I'm pleased with Neko's code so far, it's very well-organized. The random walk is my best yet so I'll explain it for the sake of anyone who doesn't know how to read code, but would like a little puzzle to try it out.
This a screenshot of one of the functions in my program: randomWalk(). I tell the function to repeat infinitely with two parameters: the maximum distance the brush should jump, and the time to pause after each iteration. My current parameters are 50 steps and 500 milliseconds, so when the computer reads the instruction randomWalk(50, 500) it will run this piece of code with the variables jump and del set to 50 steps and 500ms, respectively.
This function uses randomness in two ways: it randomly picks one of the six motors, then it randomly picks the number of steps for that motor to move.
Reading live data as scrolling lines of serial output can be quite meditative. I just disabled the motors and moved the brush around the canvas by hand, allowing my own neural network to get a sense of how the sensor data changes while drawing different shapes and lines. As a stepping-stone to a Kalman filter, I'll now try writing a complementary fiter to combine accelerometer and gyroscope data and determine how the arm is moving.