In this video I explain how one of my algorithms is able to guide a team of drones to fly in formation requiring minimum information.
Kalman filter is a must tool in every engineer’s toolbox. I have written a course explaining in a detailed and comprehensive way all the steps involved in the Kalman filter algorithm and its actual implementation. In particular, I have focused on examples and problems very common in drones. The Home with lessons covering up to the Discrete linear Kalman filter are available.
My university has written a small reportage about my thesis. It is quite illustrative and I am quite happy with it, they have put simple words and made my thesis understandable to non-technical people.
If you are more interested in how my robots behave in one of the key points of my thesis, I prepared the following video time ago :P.
I have written an intuitive flight simulator in Python for controlling quadcopters. In particular, you can try the Formation Control algorithms from my thesis, or to learn how to control the altitude and attitude of one these machines.
I have added a new lesson in the Artificial Intelligence for Mobile Robots course. This time I show, mathematically and with actual code, how to emulate the behavior of fish schools or flocking birds.
My guide about how to build your own bungee launcher. Basically you can throw whatever you want, I find it useful for my fanjet.