Week 15 - No Improvement
Progress This Week
Objective
The objective was to achieve a well-functioning neural pilot. Although most attempts started well, with the vehicle taking curves correctly, they suddenly stopped turning and crashed into the wall.
Data
To improve the pilot, I acquired more data for training. It is important to note that the amount of data doubled due to data augmentation. Specifically, images were flipped along their vertical axis, and the angular speed was inverted. This not only doubled the data but also ensured a perfect balance between right and left curves. Training without this augmentation did not yield better results.
We have three different datasets:
Many Curves
This main dataset was taken on a circuit with many curves to both sides. It consists of 3522 pairs of images and velocity commands. The data distribution is as follows:
Simple Circuit
This dataset was generated on the circuit where we intend to test and compare the models. It has mainly been used to test the neural network after training, but also for training in some attempts. It consists of 1338 pairs of images and velocity commands. The data distribution is as follows:
Montreal Circuit
This dataset was generated on the Montreal circuit and consists of 1338 pairs of images and velocity commands. The data distribution is as follows:
Montmelo Circuit
This dataset was generated on the Montmelo circuit. It has not been used because the expert pilot did not perform consistently well. Furthermore, if we refer to past general models, we should not need additional data to make it work.
Training
I have made numerous attempts, changing the learning rate and the number and combination of datasets. However, I observed a tendency for the loss to plateau between 1 and 0.7 and not decrease further. This pattern is evident in the training curves:
The second curve is better but not satisfactory. In both cases, it can be seen that from epoch 50 onwards, there appears to be a horizontal asymptote.