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Flight data useful for training neural network

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Flight data useful for training neural network

Postby velikolay » Sat Aug 08, 2015 4:12 pm

Hello Team,

I would be happy if I can use Flight Gear for my master`s degree thesis. The basic idea is to create a fully automated landing system taking advantage of AI. I plan to use neural network(s) for doing the controlling part(pitch, roll, altitude, etc). For that purpose I need enough landing data(preferably under various weather conditions and terrains) in order to do the training of the model. Once I train the model(offline), I'll stream Flight Gear data to my neural network and then use it`s output to execute Flight Gear commands for controlling the plane.
Do you happen to know if such sample data is available? Any help/comment is highly appreciated.

Thanks!
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Re: Flight data useful for training neural network

Postby Johan G » Sat Aug 08, 2015 4:45 pm

velikolay wrote in Sat Aug 08, 2015 4:12 pm:Hello Team

Hello and welcome to the forum! :D

velikolay wrote in Sat Aug 08, 2015 4:12 pm:Do you happen to know if such sample data is available?

One of the easer ways, provided you can land a simulated aircraft yourself and have the time, would be to land in various conditions while logging properties you think are relevant.

Three FlightGear wiki articles that may be of help are: Property tree, Property browser and Logging properties.

One crucial question is what you intend to use for feedback to the AI. Are you going to use imagery, the ILS system, augmented GPS coordinates or something else? Many things are available in the property tree but not everything. :wink:
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Re: Flight data useful for training neural network

Postby velikolay » Sun Aug 09, 2015 5:29 pm

Thanks for your answer Johan!

The problem with me generating the data is that I'm not a good pilot that can serve as a reference for the AI. It`s crucial that the data contains a variety of landing scenarios(some of which non-trivial).

Regarding feedback: The neural network will take decisions in terms of control(e.g. roll right, pitch down, throttle increase), the feedback from the ILS and GPS is in terms of position rather than action(or at least I think so :)).
The data from the ILS and GPS will be still valuable - for instance the ILS asks for 3% horizontal angle, the plane is currently at 1% => the pilot commanded pitch up 2%. This could be a very simple training rule for the network.
What I'm missing here are the correct command from an experienced pilot.

I hope I explained it well. Please let know if I'm writing nonsense - it`s very likely :)
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Re: Flight data useful for training neural network

Postby GaelMisael47 » Wed Oct 07, 2020 9:31 am

@velikolay has this been resolved ? What did you learn from the project, I am currently doing a similar project and would like to know the outcomes and how you were able to use the Neural Network's output to to execute Flight Gear commands for controlling the airplane.
This is 5 years ago and for sure the FlightGear software is much different now.

Regards,
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Re: Flight data useful for training neural network

Postby Hooray » Wed Oct 07, 2020 10:08 am

Actually, believe it or not, the interfacing portion of the code that you need to control FlightGear, hasn't changed at all over the years - there's a well-defined set of I/O protocols and interfaces that can be used to accomplish this, which basically shields you from low-level changes in FlightGear itself.
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Re: Flight data useful for training neural network

Postby Johan G » Wed Oct 07, 2020 11:07 am

Indeed. A good starting point might be http://wiki.flightgear.org/Interfacing_FlightGear
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Re: Flight data useful for training neural network

Postby Hooray » Wed Oct 07, 2020 11:22 am

The OP wanted to use landing data from actual landings in FlightGear - the easiest way to obtain that would be to use a handful of airports/runways and different environmental settings, and then batch-run these in FlightGear while creating a recorded flight (fgtape), possibly using time-warp mode - at that point, dozens or even hundreds of fgtapes could be created automatically, and then post-processed using a neural network.

For example, imagine querying the navdb for ~10 airports, each having at least 3 runways (+ reciprocals), using 5 different weather scenarios, and 5 different aircraft, you'll quickly end up with hundreds of fgtape files in a semi-automated fashion.

You could even run a PID controller to fly each approach (sampling the surrounding terrain upfront to determine a MSA and suitable orientation to vector the aircraft)

Note that such a setup could even run FlightGear in headless mode, i.e. all you care about are the flight dynamics/terrain clearance and getting your hands on the sampled data (flight profile).

In summary, the kind of data you need is very much overlapping with the GCA/PAR add-on functionality:

http://wiki.flightgear.org/PAR_instrument
Image

Also, this is overlapping with the idea of creating a mission generator:

http://wiki.flightgear.org/FlightGear_M ... Adventures
Image

To speed up things even more, consider running the fdm (think jsbsim) in standalone mode.

Another option would be hooking up an observer script/module to gather flight data that way, and serialize it to disk - or even customizing a fgms fork along these lines.
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