/TriTorch

Primary LanguageJupyter Notebook

TriTorch - Jetracer build

Summary: TriTorch is a modified version of the Jetracer robot. Go to the develop branch to try out new features.

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Installation & Training Process

Step 0 - Flash your 64GB SD card with the TriTorch image:

TriTorch1p0.img

Step 1 - Connect a monitor, keyboard and mouse to your Jetson Nano and configure your WIFI settings.

  • right-click and open a terminal.
  • ifconfig
  • Check your IP address and take note.

Step 2 - Connect to your Jetson Nano with you local machine via Jupyterlabs:

  • Type in the IP address in the local machine webrowser.
  • http://#.#.#.#:8888/

Step 3 - Navigate to the working notebooks:

  • TriTorch/notebooks/
  • Start with interactive_regression.ipynb.
  • Convert model with torch2trt.ipynb.
  • Test model with TriTorch_run.ipynb.

FINISHED

Below are extra steps to improve data quality, but are not required.

Step 4 - Alternative data collecting:

  • Try out collect_images.ipynb and drive the car manually while it takes pictures. This will require post processing on your local machine with the postprocess_images.py file.
  • You can transfer these processed images back to your Jetson Nano to finish training or transfer to Google Colab.

Step 5 - Google Colab training:

  • Install Google Colaboratory for your Google drive.
  • Copy TriTorch_Colab folder to your Google Drive if you wish to utilize Google Colab GPUs.
  • Follow TriTorch_regression.ipynb to complete GPU training.
  • Transfer model to Jetson Nano to convert to trt and test model.

FINISHED

Jetracer Terminology:

Jetracer is a NIVIDA open source road following algorithm. It is software that can be used on any kind of car using a Jetson Nano GPU.

Jetsim is a folder containing the Jetracer algorithm but can can interface with the Donkeycar simulator. Triton AI has developed this desktop computer version to take it off the Jetson Nano.

"jetsim" Environment is the Jetracer environment for a desktop computer. Triton AI is developing this now so that Jetsim can run in this desktop virtual environments. This should be built using conda.

jetsim-local is the Jetsim local folder and needed files for a desktop computer. This will connect with your local Donkeycar simulator for driving manually and collecting data only.

jetsim-google-colab is the Jetsim folder and needed files for a Google Drive setup. This will allow you to train on Colab GPU's and connect you to the virtual race track to test and race your model.

Jetcard is a flashed image with the Jetracer environment. This is ONLY used for SD cards for the Jetson Nanos to run Jetracer.

Jetson Nano is a small developer kit CPU with CUDA GPU programming capabilites. It typically runs Ubuntu 18.04 on arm64. Most applications do not work on arm64.

gym-donkeycar is the OpenAI gym environment to interface a AI framewrok with the Donkeycar similator.

Donkeycar simulator like a video game, simulates a 3D car that can take control inputs and return images. This Jetsim will work with the latest version Race Edition 21.04.15