I wrote about the simulated drone flying championship (or competition) some time ago. I wrote that why the simulated drone flying championship could be useful and from where I got the inspiration. What I did not write was the exact details of how it is going to work. In this article I am going to comprehensively explain how I think that the championship should work. It is quite easy. Just pay attention as you read the following details.
My inspiration for the simulated drone flying championship ensues from my interest in the simulated car racing championship. The latter competition is overseen and managed by the GECCO (Genetic and Evolutionary Computation conference) and the wider community of evolutionary algorithms practitioners.
The simulated car racing championship provides its participants a software which is essentially a simulation environment for racing cars, or car racing. The simulation environment has everything in it including environments for car racing, such as different types of laps on different types of terrains, different types of cars with different specifications etc. It also has a so called physics engine which emulates other environmental factors for the car racing simulator. The physics engine emulates real life factors such as aerial drag, road friction etc. It is important to take such factors into account so as to be able to emulate the car racing competition as close as possible to the reality.
The simulator can also be integrated with third party software through its programming interfaces. It is an open source project. And this is where the fun begins.
Competitors are invited to plug in and test their own software controllers for the racing cars. Design parameters for the software controllers are somewhat easy to understand conceptually as well. As a matter fact the simplest design goal is to come up with controllers that can help a car to win a race. That is quite simple to state and understand at this level.
And this is where the whole competition becomes a lot more fun. Machine learning, and specially chauvinists of evolutionary algorithms, try to solve this problem from a totally different perspective. And that is their perspective. And in order to understand their perspective you would have to understand either one of these disciplines in a bit more detail. Explaining machine learning or evolutionary algorithms is beyond the scope of this article. You can nonetheless read this tutorial to get a better understanding of evolutionary algorithms.
Stated shortly, the idea is to evolve a set of optimum controllers for the racing cars that would help the car win the competition. People have tried plenty of algorithms. One may as well cook up new algorithms along the way to design newer controllers. I shall explain how a set of controllers can be precisely evolved using an evolutionary algorithm in a subsequent article. Suffice it say for now that if you have understood the basic working of an evolutionary algorithm, you would not find it very hard to learn the whole idea behind the competition.
The simulated drone flying championship can also be designed in a similar way. There are plenty of simulators for drone flying available online. You can try either one of them. I have particularly liked UAV Playground. This is written in Java and can also be found on google. This is open source and quite modular. It also allows integration with third party software as well. It also emulates virtual reality quite well. You can integrate it with a machine learning package and try to design controllers for drone planes with simpler objectives. The objectives could be to fly a drone all over a place and perform some simple navigation. You can also use this package for genetic programming that I wrote myself for symbolic regression. This is written in java and works pretty well. Of course you are free to use your own software package and run it. And obviously everyone would have to try something different for this championship to work. If it all goes well and many people participate in it, the state of the art in drone industry could evolve pretty fast to sophisticated drones.
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