Demonstration code for running a small vehicle intersection with figure 8 loop using SLAM.
Get Started Fast:
Simulation:
To run the code in simulatuion mode (i.e. no real RC cars), simply run pip install -r requirements.txt and then python main.py. Enter target speeds for each of the 2 vehicles, this should be between 0 and 1 (units is meters per second) otherwise the control system will not be able to keep the vehicles on the track. Once there is a speed entered for both, click the "start test" button. The pause test will set the target speeds to 0 to temporarily pause the test. You can also update the target speeds in real time.
1/10 Scale Vehicles: To Install on physical Jetson hardware:
- Download the SD card image and upload to 64 GB SD card. This will save days of building the correct libraries, etc.
- TODO: Place google drive link here for Jetson TX2
- Clone this repo on the Home/Projects/ folder.
- TODO: Place google drive link here for Jetson Nano
In order to recognise the 1/10th scale vehicles you will need the retrained version of YoloV4 tiny. Be sure to download and add the following YoloV4 files into the darknet folder:
- yolov4-tiny-cav.cfg, needs to be located in /cfg
- cav.names, needs to be located in /data
- cav.data, needs to be located in /data
- yolov4-tiny-cav.weights, needs to be located in /weights
If you are interested in the data that was used to build this, you can find the 416x416 pictures converted for darknet here: Training Data. Over time this will increase in size as we add more data.
To run, type python main.py