The goal of this project was to implement stereo vision in the Donkeycar framework using two USB cameras, training the neural network to drive our robot car around a track, and compare its performance to that of Donkeycar vehicle trained on the same track with only one camera.
Page still in progress.
Mounting USB Cameras to the Car
A 3D printed mount was created for the front of the car was created that would hold both USB cameras. The mount was designed so that the seats for both cameras would move as a single unit, pointing them at the same angle and minimizing the possibility of them pointing in different directions.
The mount also contains screw holes in the center that were intended to attach the original Picamera mount that we used earlier in the first half of the quarter. See the section "Possible Improvements" for more details on how this was meant to be used.
For a more accurate comparison of the performance between the stereo and mono regimes, we considered recording using the Picamera concurrently with the two USB cameras to record data through all three cameras simultaneously. This would ensure that both the stereo and mono models were trained in the same conditions with similar data, giving us a mono model that would act as a proper control group.