The idea behind this repo is to feed some of the West Balkan's UAV R&D engineers with the information they DESPERATELY tried to obtain from me (Y2010 up to nowadays). I have some obligations to keep some sensitive data at least for 20Y, but anyway, these days the UAV R&D went far fast forward from the Stone Ages of UAVs (in the 1980s and 1990s).
Remember, the first very primitive UAVs were invented by Nazi Germany in late 1930s/beginning of 1940s.
They were called V1, or FAU1 (German spelling of letter V):
[OFF Topic] Saturn V is a retired American super heavy-lift launch vehicle developed by NASA under the Apollo program. Some people call Saturn V as Saturn 5. Some: Saturn Fau (developed from V2 (Fau zwei).
Many of private companies, as well as military ones were mortally hypnotised/inspired with Tomahawk design from late 1990s, and the efficiency!
Since then, many HW and SW improvement were done to such kind of UAVs, especially in the HW VLSI fields (the silicon gate become to be very thin (14nm - 10nm), allowing very complex silicons (mainly SOCs) to be developed and manufactured.
Also the different controllers, especially gyroscopes and cameras were invented: 3D gyroscopes, ADIRUs, as well as LIDAR technology, allowing much more precise and far richer feature set.
Talking NOT only about Tomahawk missile, but also about modern UAVs, driven by AI (Artificial Intelligence), which uses Learning Algorithms based upon Neural Networks (with 10 of millions of neural reconfigurable nodes (given ULSI HW), each node with given specific logic).
I decided to do for free some google search/investigation and deliver for anyone/groups who is/are interested in UAV papers, articles and high level algorithms, www pointers to very complex flight controller databases/repos, which are serving as an useful codebase resources for the drone flight controller subsystem implementation.
Algorithms posted for free to boost the Development and Research (R&D) in the area of UAVs (Unmanned Areal Vehicles).
This I plan to do as a roling repo update (as Time allotted and opportunities allow).
Here are the base pointers to these documents (author's choice). Some of the documents in .pdf formats are posted in the same directory as this README.md document.
This paper describes the flight path planning for unmanned aerial vehicles (UAVs) based on the advanced swarm optimization algorithm of the bat algorithm (BA) in a static environment. The main purpose of this work is that the UAVs can obtain an accident-free, shorter, and safer flight path between the starting point and the endpoint in the complex three-dimensional battlefield environment. Based on the characteristics of the standard BA and the artificial bee colony algorithm (ABC), a new modification of the BA algorithm is proposed in this work, namely, the improved bat algorithm integrated into the ABC algorithm (IBA). The IBA mainly uses ABC to modify the BA and solves the problem of poor local search ability of the BA.
This paper explains heuristic algorithms, machine learning methodology, multi-UAV formation algorithms and trajectory planning.
As to have further understanding, the paper tries to explain Artificial Intelligence (AI) using all the above techniques.
Three dimensional stabilization controller based on improved quaternion transformation for fixed-wing UAVs.
In this paper, the methods of the stability theory of differential equations with time delays are used in the study of an actual engineering problem of a drone (UAV) autonomous flight. We describe correct operation of autopilot for supply stability of desirable drone flight. There exists a noticeable delay in getting information about position and orientation of a drone to autopilot in the presence of vision-based navigation (visual navigation). In spite of this fact, we demonstrate that it is possible to provide stable flight at a constant height in a vertical plane. We describe how to form relevant controlling signal for autopilot in the case of the navigation information delay and provide control parameters for particular case of flight.
This is the Open Source repo for the autopilot development.
It is mainly driven by Swiss company called Auterion:
On github:
Overall PX4 github repos' search:
For Building Flight Controller Products Pixhawk Autopilot Reference Standard:
On github:
MAVLink is a very lightweight messaging protocol for communicating with drones (and between onboard drone components).
I spent some few days of my time to get these, so I guess, these are destined to whom it may concern!
About Boeing MQ-2X and such of Life wonders/beauties! Please, address the concerns to the Boeing corporation:
Ghost Bat Is An Aircraft Like No Other:
About Reaper MQ-9 and such of Life wonders/beauties! Please, address the concerns to the General Atomics corporation:
How Air Force Drone Pilots "Fly" The $32 Million MQ-9 Reaper:
About MQ-8 and such of Life wonders/beauties! Please, address the concerns to the Northrop Grumman corporation:
About RQ-170_Sentinel (one captured by Iran), please, address the concerns to the Lockheed Martin corporation:
Many thanks for reading and understanding,
Author