Hi,

This is my last Project, where I've developed a new technology (CACM-RL) to control Nonlinear and Unstable Robots, like aircrafts, Xcopters, cars, anything, without any mathematical model, because I've applied auto-learning to autodiscover the platform and Optimal Control to obtain the Optimal Controller... obviously.



http://youtu.be/cKHisPFz56U

I've used NXT to develop this demo, but I will like someone knock to my door with a interesting challeng and money.

I hope you like, and I appreciate any support...

That is quite interesting! Very smooth and precise control! Any chance of seeing the source code?

The algorithm is under Patent, but the basic idea is to estimate the vector state (Th, Vth), and look into a Optimal Control Table, the optimal action associated to this state, iteratively.

In this way the NXT computation is very light, because it only has to look into a memory cell addressed by the status vector.

The dificulty is to construct the Optimal Control Table. It's a checkerboard where each state has one action.... the optimal, and the algoritm to construct this table is based in Reinforcement Learning, to avoid in this way to have to work with a math-model.