Over the course of the past 2-3 weeks I decided to take the plunge of learning a new training algorithm which had quite alot of attention in the academic community but was also well constructed for easier implementation. The work by Peng et al on developing the Continuous Forward Algorithm (CFA) was my subject of attention. The overall premise behind implementing this algorithm was to investigate less memory-intensive machine learning algorithm that will not sacrifice accuracy or robustness. The ability to have a real-time learning system for low-cost electronics (such as the Teensy 3.6 ) has huge implications for the commercialization and affordable access of intelligent drones specifically for developing and even under-developed economies. The far-reaching impact of having technology leveraging efforts of farmers, herders, game rangers, biologists is the next wave of industrialization. This is the essence of this blog. The journey is very exciting and eventual results even mo...

It's amazing how a continuous search at possibilities eventually leads to finding a "needle in a haystack". Introducing the Teensy 3.6 development. It a 32-bit Cortex M4 ARM core with (FPU) at a 1/6th of the price of the Pixhawk (The Pixhawk runs the same chip although has double the Flash memory). Granted, it doesn't have any sensors but man, that's find. Did I also mention that it works straight with arduino code. This means that I've upgraded to the most powerful MCU in the market at the same price as an Arduino Due . Wow! I overcame my shock by going to Robotics in Centurion and getting my hands on this dynamite. It can even run X-plane flight simulation controls in real-time communicating through the USB port! Ok enough ranting and raving! The point is now I can test the embedded algorithms on a similar ARM-based microcontroller as the Pixhawk and conclude the testing and validation up to HILS level with the sensors in the loop (while emulating th...