be EXTREMELY useful to eliminate, say, any board with less than 640k of RAM, for example ("640k isn't enough for anyone to do anything." (someone younger than Bill Gates))
So in terms of ram, assuming each term in the K equation is a 6x6 matrix (36 elements, 8 bytes per element, 288 RAM), the total ram required is 1,728 RAM (based on 6 terms, 288 RAM each) - tiny compared to Arduino Due's 96,000 RAM.
Can python or Octave fit on the Arduino Due? I can't say for sure, but I know the leaflabs people successfully ran a watered-down version of Python called pyMite on their Maple board (32bit, 20KB RAM, 120KB flash). pyMite does not support matrix math, but I can't imagine that matrix addition, multiplication, transpose and division would require much more flash.