Week 12 - Happy Birthday to Me
Summary
At the start of last weak I managed to destroy some important files for Ubuntu, which has ment that I have spent a weak reinstalling and re-testing everything. Luky for me the last time I followed my cordinator suggestions and uploaded most things to the repository (being datasets and models the exceptions). So I did not have to re-do most things. After completion I had a few problems I still don’t undertand and I managed to advance to fulfill the objectives setted last time.
Progress This Week
Objective
As stated in the last post the objective was to have an expert pilot that accelerated in straight lines. With this pilot we wanted to generate a single dataset to train a Neural and a TripleNeural pilot in order to be able to compare and decide if it was worth dividing the tasks between experts or if it was better to just have a general good pilot.
Expert Pilot
For the expert pilot I used the same I had used For the previous models, however this time I created a clasification sistem that had 3 outputs, when it was a hard curve, it used the same speed given by the PID, when it was an easy curve it multiplied it by 1.3 and when it was a straght line by 2.
This way we obtained a less precise (it had a bit of inertia and it somnetimes confused small curves with straght ones) but quite fast pilot that compleated the simple circuite (the one we will use to test for now) in 1 minute and 1 second.
You can see the video here: https://youtu.be/yMTMOGzndFk
General Neural Pilot
With the expert pilot done I recorded a dasest in the many curves circuit given that the curves are the hardest part for any pilot.
Afterwards I trained a pilot with the full set of data, achieving a General Neural Pilot that was tested in the simple circuit. This Pilot was faster and less precise than the general pilot we had before, but this was to be spected given that those same changes had been observed in the pilots that generated the datasets. However it had a safer behaviour and compleated the testing circuit in 1 minute and 18 seconds.
You can see the video here: https://youtu.be/4kDps2CMJWM
Triple Neural Pilot
This pilot would work as descrived in previous posts, having to experts and a selector to choose which to ask:
Curves expert
This expert was trained by using the same dataset as the general, but instead of balancing it, unbalancing it, which meand only picking those considered to be curves (easy or hard). The result was a net that could compleate the circuit alone in 1 minute 20 seconds. This is similar to the general one given that the training circuite had mostly curves, however in the videos you might apreciate the difference in straight lines.
You can see the video here: https://youtu.be/2WUf97NpPeQ
Straight lines expert
Similarly to the curves expert I used the same dataset, but just feeding the net with the straight line values, obtaining a crazy-for-speed net that could not pass the first curve of the circuit.
You can see the video here: https://youtu.be/hvcO9IyZAx0
Selector
The selector, has the last time, I trained it with the same dataset, but changeing the linear speed to 1 or 2 depending on the curve criteria I had followed in the other ones, leting it give me a range between both numbers. The closer the given number is to 1 the straighter it thinks the line to be. Which means that if I make the division in 1.5 it will be quite acurate, if I make it in 1.75 it will tend to accelerate more and in 1.25 it will try to not accelerate unless it is sure.
Result
The result (with 1.5) was a pilot that completed the testing circuit in 58 seconds. Being the faster yet, plus, although not adjusting to the red line, it clearly followed the circuit.
You can see the video here: https://youtu.be/E39KqsddeQA